Industrial Engineering and Complexity Management - insisoc

10-12th july, 2013

&

2013

Spain

ICIEOM

XIX

7 th International Conference on Industrial Engineering and Industrial Management XVII Congreso de Ingeniería de Organización

2013

www.cio2013.org

Fundación General

INSISOC

S O C I A L S Y S T E M S ENGINEERING CENTRE

bpmsat

Business Solutions

ABEPRO

ASSOCIAÇÃO BRASILEIRA DE ENGENHARIA DE PRODUÇÃO

&

Project Management Technologies

Cátedra UVa

Asociación para el Desarrollo de la Ingeniería de Organización

Industrial Engineering and Complexity Management

Book of Abstracts of the

Managing Complexity: Challenges for Industrial and Operations Management.

Industrial Engineering and Complexity Management Book of Proccedings of the

ABEPRO



INSISOC



BOOK OF PROCEEDINGS 7th International Conference on Industrial Engineering and Industrial Management XVII Congreso de Ingeniería de Organización. Valladolid July 10-12th, 2013

Tittle/Título de la obra: “Industrial Engineering and Complexity Management”. Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización.

Executive Editors/Editores: Cesáreo Hernández Iglesias José M. Pérez Ríos Editorial Management / Coordinación editorial: Cristina Ruiz Martín David Jesús Poza García Iván Velasco Jiménez Grupo INSISOC Universidad de Valladolid Escuela de Ingenierías Industriales, sede Paseo del Cauce C/ Paseo del Cauce 59 47011 Valladolid (Spain) Printed / Imprimido

© Copyright, by the authors Legal Deposit/Depósito Legal: ISBN: 978-84-616-5410-9

Not authorized for further reproduction or distribution of any kind without prior permission from the authors. No está permitida la reproducción total o parcial, ni su tratamiento informático, ni la transmisión de ninguna forma o por cualquier medio, ya sea electrónico, fotocopia, registro u otro, sin permiso previo y por escrito de los autores.

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización.

Foreword and Welcome It is our honour to present the Proceedings of the 7th International Conference on Industrial Engineering, XVII Congreso de Ingeniería de Organización (CIO2013) and the XIX International Conference on Industrial engineering and Operations Management (ICIEOM). The CIO&ICIEOM 2013 is being organized by the INSISOC Group and the Industrial engineering School of the University of Valladolid. Following with the promotion of internationalization the Conference is the first joint event of ADINGOR (Asociación para el Desarrollo de la Ingeniería de Organización) and ABEPRO (Associaçâo Brasileira de Engenharia de Produçâo) the two main Spanish and Brazilian Scientific Societies in the field of Industrial and Management Engineering. The mission of the Conference is to promote links between researchers and practitioners from different branches to enhance an interdisciplinary perspective of industrial engineering and management. It is a forum to exchange ideas, academic and professional experiences to all branches of industries, information on the most recent and relevant research, theories and practices in Industrial Engineering, Management and Operations. The motto of the Conference “Managing Complexity: Challenges for Industrial and Operations Management” underlies the fact that in an open and global world, to handle complexity, cooperation is needed. We want to thanks the support given by the Cátedra Michelin of Industrial Organization and the Industrial Engineering School of the University of Valladolid. We also send our recognition to the keynote speakers for sharing with us their wisdom and experience and to the authors that sent their work for revision. Last but no least we gratefully acknowledge the hard and generous effort of those that took part in the peer-review process to maintain the high scientific level of the Conference series. And of course we do not forget the backstage work of the Scientific and Organizing Committees. We hope that the Conference will meet your expectations and will strength your professional and personal relations. We invite you to enjoy Valladolid, a name full of historical significance for the Spanish, Portuguese and Brazilian citizens, since the signing of the “Tordesillas Treatry” back in 1494. Best wishes, Valladolid, July 2013

Cesáreo Hernández Iglesias Chair of the Conference

José M. Pérez Ríos Chair of the Scientific Committee i


Organizing Committee Chair: Cesáreo Hernández Iglesias, Universidad de Valladolid Vice-chair: Adolfo López Paredes, Universidad de Valladolid Support crew: Fernando Acebes Senovilla, Universidad de Valladolid Alberto Araúzo Araúzo, Universidad de Valladolid Aldora Gabriela Gomes Fernandes, Universidad de Valladolid Mónica Iglesias Sanzo, Universidad de Valladolid Javier Pajares Gutiérrez, Universidad de Valladolid José M. Pérez Ríos, Universidad de Valladolid Marta Posada Calvo, Universidad de Valladolid David J. Poza García, Universidad de Valladolid Mario Ramírez Ferrero, Universidad de Valladolid Cristina Ruiz Martín, Universidad de Valladolid Pablo Sánchez Mayoral, Universidad de Valladolid Iván Velasco Jiménez, Universidad de Valladolid Félix A. Villafáñez Cardeñoso, Universidad de Valladolid Secretariat: Natividad Cabreros Martínez, Universidad de Valladolid Webmaster: Félix A. Villafáñez Cardeñoso, Universidad de Valladolid

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Scientific Committee Chair: José M. Pérez Ríos, Universidad de Valladolid, Spain Vice-chair: Francisco Soares Másculo, Universidade Federal da Paraíba, Brazil. Members: Segismundo S. Izquierdo Millán, Universidad de Burgos, Spain Jose M. Galán Ordax, Universidad de Burgos, Spain Angel Gento Municio, Universidad de Valladolid, Spain Jesús Gutiérrez Cillán, Universidad de Valladolid, Spain Juan Hernanagómez Barahona, Universidad de Valladolid, Spain Adolfo López Paredes, Universidad de Valladolid, Spain Miguel Ángel Manzanedo del Campo, Universidad de Burgos, Spain Natalia Martin Cruz, Universidad de Valladolid, Spain Gianni Mummolo, Politecnico di Bari, Italy Javier Pajares Gutiérrez, Universidad de Valladolid, Spain Marta Posada Calvo, Universidad de Valladolid, Spain Heitor M. Quintela Unisys, Brazil Alfonso Redondo Castán, Universidad de Valladolid, Spain Ana Isabel Rodríguez Escudero, Universidad de Valladolid, Spain Lourdes Saiz Bárcena, Universidad de Burgos, Spain José Ignacio Santos Martín, Universidad de Burgos, Spain Luis Felipe Scavarda, PUC-Rio, Rio de Janeiro, Brazil Markus Schwaninger, Univ. of St.Gallen, Institute of Management, Switzerland Tom Taylor, President of Association for Project Management (APM), UK Milton Vieira Junior, UNINOVE, Brazil Referees: María del Mar Eva Alemany Díaz Universitat Politècnica de València, Spain Rui Manuel Alves Silva Sousa DPS - UMINHO, Portugal Dilanthi Amaratunga University of Salford, UK Antonio Andrade Dias President of APOGEP, Portugal Carlos Andrés Romano Universitat Politècnica de València, Spain Madalena Araújo DPS - UMINHO, Portugal José Dinis Araújo Carvalho DPS - UMINHO, Portugal Eugenia Babiloni Universitat Politècnica de València, Spain Bopaya Bidanda University of Pittsburgh, USA Andrés Boza García Universitat Politècnica de València, Spain v


Agostino Bruzzone University of Genova, Italy Luis Camarinha Matos Uninova, Portugal Francisco Campuzano Bolarín Universidad Politécnica de Cartagena, Spain Manuel Cardós Carboneras Universitat Politècnica de València, Spain Javier Carrasco Arias Universidad Politécnica de Madrid, Spain Vagner Cavenaghi UNESP - Bauru, Brazil Juan Gabriel Cegarra Navarro Universidad Politécnica de Cartagena, Spain Ernesto Cilleruelo E.T.S. de Ingeniería de Bilbao, Spain José A. Comesaña Benavides Universidad de Vigo, Spain Ramón Companys Pascual Universitat Politècnica de Catalunya, Spain Albert Corominas Subias Universitat Politècnica de Catalunya, Spain Pablo Cortés Achedad Universidad de Sevilla, Spain Anna M. Coves Moreno Universitat Politècnica de Catalunya, Spain José Crespo de Carvalho ISCTE, Portugal Virgilio Cruz Machado Uninova, Portugal Lluís Cuatrecasas Arbós Universitat Politècnica de Catalunya, Spain Llanos Cuenca Gonzalez Universitat Politècnica de València, Spain Ricardo Chalmeta Rosaleñ Universidad Jaume I, Spain Jens J. Dahlgaard Linköping University, Sweden Valério de Carvalho DPS - UMINHO, Portugal María Victoria De la Fuente Aragón Universidad Politécnica de Cartagena, Spain David Alfonso De la Fuente García Universidad de Oviedo (EPI GIJON), Spain Carmen De Nieves Nieto Centro Universitario de la Defensa (CUD), Spain Ricardo Del Olmo Martínez Universidad de Burgos, Spain Pablo Díaz de Basurto Uraga Universidad del País Vasco, Spain Silvio do Carmo Silva DPS - UMINHO, Portugal Alfonso Durán Heras Universidad Carlos III, Spain Enda Enda Fallon NUI, Ireland Ander Errasti Opacua Centro de Estudios e Inv. Técnicas de Guipúzcoa, Spain Sofía Estellés Miguel Universitat Politècnica de València, Spain Vicenç Fernández Alarcón Universitat Politècnica de Catalunya, Spain Arturo José Fernández González Universidad de Vigo, Spain Isabel Fernández Quesada Universidad de Oviedo, Spain Paulo Ferrão Director do MIT Portugal, IST-Portugal Adriana Ferreira de Faria UFV, Brazil Rui Francisco M. Marçal PUC-PR, Brazil Jose M. Galán Ordax Universidad de Burgos, Spain Jesús García Arca Universidad de Vigo, Spain José Pedro García-Sabater Universitat Politècnica de València, Spain Angel Gento Municio Universidad de Valladolid, Spain Sergio Eduardo Gouvea da Costa PUC-PR, Brazil Gonzalo Grau Gadea Universitat Politècnica de València, Spain Gil Gutiérrez Casas Universidad Carlos III, Spain vi


Jesús Gutiérrez Cillán Universidad de Valladolid, Spain Cesáreo Hernández Iglesias Universidad de Valladolid, Spain Antonio Hidalgo Nuchera Universidad Politécnica de Madrid, Spain Eloy Hontoria Hernández Universidad Politécnica de Cartagena, Spain M. Carmen Jaca García Universidad de Navarra, Spain Segismundo S. Izquierdo Millán Universidad de Burgos, Spain Tomasz Janowsky UNU-IIST, Macau Kalle Kähkönen Tampere University of Technology, Finland Franz-Josef Kahlen University of Cape Town, South Africa Katja Klingebiel Technische-Universität Dortmund, Germany Francisco Cruz Lario Esteban Universitat Politècnica de València, Spain Gilson Lima Universidad Federal Fluminense, Brazil Rui M. Lima DPS - UMINHO, Portugal Adolfo López Paredes Universidad de Valladolid, Spain Amaia Lusa García Universitat Politècnica de Catalunya, Spain Julient Maheut Universitat Politècnica de València, Spain Anna-Bella Manalang De La Salle University (DLSU), Philippines Miguel Ángel Manzanedo del Campo Universidad de Burgos, Spain Juan A. Marin-Garcia Universitat Politècnica de València, Spain Natalia Martin Cruz Universidad de Valladolid, Spain Eva Martínez Caro Universidad Politécnica de Cartagena, Spain Carme Martínez Costa Universitat Politècnica de Catalunya, Spain Francisco Soares Másculo Universidade Federal da Paraíba, Brazil Manel Mateo Doll Universitat Politècnica de Catalunya, Spain Ana María Mejías Sacaluga Universidad de Vigo, Spain Pedro Mondelo Universitat Politècnica de Catalunya, Spain Josefa Mula Bru Universitat Politècnica de València, Spain Gianni Mummolo Politecnico di Bari, Italy Jesús Muñuzuri Sanz Universidad de Sevilla, Spain Luis Onieva Giménez Universidad de Sevilla, Spain Ángel Ortiz Bas Universitat Politècnica de València, Spain Sergio Palomero Ródenas Universidad Jaume I, Spain Javier Pajares Gutiérrez Universidad de Valladolid, Spain Juan E. Pardo Froján Universidad de Vigo, Spain Edson Pinheiro de Lima PUC-PR, Brazil Raúl Poler Escoto Universitat Politècnica de València, Spain Eva Ponce Cueto Universidad Politécnica de Madrid, Spain Marta Posada Calvo Universidad de Valladolid, Spain José Carlos Prado Prado Universidad de Vigo, Spain Bernardo Prida Romero Universidad Carlos III, Spain Goran Putnik DPS - UMINHO, Portugal Heitor M. Quintela Unisys, Brazil Shahin Rahimifard Loughborough University, UK vii


Alfonso Redondo Castán Universidad de Valladolid, Spain Imma Ribas Vila Universitat Politècnica de Catalunya, Spain Ana Isabel Rodríguez Escudero Universidad de Valladolid, Spain Carlos Rodriguez Monroy Universidad Politécnica de Madrid, Spain Luiz Felipe Roriz R. Scavarda do Carmo PUC-RIO, Brazil Diego Ros McDonnell Universidad Politécnica de Cartagena, Spain Lorenzo Ros McDonnell Universidad Politécnica de Cartagena, Spain Patxi Ruiz de Arbulo López Universidad del País Vasco / EHU, Spain Rui Manuel Sá Pereira Lima DPS - UMINHO, Portugal Rashed Sahraeian Shahed University, Tehran, Iran Lourdes Saiz Bárcena Universidad de Burgos, Spain Javier Santos Universidad de Navarra, Spain José Ignacio Santos Martín Universidad de Burgos, Spain Luis Felipe Scavarda PUC-Rio, Rio de Janeiro, Brazil Markus Schwaninger Univ. of St.Gallen, Institute of Management, Switzerland M. Val Segarra Oña Universitat Politècnica de València, Spain Pep Simó Guzmán Universitat Politècnica de Catalunya, Spain Rui Sousa Universidade Católica Portuguesa, Portugal Ana Suárez Sánchez Universidad de Oviedo, Spain Gursel A. Suer Russ College of Eng. & Technology, Ohio University, USA Josu Takala University of Vaasa, Finnland Tom Taylor President of Association for Project Management (APM), UK Senhorinha Teixeira DPS - UMINHO, Portugal Guilherme L. R. Vaccaro UNISONOS, Brazil Jaume Valls Pasola Universidad de Barcelona, Spain Ton van der Wiele Erasmus University, The Netherlands Mario Vanhoucke Ghent University, Belgium María José Verdecho Sáez Universitat Politècnica de València, Spain Eduardo Vicens Salort Universitat Politècnica de València, Spain Milton Vieira Junior UNINOVE, Brazil

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Proceedings Index English Tracks ..................................................................................................... 13 EN-01 Strategy and Entrepreneurship .............................................................. 15 A Valuation of SAREB, the Spanish “Bad Bank”, Upside Using the Real Options Methodology .......................................................................................... 17 Roux Martínez F, Ruiz López F, Eguren S

Corporate Entrepreneurship: Types and Determinant Factors. A Case Study Based Analysis of Technology Based and R+D Active Companies. ................ 25 Onaindia E, Goyogana U, Ochoa Laburu C

The impact of innovation management techniques on radical innovation: An empirical study .................................................................................................... 33 Igartua J.I, Errasti N, Ganzarain J

An Empirical Analysis of the Spanish Gas Price Structure ............................. 42 Cansado P, Rodríguez Monroy C

Capabilities Generation Mechanisms in Alliances. Case Based Analysis ....... 50 Morcillo Bellido J, Duran Heras A

Best Practices in Sustainable Supply Chain Management: A Literature Review .................................................................................................................. 59 Mejías A.M, Pardo J.E

State of the Art of Challenges on International Operations Management for SMEs..................................................................................................................... 67 Martínez S, Mediavilla M, Errasti A, Santos J, Mula J

Economic and Financial Profile of High-Growth Firms vs. Normal Firms from New Industry in the Basque Country: a Discriminant Analysis ............ 76 Ruiz de Arbulo P, Landeta B, Basañez A, Insunza G, Gonzalez X

High-growth Firms: Qualitative Analysis Via Case Study .............................. 85 Insunza Aranzeta G, Basañez Llantada A, Ruiz de Arbulo López P, Landeta Manzano B, González Laskibar X

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Analysis and Characterisation of the High-growth Firm in the Basque Country ................................................................................................................ 94 Gonzalez X , Ruiz de Arbulo P, Landeta B, Basañez A, Insunza G

The Delphi Method Applied for Validates the Regional Innovation Model. Case Study Applied in Central Region Romania. ........................................... 102 Moica S, Ganzarain J

Regional Strategic Development Method as a Tool for the Emergence of New Industries at Regional Level ............................................................................. 111 Ganzarain J, Igartua J.I , Markuerkiaga L

Costing a Product by Old and New Techniques: Different Wines for Different Occasions ............................................................................................................ 120 Ruiz de Arbulo López, P, Fortuny-Santos, J, Vintró-Sánchez, C

An Electric Taxi Fleet Charging System Using Second Life Electric car Batteries Simulation and Economical Approach ............................................ 129 Canals Casals Ll, Amante B

Decision Tool Based on Cloud Computing Technology ................................. 137 Zabalza-Vivanco J, Rio-Belver R, Cilleruelo E, Acera-Osa F.J, Garechana G

Productivity in Knowledge Worker Teams ..................................................... 146 Moreno A, Varanki H, Mahou A.

Return of Equity Issues in the Spanish Stock Market from the Investor’s Perspective, during the 1997-2012 Period ....................................................... 154 Parreño J, Ruiz F, Roux F

Sustainable Balanced Scorecard: Practical Application to a Services Company ............................................................................................................ 163 Redondo A, Pascual J.A, Gento A, Muñoz J

Applying Cluster Analysis to Renewable Energy Emergent Sector at Local Level ................................................................................................................... 172 Larruscain J, Río-Belver R, Cilleruelo E, Garechana G, Gavilanes-Trapote J

Application of Reverse Innovation in SMEs ................................................... 180 Garcia Miranda I, Duran Heras A, Giraldo Casado E

Analysis of the Electric Car Via Patents ......................................................... 189 Fernandez de la Bastida E, Gavilanes-Trapote J, Río-Belver R, Cilleruelo E, Larruscain J

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Quality in a Small Service Organization and its Relation with Sand Cone Model .................................................................................................................. 197 Braga C, Migowski S, Libânio C, Spindler G, Duarte F

CBA and CEA Analysis on Occupational Safety and Health. A New Proposal for Investment Decisions ................................................................................... 209 Cuervo MA

New Technologies and Entrepreneurial Intention .......................................... 221 Martin-Cruz N, Rodriguez-Escudero AI

EN-02 OR, Modelling and Simulation ............................................................. 233 Toward Various Exact Modeling the Job Shop Scheduling Problem for Minimizing Total Weighted Tardiness ............................................................ 235 Namakshenas M , Sahraeian R

Two Simple Constructive Algorithms for the Distributed Assembly Permutation Flowshop Scheduling Problem ................................................... 245 Hatami S, Ruiz R, Andrés Romano C

Set-up Continuity in Tactical Planning of Semi-continuous Industrial Processes ............................................................................................................. 253 Pérez D, Alemany M.M.E, Lario F.C , Fuertes V.S

Literature Review of Master Planning Models with Lack of Homogeneity in the Product Characteristics under Uncertainty Context ............................... 262 Mundi I, Alemany M.M.E, Poler R, Fuertes V.S

A MILP Model for the Scheduling of Non-continuous Serial Multi-product Multi-stage Batch Processes with Non-identical Machines. ........................... 271 Latorre F, García-Sánchez A, Méndez C, Aguirre A, Ortega-Mier M

NTIGen: a Software for Generating Nissan Based Instances for Time and Space Assembly Line Balancing ....................................................................... 281 Chica M, Cordón O, Damas S, Bautista J

Agent-based Modelling and Archaeological Complexity ............................... 289 Poza D, del Olmo R

Optimizing Stochastic Supply Chains via Simulation: What is an Appropriate Simulation Run Length? ................................................................................... 297 Arreola-Risa A, Fortuny-Santos J, Vintró-Sánchez C

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Localization Based on Business Interactions through a Simulated Annealing Algorithm ........................................................................................................... 306 Sánchez R.M, Galán J.M, Santos J.I

Applications of the Lagrangian Relaxation Method to Operations Scheduling315 Laviós-Villahoz J.J ,Arauzo J.A, del-Olmo-Mártinez R, Manzanedo-del-Campo M.A,

Methodology for the Strategic Capacity Planning in Universities ................ 324 de la Torre R, Lusa A, Mateo M

A MILP Event Based Formulation for a Real-world Multimode RCSP with Generalized Temporal Constraints.................................................................. 332 Borreguero T, García A, Ortega M

A Model of Makespan Flow-shop Scheduling under Ergonomic Requirements ..................................................................................................... 341 Asensio-Cuesta S, Gomez-Gasquet, P, Andrés C, Alemany M.M.E

Solving the Car Resequencing Problem with Mix Banks .............................. 354 Valero-Herrero M, Garcia-Sabater J.P , Vidal-Carreras P, Canos-Daros L

Gaia Analysis and Design of a Multi-agent-based Shop Floor Control System363 Arauzo J.A, del-Olmo-Mártinez R, Labiós-Villahoz J.J

Estimating Costs in the EOQ Formula ............................................................ 372 Vidal-Carreras P.I, Garcia-Sabater J.P, Valero-Herrero M, Santandreu-Mascarell C

Integrated Production and Simulation Scheduling Tool to Solve the Mix Model Assembly Line Problem Considering Heijunka and Operational Constraints: a Case Study ................................................................................ 381 Maheut J, Garcia-Sabater J.P, Garcia-Sabater J.J

Electrical Markets and Agent-Based Computational Economics: a Critical Review of the Last Two Decades of Researching ............................................ 389 Ferrero R

The Inventory Routing Problem for the Mixed Car Model Assembly Line. 398 Pulido R, García-Sánchez A, Ortega-Mier M

EN-03 Logistics, Production and Information Systems ................................. 407

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Solving the Mixed Model Sequencing Problem with Workload Minimization with Product Mix Preservation ........................................................................ 409 Bautista J, Cano A, Alfaro R, Batalla C

Enhanced Supply Chain Management Using SCOR and BPM. Application to the Spanish Road Transport SME. .................................................................. 418 Franconetti P, Ortiz A

Incorporating the Work Pace Concept into the MMSP-W ............................ 427 Bautista J, Alfaro R, Batalla C, Cano A

Impact of Ergonomic Risk Reduction in the TSALBP-1 ................................ 436 Bautista J, Batalla C, Alfaro R, Cano A

Order Promising Process for Supply Chains with Lack of Homogeneity in the Product ............................................................................................................... 445 Alemany MME, Boza A, Ortiz A, Poler R

Modeling the Master Plan for Supply Chains with Lack of Homogeneity in the Products ....................................................................................................... 454 Alemany MME, Cuenca L, Ortiz A, Pérez D

A Design Framework for Flexible Automated Warehouses .......................... 463 Marín L.F., Carrasco-Gallego R

Supplier Evaluation and Selection: a Review of the Literature since 2007 .. 472 Moliné JI, Coves AM

A “Collaborative Me” Crossroad: Individual Beliefs and the Adoption of Corporate Blogs ................................................................................................. 481 Fernández-Cardador P, Hernández-García A, Iglesias-Pradas S

Improving the Distribution Process in a Meat Company .............................. 490 Pérez I,Ulabarry L. E, Moreno K,Parra C

A New Constructive Heuristic for the Fm|Block|∑T ...................................... 500 Companys R, Ribas I

A Roadmap to Establish Collaboration among SMEs belonging to NonHierarchical Networks ...................................................................................... 508 Andres B, Poler R

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Measures to Diagnose the Power Balance in a Non-hierarchical Manufacturing Network ................................................................................... 517 Andres B, Poler R

New Tool for Aiding Warehouse Design Process ............................................ 526 Chackelson C, Errasti A, Santos J

Calculation of the Approaches to CSL in Continuous Review Policy (s,Q) from an Analogy of a Periodic Review Policy (R,S). ...................................... 534 Estelles-Miguel S, Albarracin J.M, Cardós M, Guijarro E.

Determining the Order-up-to-level Using the Normal Approximation in a Discrete Context ................................................................................................ 543 Guijarro E, Babiloni E, Cardós M, Palmer M

On the Selection of Customer Service Metrics in Inventory Control ........... 551 Guijarro E, Babiloni E, Cardós M, Estellés S

Analysing the Purchase Intention of Spanish Consumer: A Study about Remanufactured Products ................................................................................ 560 Jiménez-Parra B, Rubio S, Vicente-Molina M A

Non Parametric Estimation of the Cycle Service Level of a Periodic Review Policy in a Discrete Context .............................................................................. 568 Cardós M, Babiloni E, Estellés S, Guijarro E

Proposal of a Classification of the Different Data Models to Manage Materials in Industry ........................................................................................ 576 Maheut J, Garcia-Sabater JP, Marin-Garcia JA

Packaging Logistics. A Case Study in Dairy Sector ....................................... 585 García Arca J, Prado Prado JC, González-Portela Garrido A.T

Inter Enterprise Framework for Hierarchical Decisions ............................... 594 Vargas A, Boza A, Cuenca L, Ortiz A

Enterprise Resilience Assessment: A Categorisation Framework of Disruptions ......................................................................................................... 603 Sanchis R, Poler R

Trajectory Analysis of the Valencian Automobile Industry Implementing Lean Management ............................................................................................. 611 Valero-Herrero M, Marin-Garcia J , Garcia-Sabater J, Vidal-Carreras P

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Long Term Capacity Planning with Products’ Renewal ............................... 620 Yilmaz G, Lusa A, Benedito E

Multiagent Model for Supply Chain Management ......................................... 630 Ponte B, Pino R, Fernández I, García N, Monterrey M

Revisiting the SEC Classification Framework in Traditional and Electronic Commerce .......................................................................................................... 639 Agudo-Peregrina AF, Chaparro-Peláez J, Pascual-Miguel FJ

Utilization of Tool Value Stream Mapping (VSM) for Improvement of Welded Assembly Manufacturing Process ...................................................... 647 Guimarães G, Muller M, Taffarel L, Lash M, Bechert T

Logistic Management in a Fresh Food Firm: A Case Study .......................... 655 García Márquez F.P, Peña García-Pardo I, Trapero Arenas J.R

City Logistics: Are Sustainability Policies Really Sustainable? .................... 665 Grosso R, Muñuzuri J, Cortes P, Carrillo J

A Model for Coordination of Production Planning, Forward and Reverse Logistics Management in a Multi-product and Multi-plant Environment, with Reusable Bottles Constraints ................................................................... 674 Parra Peña J, Vicens-Salort E, Ortiz Bas A

Neural Network Application for Risk Factors Estimation in Manufacturing Accidents. ........................................................................................................... 683 Carrillo JA, Guadix J, Grosso R, Onieva L

EN-04 Quality and Product Management ....................................................... 691 Information Capability in Basque Country Quality Award Winners .......... 693 Zárraga-Rodríguez M, Álvarez MJ

Market Oriented New Product Development Process: a Case Study ........... 702 Nunes M, Afonso P

The Logical Framework Approach and Worker Commitment .................... 720 Paipa-Galeano L, Jaca C, Viles E, Mateo R, Santos J

How to Choose the Best Order when Implanting HIWP in Operations Area728 Marin-Garcia JA, Perello-Marin MªR, Canos-Daros L, Valero-Herrero M

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EN-05 Knowledge and Project Management .................................................. 737 Competitive Intelligence Practices in Microenterprises and SMEs from the Industrial Sector: the Case of Basque Country .............................................. 739 Aldasoro J C, Cantonnet M L, Cilleruelo E

Web 2.0 as a Key Tool for Sharing Knowledge in Basque Country SMEs .. 747 Alvarez Meaza I, Cilleruelo Carrasco E, Zamanillo Elguezabal I

Predisposition of Workers to Share Knowledge: an Empirical Study .......... 755 Sáiz L, Díez J I, Manzanedo, M A, Del Olmo, R

User Software and Information Systems in Engineering Project Management763 Arias J, Rubio R, Solana J

Application of Public Private Partnerships to the Spanish Airport System 772 Coello N, Rodríguez Monroy C, Calvo F

Towards Strategic Project Management ......................................................... 780 Hermano V, Martín-Cruz N.

Analysis of Common Maturity Models Applied to Project Management .... 788 Montero G

Patterns in Innovative Companies in Rio de Janeiro (Brazil) ....................... 795 Canós-Darós L, Santandreu-Mascarell C, Marin-Garcia JA, García-Sabater JJ

How Organizational Cybernetics Can Help to Organize Debates on Complex Issues................................................................................................................... 803 Pérez Ríos J, Velasco Jiménez I, Sánchez Mayoral P

The M.A.G. Factor. Management, Administration and Guidance. Where and How Much MAG Does Each Project Deserve and Need? A New, Original Assessment and Scoring System ....................................................................... 813 Taylor T

EN-06 Service Systems ...................................................................................... 823 Tourism Destination Web Monitor: A Technological Platform for the Acquisition of Tourist Information through the Web Presence of the DMOs825 Rebon F, Gerrikagoiti J.K, Ochoa Laburu C

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Methodology for Analysis and Decision Making by Sampling in Buildings. 833 Aparicio P, Guadix J, Onieva L, Escudero A

E-Government Interoperability Frameworks: Administration to Business. 842 Andres B, Poler R

Economic Performance and Financial Profitability: Two Study Cases in F&B Industry .............................................................................................................. 851 Santandreu-Mascarell C, Canós-Darós L, Vidal-Carreras PI, Valero-Herrero M

Appropriate Work Design in Lean Production Systems ................................ 858 Dombrowski U, Hellmich E-M., Mielke T.

Model of a Public Private Partnership in the Spanish Health Context ........ 867 Pérez J

Complex Networks Applied to Communication Management in Emergency Crisis ................................................................................................................... 876 Ruiz Martín C, Ramírez Ferrero M, González Álvarez J.L, Poza D

EN-07 Education................................................................................................ 885 Applying the LEGOstics Concept in Formal Education at Technical University of Cartagena .................................................................................... 887 Bojan P, de la Fuente Aragón MV, Ros McDonnell L

Teaching Operation Management with GeoGebra. An example of Make-tostock Problem Solving ....................................................................................... 895 Calona Z, Santos J, Arcelus M

Factors Involved in the University-industry Collaboration; a Final YearProject Approach ...................................................................................... 903 Errasti N, Ganzarain J, Markuerkiaga L, Martinez de Zuazo M

How to Assess the Innovation Competency of Higher Education Students . 912 Marin-Garcia JA , Perez-Peñalver MªJ, Vidal-Carreras PI, Maheut J

Using Rubrics for Monitoring and Evaluating Degree Projects in Industrial Management Engineering ................................................................................. 921 Barbera-Ribera T, Estelles-Miguel S, Dema Perez C.M, Garrigos-Simon F.J.

Spanish Tracks .................................................................................................. 931

9


SP-01 Estrategia y Entrepreneurship .............................................................. 933 La Satisfacción de Clientes como Estrategia de Marketing para la Venta... 935 Dalongaro R.C, Froemming L.M.S

La Importancia de las Innovaciones No Tecnológicas en las Empresas Españolas ........................................................................................................... 943 Larrea Unzain A, Aldasoro Alustiza J.C, Cantonnet Jordi Mª L

Open E-Government y Cambios Organizativos en las Administraciones Públicas Españolas ............................................................................................ 951 Martínez Núñez M , Pérez Aguiar WS, Martin-Fernandez L

Análisis de Buenas Prácticas en Transferencia Tecnológica en el Sector TIC966 Artal A., Sanchez Granados A.M., Gil Garcia E.

SP-02 Investigación Operativa, Modelado y Simulación ............................... 975 Comparativa de Heurísticas Multiobjetivo Voraces y Poblacionales Aplicadas a la Optimización Mono-objetivo en Entornos Industriales Flow Shop con Permutación ....................................................................................................... 977 Valledor P, Gómez A, Díaz D, Priore P, Rosillo R

Estudio sobre el Efecto de la Complejidad e Incertidumbre en el ELSP ..... 986 Cortés R, García-Sabater J.P, Molina P

SP-03 Logística, Producción y Sistemas de Información ............................... 997 Mejora del Sistema Productivo mediante Value Stream Mapping. Aplicación a una Empresa de Diseño .................................................................................. 999 De la Fuente MV, Alonso M, Hontoria E, Ros L

Sistema Integrado de Planificación de la Producción y Distribución para la Gestión de Excepciones ................................................................................... 1007 Álvarez E, Villalón L, Osaba E, Díaz F

Técnicas de Predicción Cuantitativas Aplicadas a la Cadena de Suministro. Un Caso de Estudio ......................................................................................... 1016 Trapero Arenas J.R , García Márquez F.P

Decisiones en el Diseño de Redes de Logística Inversa: Propuesta de un Modelo de Decisión. ......................................................................................... 1025 Ribas I, Rubio S

10


La Mejora Dinámica del Rutado de Vehículos: Eventos de Reoptimización1034 Escudero A, Muñuzuri J, Cortés P, Aparicio P

Sistemas de Ayuda a la Toma de Decisiones para la gestión de Incidencias1043 Valero R, Boza A, Vicens E

Sistema de Control y Reprogramación de la Producción basado en Captura Inalámbrica de Datos en Planta ..................................................................... 1050 Eguizábal L, Lago A, Fernández A

Planificación y Control de la Producción en la Mejora del Proceso de Producción de Fabricación de Juegos Mesas: un Estudio de Caso ............. 1060 RaposoJ, Costa-de MatosAN, NunesA

SP-04 Calidad y Gestión del Producto ........................................................... 1069 Las Empresas de Servicios Energéticos (ESE) en España y su contribución al desarrollo de las Ciudades Inteligentes (Smart Cities) .................................. 1071 Morcillo Bellido J, Prida Romero B

El Análisis del Ciclo de Vida en España. Temas de Investigación Principales y Agentes Clave ................................................................................................... 1080 Basañez Llantada A, Martínez de Alegría Mancisidor I, Insunza Aranzeta G, González Laskibar X

Un Sistema Integrado de Gestión como Elemento de Mejora Competitiva 1089 Fortea E, Mikeo I

Modelo para la Implementación de Sistemas de Gestión Preventivos en Sectores Singulares .......................................................................................... 1097 Solano Martos J, Maeso González E

SP-05 Gestión del Conocimiento y de Proyectos ........................................... 1107 Estimación de la Evolución de Proyectos en el Ámbito de la Producción Industrial mediante la Parametrización de la Curva S del Coste Acumulado1109 García Escribano E

Aprendizaje Organizacional: Estudio de Caso Sector Turismo de Ciudad Guayana, Venezuela ........................................................................................ 1118 D’Armas M, Arzola M

11


Gestión de la Innovación y el Papel de las TIC: El caso de SILK ............... 1128 Planuch Prats C, Salvador Vallès R

La Intragestion Financiera a través de las TIC Basada en la Auditoria de Orden del Sector Universitario Venezolano .................................................. 1137 Guaido Suarez D

SP-06 Sistemas de Servicios ............................................................................ 1143 La Calidad de E-Servicio en Portales Web B2C: Evaluación Mediante Sistemas de Inferencia Borrosos .................................................................... 1145 Castro A, Puente J, de la Fuente D, Parreño J, Lozano J

SP-07 Educación .............................................................................................. 1155 Tendencias y Aseguramiento de la Calidad en la Educación Superior: Mapa Europeo y Caso de España ............................................................................. 1157 Gonzalez Lasquibar X, Ruiz de Arbulo López P, Landeta Manzano B, Basañez Llantada A, Insunza Araceta G

Satisfacción en la Utilización del Video por el Discente en su Proceso Activo de Aprendizaje. Una Experiencia en el Contexto de los Grados en Ingeniería de Telecomunicación. ...................................................................................... 1167 Pérez-Aguiar W, Martínez-Núñez M

Aplicación de la Tecnología BPMS en la Gestión de los Procesos Relacionados con la Actividad Docente en un Centro Universitario .................................. 1178 Pardo JE , Mejías AM

12


English Tracks

13


EN-01 Strategy and Entrepreneurship

15


A Valuation of SAREB, the Spanish “Bad Bank”, Upside Using the Real Options Methodology Roux Martínez F1, Ruiz López F2, Eguren S3 Abstract This paper develops a model to analyze the upside potential of profitability of the SAREB (“Asset Management Company for Assets Arising from Bank Restructuring”), the Spanish “Bad Bank”. The model is based in the Real Options methodology, that is especially adequate due to the convergence of two elements, (i) depreciated assets with a high upside potential, and (ii) a highly volatile market as it has shown to be the real estate Spanish market. Our results suggest that the SAREB has a higher than expected profitability potential that would be dedicated to increase the return to its shareholders, mainly private banks. Consequently we also show that after the financial crisis are emerging two types of banks in Spain, in one hand the losers who are transferring their real estate assets at a deep discount, and in the other hand the winners, capturing the upside potential of those assets as shareholders of SAREB, and consequently consolidating their strength in the Spanish Real Estate Industry. It is worth to mention that Governments should make an effort in properly redistribute the wealth generated by the real Estate industry.

Keywords: Bad Bank, Real Options, Valuation, Financial Crisis, Real Estate.

1Félix

Roux Martinez ( e-mail: [email protected]) Dpto. de Administración de Empresas. Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2. 28006 . Madrid

2Félipe

Ruiz López ( e-mail: [email protected]) Dpto. de Administración de Empresas. Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2. 28006 . Madrid 3Santos

Eguren ( e-mail: [email protected]) Dpto. de Administración de Empresas. Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2. 28006 . Madrid

17


1 SAREB Overview and Background

1.1 Legal Structure On 25 June 2012, Spain requested the Eurogroup financial assistance to recapitalize the Spanish banking industry. In accordance with this request, the Spanish Administration created the SAREB to segregate impaired financial assets “toxic assets” of those credit institutions receiving public funding. The legal structure of the SAREB was defined in RDL 24/2012, now passed as law 9/2012. The SAREB will be incorporated for a maximum period of 15 years, and initially as a Public Limited Company (Spanish “Sociedad Anónima”). The purpose of the SAREB is the holding, management, acquisition and disposal of assets to be transferred to it by credit institutions receiving public support. These institutions receive debt securities issued by the SAREB with a State guarantee as payment for the assets transferred. (European Central Bank, 2012) In a second phase starting by 2013, the SAREB eventually will set up a number of funds and a management company, to create and finance portfolios of assets in response to specific investor demand.

1.2 Funding Required, Capital Structure and Cost of Capital. SAREB shareholders are mixed, Public and Private, Public ownership may not exceed 50% (BOE, Ley 9/2012) to prevent SAREB debt to consolidate as public debt increasing the total amount of Spanish debt outstanding. In any case the State guaranteed debt of the SAREB should increase the overall risk of the Spanish debt. The equity mix is expected to be in the range of 45% Public vs. 55% Private. Although when facing a banking crisis regulators are forced to improvise (Aghion P et al, 1999) this private majority, could generate a conflict of interest (ECB, 2012) because private shareholders are banks and financial institutions that also have significant interests in the Spanish real estate industry, as shown in Table1. The total amount of assets to be transferred initially in December 2012 to SAREB will include those of; BFA-Bankia (22,318 million €), Catalunya Bank (6,708 million €), Novagalicia and Banco Gallego (5,097 million €) and Banco de Valencia (1,964 million €), in total 37.110 million € (El País, 2012) The transfer of additional assets of other banks, such as Caja España-Duero, Liberbank, and BMN, will start in 2013 and will require further capital by current or new shareholders, but as stipulated in Law 9/2012 the total amount of assets of SAREB will never exceed 90.000 million Euros. 18

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 SAREB ownership as at 28 December 2012 Institution

Capital (million €)

Stake (%)

Private Stake1

2,114

55%

Direct funds

524

14%

Subordinated Debt

1,590

42%

Public Stake

1,705

45%

Direct funds

432

11%

Subordinated Debt

1,273

33%

Total Equity 3,819 100% 1 Private shareholders include; Banco Santander, CaixaBank, Sabadel Popular, Bankinter, Cajamar, Banca March, Deutsche Bank, CCS, Mutua Madrileña, Catalana Occidente, Asisa y Mutua Pelayo. Source: Expansion, 2012.

Taking into account these numbers we can build an illustrative balance sheet of SAREB, as shown in Figure 1, it shows that when matching the total amount of assets transferred with the sources of funds, it can be seen at a glance that 91% of funds comes from state guaranteed debt and only 9% is equity. Assets (million Eur).

Liabilities (million Eur).

From Novacaixa and Banco G. 6,122 M€ From Catalunya Caixa 6,708 M€

Bonds issued by SAREB State Guaranteed 37,110 M€

DEBT

91%

From Bankia BFA 22,318 M€

Initial Cash and equivalents Shareholders 3,818 M€

Public S hareholer (FROB); 45% of equity, 1,705 M€ Private S hareholers (Banks); 55% of equity, 2,114M€

EQUITY (*) 9%

From B.Valencia 1,962 M€

(*) Equity icludes shareholders funds and subordinated debt

Fig. 1 Illustrative Balance Sheet of SAREB by December 2012

This high proportion of debt will have a very low cost because is State Guaranteed, consequently leverages the stream of earnings to be paid to the equity, in fact borrowing at a fixed low rate is increases sharply the rate of return of the firm´s equity (Brealey Myers, 1996). The estimation of the minimum expected return on equity (ROE) according to the FROB (Fund for Orderly Bank Restructuring) is at 14%. But more importantly any increase on profitability on the total volume of assets goes to the equity, mainly controlled by Private banks. 19


1.3 Transfer Price of Real Estate Assets to SAREB The transfer prices have been determined by Banco de España, and were sharply adjusted, they are based on the exercise performed by Oliver Wyman, a consultancy firm, in 2012, as presented in table 2, and include additional discounts taking into account some costs of SAREB such as administration and financial costs. Table 2 Type of asset and haircut applied in the transfer price to SAREB according to FROB Asset Type

Average haircut

Asset Type

Average haircut

Loans1 45.6% Foreclosed assets2 63.1% 1 Loans include; loans on finished housing, land, projects, and other Real Estate assets. 2 Foreclosed assets include; new housing, developments in progress and land.

As a consequence of the haircuts applied, the final price of the assets ranges between 54% and 37% of their initial book value, depending if they are loans on assets or physical real estate assets.

2 The Real Options Approach

2.1 Advantages of the Methodology An increasing number of academics and corporate practitioners defend that traditional discounted-cash –flow (DCF) approaches such as the standard net-presentvalue (NPV) rule, cannot properly capture management´s flexibility to adapt and revise decisions in response to unexpected market developments (Trigeorgis, 1996). DCF approaches build “expected scenarios” based on assumptions. But they are not able to capture the management´s flexibility to make decisions throughout the process changing the outcome of the project. Real Options methodology is based on the financial options theory to value derivatives, but instead of using a financial asset (e.g. a share) as underlying, uses a real asset (e.g. a physical asset or a project), its advantage is that allows to value investment decisions taking into account the flexibility to adapt to the changing market conditions and make decisions throughout the life of a project. An Option is conceived as a right but not an obligation to make a decision in a period of time. There are two kinds of options, “calls” and “puts”, a “call” option gives the right to buy an asset at a specified exercise price, and the “put” option gives the right to sell the asset at that exercise price. Both “calls” and “puts” can be “European”, if they must be exercised at a fixed date, or “American” if they can be exercised at any time before a final date. 20


2.2 Numerical Methodology Application to Value the SAREB To value the SAREB we take into account its flexibility to adapt to market conditions, meaning that if Real Estate Market conditions improve it can gain the upside, and if they decline SAREB does not lose a lot because it can always sell all or part of its assets that are valued at a low price vs. the market. Consequently the assets of SAREB include an abandonment option, which is an American Put Option. To show the value of it, we build a base case and some sensitivities regarding (ii) the standard deviation, and (iii) the abandonment price. The valuation methodology applied is the simple discrete-time model presented by Cox, Ross and Rubinstein in their famous article published in the Journal of Financial Economics in 1979. As a starting point five variables must be defined: The underlying assets; are the Real Estate assets transferred from the affected banks. We take the value of the assets transferred until December 2012 amounting 37,110 million €. We assume that the haircut that they have suffered is 55%, a figure between 46% and 63% as presented in previous points, consequently their initial book value was 82,470 million €. We also treat the total amount of assets as a whole and its evolution in percentage in order to show in a simple manner the evolution of its value. Meaning that the 82,470 million € are 100% of the value before the haircut, and that 37,110 million € are 45% of the book value. One important element of the Real Options vs. Financial Options, is that the owner of a financial option can not affect the value of the underlying asset (e.g. a share of Telefónica), but the manager of a real asset can raise its value (Copeland Antikarov, 2003). Consequently the proper management SAREB assets have a lot to do with the final value extracted from them. The exercise price; the minimum price at which assets can be sold. Due to the haircut suffered by the assets transferred to SAREB it can be assumed that it is 37,110 million €. Time to expiration of the option; fifteen years, equal to the life of SAREB. It is worth to mention that this long life increases the value of the option because the probability of price increase of the Real Estate underlying assets is also higher. The standard deviation of the price of the underlying asset; is the standard deviation of the price of the Real Estate assets. This industry traditionally has shown higher volatility than the stock market, and it has grown sharply during the last years, as shown in Table 3. In the base case it is assumed a standard deviation of 40%, showing the higher than the IBEX 35 volatility of the industry. 5. The risk-free rate over the life of the option; we assume it is the rate of the Spanish Public Debt for an equivalent period of time of 15 years, of 6.5%.

21

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 Annual Standard deviation of Real State Spanish quoted companies, average of them and IBEX 35 as a reference Company Name, average and Index

Standard Deviation σ (3 years period 2010 - 2012)

Reyal Urbis

96%

Colonial

69%

Sacyr y Vallermoso

59%

Realia

48%

Average

68%

IBEX 35 Source: La Caixa, December 2012

29%

Once the variables are identified, an event tree showing the paths that could be followed by the value of the underlying asset is built, as shown in Figure 2. Year σ=

1

2

3

4

5

6

7

8

9

10

11

12

13

8157% 3665%

Million € 82,467

2457%

% 100%

1647% 1104% 740%

Haircut

45,357

55,0%

496% 333% 223% 149%

Value of the assets transferred

Million € 37,110

15 18154%

12169%

40% 5468%

Book Value

14

100%

% 45%

67%

100%

45% 30% 20%

45%

20%

45%

20% 14%

9%

20% 14%

9% 6%

9%

4%

20%

9%

4% 3% 2%

9%

3%

6% 4%

3% 2%

1% 1%

14% 9%

6% 4%

2% 1%

30% 20%

14%

6% 4%

67% 45%

30%

14%

6%

3%

45%

20%

149% 100%

67%

30%

14%

6%

100%

45%

333% 223%

149%

67%

30%

740% 496%

223%

100%

1647%

333%

149%

67%

30%

496%

223%

100%

2457% 1104% 740%

333%

149%

67%

30%

14%

223%

100%

45%

496%

3665%

1647% 1104%

740%

333%

149%

67%

30%

496%

223% 149%

67%

740%

333%

2457% 1647%

1104%

8157% 5468%

3665%

3% 2%

1% 1%

1%

1% 1%

1% 0%

1% 0%

0%

0% 0% 0%

Fig. 2 Present Value event tree without abandonment option

After building the event tree, the real option to abandon is computed at each node of the tree and calculated the present value of it. As shown in figure 3, the flexibility has added value, enhancing the project upside in case of Real State Price increases, and limiting the downside to a level close to the initial assets value. When taking into account the option to abandon, the value of the assets obtained reaches 47,090 million €, 9,980 million over the initial asset valuation of 37,110 million €, representing a 12%.

22

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Year

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15 18154%

12169% 8157% 5468% 3665% 2457% 1647% 1104% 740% 496% 333%

Value of assets transferred Including Real Option

225% 152% 105%

Million € 47,090

% 57%

75% 57% 48%

224% 152%

105% 75% 47%

45%

47%

47% 45%

45% 45%

45%

46%

45%

45%

45%

45% 45%

45% 45%

45%

45% 45%

45%

45%

Abandon

45% 45%

67% 52%

45% 45%

45%

149% 100%

71% 54%

45% 45%

333% 223%

149% 102%

72%

47%

45%

45%

150%

55%

45% 45%

45%

% 12%

56%

740% 496%

333%

223%

103% 73%

1647% 1104%

740%

496%

333%

151% 104%

74% 56%

45% 45%

Increase in Value Million € 9,980

152%

Go

740%

223%

3665% 2457%

1647% 1104%

496% 333%

224%

104% 75%

57%

740% 496%

333%

3665% 2457%

1647% 1104%

8157% 5468%

45%

45% 45%

45%

45%

45%

45%

45%

45%

45%

45% 45%

45%

45%

45% 45%

45%

45% 45%

45% 45%

45% 45%

45%

45% 45% 45%

Fig. 3 Real Option calculation including per node option and decisions

Finally a sensitivity analysis is done and presented in Table 4, showing that even the most conservative case; an additional haircut of 25% in the value of assets, and a low σ at 20%, well under the IBEX35 volatility, reaches a value of 38,018 million €, over the initial value of assets of 37,110 million €. Table 4 Sensitivity analysis Standard Deviation (σ)

Initial Value 37,110 million €

Additional haircut (-25%)1

20%

40,486 million €

38,018 million €

30% (close to IBEX35)

43,683 million €

40,141 million €

40%

47,090 million € (base case)

42,694 million €

50%

50,242 million € 45,214 million € 1 An additional haircut of 25% of the price would drive to an initial value of 27,833 million €

On top of this valuation it is important to notice, that due to the high proportion of State Guaranteed debt on SAREB funds (91%) the upside on profitability will go directly to pay the equity, mainly controlled by private banks. In fact the European Central Bank on its opinion published on 14 December 2012 recommends to impose limitations on the payment of dividends to ensure the timely redemption of State guaranteed bonds, and that all cash held by the SAREB could be applied to the early repayment of the State bonds (BCE, 2012).

23


3 Conclusions Since the SAREB bears a real option that generates significant upside potential, it should be taken into account. Our valuation of the upside is in the range of 10.000 million € (+12% on the value of Real Estate assets transferred). The high volume of State Guaranteed debt at a fixed low rate on SAREB funds causes that all the upside goes to the shareholders that are mainly private banks. This makes explicit that after the financial crisis are emerging two types of banks in Spain, in one hand the losers who are transferring their real estate assets at a deep discount, and in the other hand the winners, capturing the upside potential of those assets as shareholders of SAREB and consequently consolidating their strength in the Spanish Real Estate Industry. It is worth to mention that in this environment Governments should make a real and proportionate effort to redistribute the wealth generated by the Real Estate industry.

4 References Aghion, P., P. Bolton, and S. Fries (1999) Optimal Design of Bank Bailouts: The Case of Trasition Economies, Journal of Institutional and Theoretical Economics, 155(1), 51-70 Brealey RA, Myers SC (1996) Principles of Corporate Finance. Fifth Edition, McGraw .Hill. International. Copeland T, Antikarov V (2000) Real Options, A practitioners guide. Cengage Learning, New York, New York Cox JC, Ross SA, Rubinstein M (1979) Option pricing: a simplified approach. Journal of Financial Economics 7: 229-263 ECB (European Central Bank), Opinion of the European Central Bank of 14 December 2012 on asset management companies (CON/2012/108). El País, 26 December 2012. “La banca nacionalizada traspasa al banco malo activos por valor de 37.110 millones”. Available via http://economia.elpais.com/economia/2012/12/26/actualidad/1356524351_995160.html El País, 28 December 2012. “Bancos y aseguradoras aportan 1.590 millones a la Sareb en deuda subordinada”. Available via http://economia.elpais.com/economia/2012/12/28/agencias/1356706298_756836.html Expansión, 13 December 2012. “Sareb negocia contrarreloj la entra da de Pimco y Fortress en el capital”. Available via. http://www.clipmedia.net/ficheros/2012/12_dic/sq270.pdf FROB Fondo de Restructuración Ordenada Bancaria (2012). Press Release 13 December 2012, Sareb increases capital to allow private investors to take a stake. Available via. http://www.frob.es/notas/20121213%20SAREB%20INGLES%20PROT.pdf Ley 9/2012, de 14 de noviembre, de reestructuración y resolución de entidades de crédito. Available via. http://www.boe.es/boe/dias/2012/11/15/pdfs/BOE-A-2012-14062.pdf Luehrman, Timothy A (1998) Investment Opportunities as Real Options: Getting started on the Numbers. Harvard Business Review 76: 51-67. Real Decreto-ley 24/2012, de 31 de agosto, de reestructuración y resolución de entidades de crédito. Available via. http://www.boe.es/boe/dias/2012/08/31/pdfs/BOE-A-2012-11247.pdf Trigeorgis, L (1996) Real Options Managerial Flexibility and Strategy in Resource Allocation. The MIT Press, Cambridge, Massachusetts

24


Corporate Entrepreneurship: Types and Determinant Factors. A Case Study Based Analysis of Technology Based and R+D Active Companies. Onaindia E1, Goyogana U2, Ochoa Laburu C3 Abstract Based on the integrative model proposed by Narayanan V, Yang Y, Zahra S (2009) as theoretical framework and using multiple case studies, we explore in this paper the characteristics of new business, activities or ventures; created by entrepreneurial companies and the cause-effect relationship of some “context agents”, such as: external factors (industry, technological change) and internal organizational factors (capital structure, top management commitment, competitive strategy, organizational structure, human resources management, use of public funds and policies). We have selected six technology-based companies with medium-high intensity in R+D, either small or medium-high companies, from very different industries, but all of them involved in Corporate Entrepreneurship. The preliminary results confirm the thesis pointed out in scientific literature: the implication of top management is critical, CE is a strategic issue with decisive influence for the survival of the company and the Intrapreneur has revealed to be a key agent. Nevertheless, there is a wide range of possible combinations of factors, mainly of internal ones, and their cause-effect relationships are very different.

Keywords: Corporate Entrepreneurship, Internal and External Factors, Multiple Case Studies

1

Eneritz Onaindia Gerrikabeitia ( e-mail: [email protected]) Dpto. de Organización de Empresas. EUITI-Eibar. UPV-EHU Avda Otaola 29, 20600 Eibar.

2 Unai Goyogana Quesada ( e-mail: [email protected]) Dpto. Organización de Empresas, UPV – EHU. Escuela Politécnica. Universidad del País Vasco. Plaza de Europa 1, 20018 San Sebastián. 3

Carlos Ochoa Laburu ( e-mail: [email protected]) Dpto. Organización de Empresas, UPV – EHU. Escuela Politécnica. Universidad del País Vasco. Plaza de Europa 1, 20018 San Sebastián.

25


1 Introduction and Approach of the Project The interest in “business creation” (entrepreneurship) and its protagonists (entrepreneurs) is a classic issue in economic literature and, specifically in literature about management. This issue is specially recurrent and relevant in economic crisis times. But, despite all the generated literature there is still a wide field of study about the “type” of Corporate Entrepreneurship and “how” new ventures are developed, and specifically, about Internal Organizational Factors. A group of technology-based and active in R+D companies which have experience on Corporate Entrepreneurship is studied in this work. Consequently, classic questions about Entrepreneurial Orientation or about the results of that entrepreneurial activity are not proposed. The studied companies are proactive on entrepreneurship and obtain economical and not economical results from it. We question and attempt to analyze “what do technology-based and R+D investor entrepreneurial companies do? and how?” so that results can be translated to other companies.

2 Theoretical Models to Analyze Corporate Entrepreneurship We have selected the model by Narayanan, Yang and Zahra (2009) as a theoretical framework because it is focused on the “entrepreneuring company”, and specially because a section about “Characteristics of the new venture” is included:  Internally or externally developed. It means, creating a new company or a new activity line in the current company.  100% owned company or partnership as a major or minor shareholder.  Internal or external entrepreneur  Developed according to the strategy of the company or because of an opportunistic decision. The model by Narayanan, Yang and Zahra (2009) is proposed as a synthesis of the most relevant models: Guth-Ginsberg (1990), Covin-Slevin (1991) and Lumpkin-Dess (1996). A positive Entrepreneurial Orientation has a positive effect on the outcomes of the company, especially in the economic outcomes (profitability, sales increase and market share). The cause-effect relationship between them may be reversible. Good outcomes may favour Entrepreneurship. There is a set of External and Internal Factors/Agents of the company which determine the characteristics of the new activities and, by extension, their outcomes. The cause-effect relationship between them, as well as its intensity, are contingent. In other words, they do not act always in the same way but their influence depends very much on their possible combinations. 26


In the same way, there is a set of factors, external and internal to the company and to the new activities, which Moderate/Mediate in the entrepreneurship process. Moderators Environment hostility Context External Technology Demand Entrepreneurial Orientation

CV Characteristics Strategy Orientation

Internal

Finance

Top Management

Organization

Corporate Culture

Intrapreneur

Outcomes Economic Outcomes Market Performance Strategic Outcomes

Processes Compensation/Incentives Control

Mediators

Timing

Organizational Structure Market Orientation

Controlled by the parent company

Controlled by the new business

Fig. 1 Integrative model for Corporate Venturing by Narayanan, Yang, Zahra (2009)

3 Methodology: Multiple Case Study The focus of this work is mainly exploratory. It means that the available theoretical basis for the research questions are considered inadequate or incomplete and that is why new theoretical contribution is required to better understand the analysed phenomenon. Consequently, multi-case study methodology has been used (Yin, 1984). As many authors have pointed out, (Yin, 1984; Eisenhardt, 1989; Villareal and Landeta, 2006; Toledano-Urbano, 2011) the main advantage is the potential to research deeply complex phenomena, in which experience of participants are specially important and the context is essential.

27


4 Characterization of the Companies in the Study We have analyzed six companies with medium-high technological base: mediumhigh rates of assets/employee, sales/employee and added value/employee. These six companies work in very different industries. Four of them are mature companies, more than 30 years old, so these companies are managed by the second or third generation of owners. The other two are quite young, less than 10 years old, and these two companies are managed by the first generation of owners, the entrepreneur. Table 1 Characterization of the companies in the study Company

A B

Industry Electric power generation (Utilities design, construction & operation) Buildings construction (Structures design & construction)

Age

Size

(Years)

(No. of Employees)

60

5.000

40

70

C

Computer interactive graphics

5

50

D

Bicycle manufacturing

150

250

5

30

90

80

E F

Engineering services (Precision equipment for science design) Small and medium domestic appliances

Technology Intensity

Low

Assets/employee (€)

< 100.000

Medium

> 200.000

Sales/employee (€)

< 100.000

> 200.000

Added value/employee (€)

< 40.000

Company

High

> 70.000 C, D, F

A, B, E

Medium

High

R+D Intensity

Low

University graduates

< 10%

> 50%

R+D (Sales, employees)

< 5%

> 10%

Patents Company

F

D, B

A, C, E

Internationalization

Low

Medium

High

(< 10% sales) Company

(>25% sales) B, C, F

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A, D, E


5 Entrepreneurial Behaviour of the Companies in the Study The duration of the life-cycle of product or activity lines is decreasing to less than 10 years and companies are forced to set up new activities, at least, every five years. This is the reason why Corporate Entrepreneurship is so important for them by two ways: new product development and new companies development based on some of the former products. The features of the relationship between the Entrepreneurial Behaviour of the analyzed companies with their External Factors are summarized in table 2. Table 2 Types of Corporate Entrepreneurship according to External Factors change / Competitiveness of the industry)

(Technology

Life-Cycle of the Industry

Relatedness to main activities

Product life-cycle strategy

Way of the new activity

Origin of Entrepreneur

No. cases

Emergent

Emergent technology Same Technology/ Different Market

Pioneer

Spin off

External

(2) C,E

Internal

(2) A,B

Internal

(2) D,F

Mature

Mature

Same Technology/ Different Market Emergent technology Emergent technology Different Technology/ Same Market Different Technology/ Same Market

Spin off Pioneer

Strategic renewal Acquisition

Pioneer

Strategic renewal

Source: elaborated by authors

The features of the relationship between the Entrepreneurial Behaviour of the analyzed companies with their External Factors are summarized in table 3.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 Types of Corporate Entrepreneurship according to Internal Factors (Boost for Corporate Entrepreneurship / Strategy) Product lifecycle strategy Pioneer

Pioneer

LifeCycle of the Industry

Relatedness to main activities

Boost for CE

Way of the new activity

Origin of the Entrepreneur

No. cases

Emergent

Different Technology/ Different Market

Board/Management Customers R+D

Spin off

Internal

(1) A

Emergent

Same Technology/ Different Market

Board/Management Customers R+D Technology partners Entrepreneur

Spin off

External

(2) C, E

Corporation Board/Management R+D

Acquisition Strategic Internal renewal

Different Technology/ Same Market Source: elaborated by authors Follower

Mature

(3) B,D,F

6 Analysis and Discussion Companies in “mature” industries are more “follower” than “pioneer”, despite their R+D departments. Companies in “emergent” industries show an opposite behaviour. In this sample there is a similar number of both types. There are more “pioneer” companies that launch technological innovations which are very “related” to their current business. In other words, they adapt current technologies and products to new markets and customers. Most of them create ex-novo companies, but there are also some cases of acquisitions. Almost in every case the entrepreneur is external to the original company. He or she usually comes from a partner of the company or a partner in a R+D project. In fact, those collaboration projects are the main source of original ideas for future entrepreneurial projects. But the Board of the company is always on its back. The role of the “entrepreneur” who “pushes” to make the new activity develop is more often in this category Companies in “mature” industries in our sample adopt mainly one type of innovation strategy: Related innovation. In other words, different technology for same market - customers. It is executed mainly through internal development though with technological partners. The boost comes more frequently from the Management and the R+D department frequently in cooperation with technological partners. 30


Why the new ventures are created with a 100% or a majority share of the capital in some cases and with a minority share in others? It is more usual the latter than the former and the reason is not clear. It seems that the minority position is more usual in not related innovations and in emergent industries in which the company depends much more on technological partners. Why some companies use intrapreneurs and others external entrepreneurs? It is also not very clear. It seems that it is more related with the diversification to new markets than with the development of new technologies. When intending to enter in a new market it seems more appropriate to use someone with experience in them, frequently technological partners or collaborators in R+D projects. When intending to develop a new technology it seems more appropriate to rely on internal R+D and intrapreneurs. It is obvious that the Top Management role is decisive. Some of the companies in our sample (A, E) are “presidential”. In D it is the Board of the corporation, not the company who has the boost to promote innovation. In B it is the Executive Management and not the Board. In C they are some of the partners and not the CEO. In this same company, the entrepreneur was a main force in pushing forward the decision to create a new venture. In any case the role of the Board of the company is significantly moderated by (or significantly moderates to) the R+D department, the technological partners or the customers in the different cases. The use of Risk Capital does not seem to be influenced by the technological strategy (pioneering or follower) neither by the industry (emergent or mature), nor the creation of a brand new company or the acquisition of an existing one. What seems to have influence is again the destiny of the innovation. Activities created to penetrate new markets use more Risk Capital than the ones devoted to the development of new technologies. Anyway, this strategy has been used very few times. Almost all the companies in this study have used some modality of public funds: public calls for financing of R+D projects, establishments at Technology parks or Innovation Poles, or assistance to create new enterprises from CEI (Innovation and Enterprises Centres) or BIC (Business Innovation Centres).

7 References Covin, J; Slevin, D. (1991) “A conceptual model of entrepreneurship as firm behaviour”. Entrepreneurship: Theory and Practice, 16(1):7-25 Dess, G.; Lumpkin, G.; Mc. Gee, J.,(1999) “Linking corporate entrepreneurship to strategy, structure and process: suggested research direction”’. Entrepreneurship: Theory and Practice, 23(3):85-102 Eisenhardt, K. M. (1989): “Building Theories from Case Study Research”, Academy of Management Review, Vol. 14, nº 4, pp.532-550. Guth, W.; Ginsberg, A (1990) Guest Editor’s Introduction: “Corporate Entrepreneurship”. Strategic Management Journal, 11:5-15

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Lumpkin, G; Dess, G (1996) “Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of Management Review, 21:135-172 Narayanan VK, Yang Yi, Zahra S.A (2009). “Corporate venturing and values creation: A review and proposed framework” Research Policy 38; 58-76 Miles, M.; Covin, J. (2002) “Exploring the Practice of Corporate Venturing: Some Common Forms and Their Organizational Implications”. Entrepreneurship: Theory and Practice, 26(3): 21-40 Urbano, David; Toledano, Nuria; Ribeiro-Soriano, Domingo. “Socio-cultural factors and transnational entrepreneurship: A multiple case study in Spain”. International Small Business Journal 29. 2 (Apr 2011): 119. Villarreal, O.; Landeta, J. (2007) “El estudio de casos como metodología de investigación científica en economía de la empresa y dirección estratégica” Empresa global y mercados locales: XXI Congreso Anual AEDEM, Vol. 1, 2007 (Ponencias), pág. 34 Yin, R. K. (1994): Case Study Research. Design and Methods, Applied Social Research Methods Series, Vol. 5, Second Edition, Sage Publications, London.

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The impact of innovation management techniques on radical innovation: An empirical study Igartua J.I1, Errasti N, Ganzarain J Abstract While research in innovation management has provided many insights into specific aspects of innovation, the encompassing problems confronting general managers, especially managers of small and medium-size firms, have been overlooked in the development of innovation management techniques and tools. This paper analyses the way innovation management techniques (IMTs) influence innovation in firms. Specifically, this paper focuses on studying the role of IMTs on radical innovation. To this end, we propose a specific model of analysis, tested in a sample of more than five hundred Spanish companies. Research results highlight that different set of IMTs relate to radical and incremental innovation in different ways, and that therefore companies seeking for radical innovation look for certain IMTs rather than others. This empirical study will help managers and practitioners to understand the role of IMTs in structuring radical innovation strategy, as well as to researchers to focus on the role of such IMTs on innovation.

Keywords: Innovation, Radical Innovation, Innovation Management Techniques, IMTs

1 Introduction The need for understanding innovation appears to be widespread, at business level. Some researchers have developed studies regarding the measurement of innovative performance in enterprises (Mancebo Fernández and Valls Pasola, 2005), using instruments as the Community Innovation Survey instrument (CIS) trying to discover the factors that influence that result (Arundel and Hollanders, 2006). On 1

Juan Ignacio Igartua (e-mail: [email protected]) Departamento de Mecánica y Producción Industrial. Escuela Politécnica Superior, Mondragon Unibertsitatea, C/ Loramendi 4, 20500 Mondragon, Spain

33


the other hand, other scholars have investigate onto the role of innovation management and the analysis of its impact on innovation and innovation performance of firms (Rigby and Bilodeau, 2007, Adams et al., 2006) (Prajogo and Ahmed, 2006), including the emphasis on the role of systems and tools (Chiesa and Masella, 1996). Finally another incipient research approach it has been orientated to analyse the role of techniques and tools for managing innovation (Hidalgo and Albors, 2008).This approach highlights innovation as a fundamental process in organization performance (Galanakis, 2006, Raymond and St-Pierre, 2010), a process that requires setting up well-organized and well-run standardized set of tools (Igartua et al., 2010). In this direction, the aim of this paper focuses on understanding the influence of innovation management techniques (IMTs) on innovation in firms. Specifically, this paper focuses on studying the role of IMTs on radical innovation. Thus, the main purpose of the study reported in this paper is to understand how companies´ implementation of IMTs, affect innovation (product, service, process, and other kind of innovations) and the specific role of certain IMTs when looking for radical product or service innovation (McDermott and O'Connor, 2002). The aim of this paper is to understand whether IMTs play a significant role on innovation and the achievement of radical innovations. After a brief introduction to innovation management techniques (IMTs), we develop the methodology used in this study. Subsequently we show some empirical results of the investigation, including a conclusions section.

2 Innovation Management Techniques (IMTs) The need to manage the innovation process and context, demands that managers make effective and timely decisions based on multiple functions, inputs and disciplines (Brown, 1997); and therefore, management tools and techniques are needed to support these complex decisions (Phaal et al., 2006a). Brady et al. (Brady, 1997) define a management tool as “a document, framework, procedure, system or method that enables a company to achieve or clarify an objective” (p.418). Innovation management techniques (IMTs) can be defined as the range of tools, techniques and methodologies intended to support the process of innovation and help companies to meet new market challenges in a systematic way (Phaal et al., 2006a). Chiesa and Masella (Chiesa and Masella, 1996), in their audit model of the process of technological innovation, identified the effective use of appropriate tools and systems as one of three facilitators of innovation processes, in conjunction with the deployment of human and financial resources and the leadership and direction of senior management.

34


A research conducted in Europe (European Commission, 2000) affirmed that IMTs allow a company to combine technology and business strategy, fostering increased employee participation, and concluded that there is insufficient awareness of the variety and range of IMTs available, as well as the potential benefits of their use. More recently, Hidalgo and Albors (Hidalgo and Albors, 2008) argue that IMTs are critical to increasing competitiveness, showing that proper application of IMTs facilitates a company’s ability to introduce appropriate new technologies in products or processes, as well as the necessary changes to the organization. About the existing IMTs, several authors as Phaal et al. (Phaal et al., 2006a) have worked towards the development of a catalogue of tools, as well as a series of research programs. In this direction, some works have tried to summarize the existing set of techniques (Hidalgo and Albors, 2008), an approach followed by other researchers that focused on the role of certain tools (Igartua et al., 2010, Lichtenthaler, 2011, D'Alvano and Hidalgo, 2012, Aagaard, 2012, Tipu, 2012, Padilla-Meléndez and Garrido-Moreno, 2012, Huang and Rice, 2012), or empirical studies (Graner and Mißler-Behr, 2012, Barge-Gil et al., 2011, Chai et al., 2010). Thus, the present research focuses on the role of 17 groups of IMTs identify in the literature (1.- creative development, 2.- technology management, 3.- strategic management, 4.- people management, 5.- business intelligence, 6.- management innovative projects, 7.- development of new products-services, 8.- techniques and practices for collaboration and networking, 9.- design management, 10.knowledge management, 11.- new business development, 12.- financial resource management, 13.- industrial property rights management, 14.- production management, 15.- marketing, 16.- organizational practices, and 17.- process improvement) (Hidalgo and Albors, 2008 4261, Phaal et al., 2006b 1409).

3 Research Methodology The research was conducted through a survey targeted to business managers, as others research studies conducted in the field of innovation (O'Regan et al., 2006). The research is based on survey focused on innovation management where top managers, of more than five hundred companies over a defined universe of six thousand companies, were asked to answer a structured questionnaire from December 2008 till April 2009. The measurement instruments developed for the measurement of innovation (product-service and process) were based on variables used in the literature and based on the Community Innovation Survey (CORDIS, 2008). On the other hand, the measurement of the implementation of IMTs in companies was developed

35


though a scale of 53 items from the identification of the former mentioned 17 IMT groups identified in the literature (Cronbach's alpha for these scale was 0,948). The gathered data has been analysed using SPSS16 and statistical methods as T Student Test, ANOVA and regression analysis (simple linear and multiple linear). Due to the fact that the sample meets the sampling criteria needed to ensure its representativeness, the implications of the study are directly extrapolated to the entire study population.

4 Results In order to examine whether there are significant differences between the implementation of IMTs in companies and their innovation results, a Student's t-test comparison of two means was developed. The results of this test are summarized in Table 1. Thus, in all cases the t-statistic takes a critical level of bilateral significance lower than the critical value of 0.005 rejecting the null hypothesis of equality of means, and therefore concluding that the use of IMTs in companies that innovate is higher compared to those companies that do not innovate. Table 1 IMTs use related to Innovation (Product, service, process and other innovations) N Prod Inno Serv Inno

Yes No Yes No

362 186 327 221

Mean 2,4700 1,7004 2,4267 1,8741

Std.D. ,67465 ,63001 ,68541 ,73550

Std. Err. Mean ,03546 ,04619 ,03790 ,04948

Proc Inno Other Inno

Yes No Yes No

N

Mean Std.D.

378 176 409 148

2,4235 ,71159 1,7732 ,67540 2,4319 ,69673 1,6291 ,62068

Std. Err. Mean ,03660 ,05091 ,03445 ,05102

It was also considered the fact that, when analyzing the use of IMTs by companies, those could be classified into four groups, depending on product-service and process innovations (Table 2). Table 2 Companies classification based on innovation Prod-Serv Inno YES YES NO NO

Process Inno NO YES YES NO

Group 1 2 3 4

N 85 332 44 93

Thus, when analyzing the use of IMTs on these four groups the statistical results based on ANOVA analysis (with a significance of 0.000 lower that the significance lower than the critical value of 0.005), show that for all the IMTs groups 36


(excepted the group of techniques related to production management: Just-in-time, ERP, Lean Management); the mean use of IMTs is higher for those companies that do innovate in product-service and process altogether, than for those that only innovate in product, process or do not innovate (Figure 1).

Fig. 1 Mean use of IMTs by companies´ innovation activity classification

Finally, when analyzing the use of IMTs related to the innovation radicalness, two simple linear regression studies were developed, one for the radical innovation of product-services and other for the incremental one (see Table 3). The models take a very high R (0.596) for radical innovation and an also high R (0.641) for incremental innovation; indicating that 35.5% of the variability of performance in radical innovation of product-services depends on the use of IMTs, while the 41.1% of the variability of performance in incremental innovation of 37


product-services depends on the use of IMTs. In addition, the F statistic shows for both regressions a value below the critical level (Sig 0.05), so it can be argued that variables are linearly related. Table 3 Companies classification based on innovation Model

Radical Innovation R R2 Adj. R2 Std.Err. of Estimate

1 ,596a ,355 ,354 a. Predictors: (Constant), IMTs

,77389

Model

Incremental Innovation R R2 Adj. R2 Std.Err. of Estimate

1 ,641a ,411 ,410 a. Predictors: (Constant), IMTs

,78352

Besides, and in order to identify the IMT groups that most related to the radical innovation of product-services and to the incremental one, two multiple linear regression analysis were carried out introducing variables step by step till the models was validated after five steps and six steps respectively (see Table 4 and Table 5). Table 4 Multiple linear regression (step-by-step) relating IMTs and Radical Innovation Radical Innovation: Model Summaryf Std.Err. of Change Statistics Estimate R Square F df1 df2 Change Change 5 ,606e ,368 ,361 ,75135 ,008 6,581 1 508 e. Predictors: (Constant), TRed, TFinan, TCrea, TProp, TIntel f. Dependent variable: InnoRadical

Model R

R2

Adj. R2

Sig. F. Change ,011

So, the model of radical innovation was tested in five steps, after which the proposed model included a constant, and the variables related to the use of IMTs related to networking, economic and financial aspects, creativity techniques, techniques related to industrial property management, as well as those related to business intelligence and technological foresight. Table 5 Multiple linear regression (step-by-step) relating IMTs and Radical Innovation Radical Innovation: Model Summaryf Model R R Adj. Std.Err. of Change Statistics R2 Estimate R Square F df1 df2 Change Change 6 ,647f ,418 ,411 ,77402 ,008 7,226 1 504 f. Predictors: (Constant), TEmpr, TLNP, TTec, TProy, TProp, TRed g. Dependent variable: InnoIncremental 2

Sig. F. Change ,007

In contrast, the model of incremental innovation was tested in six steps, after which the proposed model included a constant, and the variables related to the use 38


of IMTs related to new business development (business plan, transfer mechanisms, and spin-offs), new product development techniques, technology management, project management, industrial property management, and those relating to the management of networking activities.

5 Discussion and Conclusions The main purpose of the article was to identify the link between business innovation and its radicalness and innovation management techniques (IMTS) implemented by companies. The IMTs measurement was based on set of 17 group of techniques taken from the literature, while the innovation measurement was based on the already existing instruments. Thus, based on the extended set of data and using statistical methods (Student's t-test, linear regression and multiple linear regressions), the research has underlined the importance of IMTs and their differential role on the achievement of different kinds of innovations (product-service and process). When analyzing innovation in companies, results indicate that the variability of performance in innovation management depends on the implementation IMTs, what underlines the importance of management techniques, coinciding with previous researchers (Phaal et al., 2006a, Hidalgo and Albors, 2008, Igartua et al., 2010, Phaal et al., 2006b, Chai et al., 2010, Barge-Gil et al., 2011, D'Alvano and Hidalgo, 2012, Graner and Mißler-Behr, 2012). Furthermore, the multiple linear regression analysis carried out also stress the role of certain IMTs for the development of radical versus incremental innovations. Thus, networking (open innovation and collaboration), as well as financing, creativity techniques, IPR management and business intelligence (technology watch) seem to be techniques that are important for the development of radical innovations, while new business development techniques, new product development techniques, technology management and project management seem to influence incremental innovation of product or services. The limitations of this paper result from the research model and the variables used. Further research and analysis would provide more detailed relationships. On the other hand, the contributions of this study must be interpreted with a degree of caution since it has focused on a regional context, which may have certain characteristics that can affect the findings.

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6 References Aagaard, A. 2012. The Contribution of Innovation Strategy Development and Implementation in Active Facilitation of Pharmaceutical Front End Innovation. Systemic Practice and Action Research, 25, 457-477. Adams, R., Bessant J. & Phelps, R. 2006. Innovation management measurement: A review. International Journal of Management Reviews, 8, 21-47. Arundel, A. & Hollanders, H. 2006. Searching the forest for the trees: “Missing” indicators of innovation. 2006 Trend Chart Methodology Report. MERIT - Maastricht Economic Research Institute on Innovation and Technology. Barge-Gil, A., Nieto, M. J. & Santamaria, L. 2011. Hidden innovators: the role of non-RD activities. Technology Analysis & Strategic Management, 23, 415-432. Brady, T., Rush, H., Hobday, M., Davies, A., Probert, D., Banerjee, S. 1997. Tools for technology management: An academic perspective. Technovation, 17, 417-426. Brown, D. 1997. Innovation Management Tools: A review of selected methodologies, Luxembourg, EUROPEAN COMMISSION: Directorate-General XIII Telecommunications, Information Market and Exploitation of Research. CORDIS. 2008. Community Innovation Survey [Online]. Available: http://cordis.europa.eu/innovation-smes/src/cis.htm. Chai, S. N. C., Sun, H. Y. & Lau, A. K. W. The impact of innovation management techniques on product innovation performance: An empirical study. 2010 Singapore. 432-437. Chiesa, V. & Masella, C. 1996. Searching for an effective measure of R&D performance. Management Decision, 34, 49 - 57. D'alvano, L. & Hidalgo, A. 2012. Innovation management techniques and development degree of innovation process in service organizations. R and D Management, 42, 60-70. EUROPEAN COMMISSION 2000. Promoting innovation management techniques in Europe. Galanakis, K. 2006. Innovation process. Make sense using systems thinking. Technovation, 26, 1222-1232. Graner, M. & Mißler-Behr, M. 2012. The use of methods in new product development-A review of empirical literature. International Journal of Product Development, 16, 158-184. Hidalgo, A. & Albors, J. 2008. Innovation management techniques and tools: a review from theory and practice. R&D Management, 38, 113-127. Huang, F. & Rice, J. 2012. Openness in product and process innovation. International Journal of Innovation Management, 16. Igartua, J. I., Garrigós, J. A. & Hervas-Oliver, J. L. 2010. How innovation management techniques support an open innovation strategy. Research Technology Management, 53, 41-52. Lichtenthaler, U. 2011. Implementation Steps For Successful Out-Licensing. ResearchTechnology Management, 54, 47-53. Mancebo Fernández, N. R. & Valls Pasola, J. 2005. El comportamiento innovador de la empresa industrial. Un modelo de análisis a partir de la encuesta del INE. Mcdermott, C. M. & O'connor, G. C. 2002. Managing radical innovation: An overview of emergent strategy issues. Journal of Product Innovation Management, 19, 424-438. O'regan, N., Ghobadian, A. & Sims, M. 2006. Fast tracking innovation in manufacturing SMEs. Technovation, 26, 251-261. Padilla-Meléndez, A. & Garrido-Moreno, A. 2012. Open innovation in universities: What motivates researchers to engage in knowledge transfer exchanges? International Journal of Entrepreneurial Behaviour and Research, 18, 417-439. Phaal, R., Farrukh, C. & Probert, D. 2006a. Technology management tools: generalization, integration and configuration. International Journal of Innovation & Technology Management, 3, 321-339.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Phaal, R., Farrukh, C. J. P. & Probert, D. R. 2006b. Technology management tools: concept, development and application. Technovation, 26, 336-344. Prajogo, D. I. & Ahmed, P. K. 2006. Relationships between innovation stimulus, innovation capacity, and innovation performance. R&D Management, 36, 499-515. Raymond, L. & St-Pierre, J. 2010. R&D as a determinant of innovation in manufacturing SMEs: An attempt at empirical clarification. Technovation, 30, 48-56. Rigby, D. & Bilodeau, B. 2007. Management Tools and Trends 2007. Bain & Company. Tipu, S. A. A. 2012. Open innovation process in developing-country manufacturing organisations: Extending the Stage-Gate model. International Journal of Business Innovation and Research, 6, 355-378.

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An Empirical Analysis of the Spanish Gas Price Structure Cansado P1, Rodríguez Monroy C2 Abstract We can say without hesitation that in energy markets a throughout data analysis is crucial when designing sophisticated models that are able to capture most of the critical market drivers. In this study we will attempt to investigate into Spanish natural gas prices structure to improve understanding of the role they play in the determination of electricity prices and decide in the future about price modelling aspects. To further understand the potential for modelling, this study will focus on the nature and characteristics of the different gas price data available. The fact that the existing gas market in Spain does not incorporate enough liquidity of trade makes it even more critical to analyze in detail available gas price data information that in the end will provide relevant information to understand how electricity prices are affected by natural gas markets. In this sense representative Spanish gas prices are typically difficult to explore given the fact that there is not a transparent gas market yet and all the gas imported in the country is negotiated and purchased by private companies at confidential terms.

Keywords: Natural Gas, Gas Price, Oil Indexation, CCGT, Spark Spread.

1 Introduction Probably the most visible link between gas and electricity prices is found when analyzing operations by gas-fired power generation plants (CCGTs). In this respect, for a CCGT the decision to generate electricity or not, will depend on the ‘spark spread’, i.e. the difference between the cost of gas generating an extra MWh of electricity and the revenue obtained from the sale of electricity at the System Marginal Price (SMP). As we said, the report aims primarily to provide a 1

Pablo Cansado Bravo ( e-mail: [email protected]) Escuela Técnica Superior de Ingenieros Industriales de Madrid. 2

Carlos Rodríguez Monroy ( e-mail: [email protected]) Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2, 28006 Madrid.

42


detailed analysis of the available gas price references to understand and quantify the essential features applying to the Spanish gas and electricity markets

2 Gas Pricing Fundamentals in Spain. Perhaps the most crucial factor having a strong influence on the existing long term contract gas prices in Spain, is the fact that the majority of those gas contracts prices are determined by a formula referenced to oil and oil products evolution. Moreover long term contracts are confidential by nature and therefore a precise determination of wholesale gas prices is opaque. Not only are most contracts confidential, but contracts are often limited to two or three years in length, and have been struck at very different prices over time. As a result the ‘average’ gas price normally quoted as a reference is often significantly different from the current contracts available in the market. Additionally to the long-term purchasing strategy, Spanish traders actively seek short term optimization opportunities which bring incoming gas of another nature, named spot LNG. This opportunistic gas supply is normally priced with reference to other benchmarks different from oil and oil products like National Balancing Point (NBP), Transfer and Title Facility (TTF) or even to the recently devised LNG spot indices. Although a detailed analysis of Spanish natural gas price influencing factors is far from the scope of this report, we will analyse those gas price formation drivers through the resulting price structure. Furthermore this will help us to better understand which would be the best option to analyze potential for forecasting gas and electricity prices in the future. The fact that gas coming into Spain is generally delivered through long-term agreements, this structure covering at least 94% of the total expected annual demand as of 2011 according to the Comisión Nacional de la Energía (CNE), creates a solid framework to assess the Spanish gas price contracting structure. Moreover a high proportion of these contracts use Brent oil and oil products as base price reference for buyers and sellers. It has to be said that, establishing a reference for end-user gas prices is also difficult. In the first place, the liberalization process in the gas market has significantly widened up the range of gas suppliers in the country adding a certain variety of gas price formulas and price levels. Furthermore the traditional regulated, i.e. fixed price reference applicable to specific customers is today only a residual share of the total gas market, i.e. the Last Resort Tariff (LRT) scheme for small customers that sets a price benchmark only relative to the actual volumes sold in that segment, around 20% of total volumes sold. Nonetheless the Ministry´s procedures to establish a transparent LRT price formation scheme has helped substantially to determine fundamentals of imported price, as we will see. 43


3 Gas Price Data Available in Spain In order to perform the analysis, we have examined the main information published ready available in Spain for wholesale gas prices, of which perhaps the most relevant today is that collected by the CNE, directly processed from imported gas price data by origin from Agencia Tributaria (AEAT) in www.AEAT.es, similar to the information that AEAT provides to all Spanish Cámaras de Comercio and that is available through the Comercio Exterior Data Base in http://aduanas.camaras.org/ web site. We will nominate this reference as CNE_AT gas price. As the second gas price reference for Spanish import prices we will select the base price benchmark described in the Last Resort Tariff (LRT) calculation methodology developed by the Ministry of Industry in 2008 with the intention to reflect existing long term contract prices into Spain for LRT calculation purposes. The benefit of this price reference is that it gives in our view a very accurate representation of larger import volumes prices into Spain but also of expected oil-indexed average price trends in the future, at least for the next four or five years. In this sense we anticipate a significant alignment between the current cost of long-term supplies into Spain (as per the CNE_AT gas price) and the LRT base price. It has to be said that additionally, the LRT Ministry´s calculation weights this long term base gas price with gas prices resulting from regular auctions and also with a percentage of NBP and Henry Hub (HH) prices. The introduction of external price benchmarks into the resulting price formula had initially the intention to take into account regular LNG spot purchases by traders at a liquid hub price. The actual weighting determined by the Ministry is in our opinion somehow misleading as it does not consider that liquid markets, like NBP and HH do also structurally fluctuate according to medium term supply/demand conditions. At this point in time and with the depressing effect of shale gas production significantly lowering HH index, we understand that a resulting weighted average of 80% LRT price and 20% NBP price to construct a final LRT proxy price is more realistic. This will be our second gas price reference. Finally and in order to complete the picture we have also considered in the analysis the NBP price benchmark to reflect trends and seasonality of global LNG spot prices as a whole affecting Spanish traders price expectations under the current market conditions.

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4 Distribution Function of Spanish natural gas prices.

4.1 Objective The objective in this section will be to understand the statistical properties of typical long term gas price benchmarks in Spain to prepare for an ulterior analysis of effects into electricity prices formation. We start with an analysis of almost eight years history (01/01/2004-01/07/2012) with price details on a monthly basis by the different benchmarks, i.e. CNE_AT, LRT proxy and NBP to set up the picture of wholesale gas price formation in Spain. The main objective of the analysis will be to conclude on the distribution patterns of the different gas price data as an essential starting point for building up gas price factors into stochastic models to determine electricity prices in the future. Modelling techniques, model testing and acceptance and finding the right parameters all depend in great extent on the choice of the relevant distribution. Although there is a vast amount work devoted to empirical analysis of the properties of gas price distributions in different markets, the Spanish gas market situation under the rules of oil-indexed contracts, make the analysis of price distributions a very challenging task. Although the opening of the gas market in Spain is prior to 2004, we will consider that a relative more stable picture for trading activities is starting around 2003 and 2004. We will try in the first place to test the hypothesis that log-returns of these values are normally distributed. We will follow the traditional methodology in finance, in particular the Black–Scholes model, that considers changes in the logarithm of energy price indices are assumed normal (these variables behave like compound interest, not like simple interest, and so are multiplicative.

4.2 Statistical Properties of Spanish Natural Gas Prices As discussed, we will start by analyzing the statistical properties of the data referred in previous sections that will allow us to examine the dynamics of the long term gas price series. At a later stage we will present a model taking into account previous observations in order to extract as much as possible significant characteristics of the data. We anticipate that general work done on modelling crude oil and their volatile will be essential for modelling identification and model selection. In order to assure that there is not trend component and data are stationary to some extent, we will analyze dynamics of returns series rather than price series themselves. We will calculate for each of the price references log returns as a sequence of prices S1 as defined by the continuous compounding basis: 45


𝑋𝑖 = ln (1 + R t ) = ln

𝑃𝑖+1 𝑃𝑖

Here Pt denotes the price of natural gas at time t. In this way we will smooth out existing trends, i.e., those arising from crude oil price evolution. Furthermore it will allow us to test the hypothesis that log-returns of these values are normally distributed in a more convenient form. Figure 1 presents the history of the gas price benchmarks considered and Figure 2 returns of LRT Proxy and NBP from January 2004 until July 2012.

Jan 11

Jan 12

Jan 10

Jan 09

Jan 08

Jan 07

Jan 06

-0,25

Jan 05

Jan 11

Jan 12

Jan 10

-0,25

Jan 09

0,00

Jan 08

0,00 Jan 07

0,25

Jan 06

0,25

Jan 05

0,50

Jan 04

0,50

Jan 04

Fig. 1 Evolution of different gas price benchmarks and electricity prices since 2004

-0,50

-0,50

NBP

LRT base (80%)and NBP (20%) proxi

Fig. 2 Evolution of returns from LRT proxy and NBP since 2004

The behaviour of prices and returns in the case of the LRT proxy is unsteady and although volatility is low compared to that of NBP, there is some evidence of volatility clustering, i.e. periods of high volatility followed by periods of relatively low volatility, what seems to be in line with typical crude oil returns characteristics. 46


Figure 3 shows the resulting histogram of long term gas price benchmarks logreturns. In the tables attached we can see the statistical parameters determining each function characteristics.

LRT Proxy 10

Density

8 6

4 2 0 -0,25

-0,15

Var1

0,15

0,05 -0,05 Var1

0,25

Number Observations Minimum Maximum First Quartile Median Third Quartile

101 -0,180 0,145 -0,007 0,015 0,037

Average Variance (n-1) Standard Deviation (n-1) Skewness (Pearson) Kurtosis (Pearson)

0,008 0,003 0,051 -1,084 2,321

Number Observations Minimum

101 -0,189

Maximum First Quartile Median Third Quartile Average Variance (n-1) Standard Deviation (n-1) Skewness (Pearson) Kurtosis (Pearson)

0,122 -0,007 0,016 0,031 0,010 0,003 0,051 -1,076 3,486

Normal(0,008;0,051)

CNE

Density

10 5

0 -0,25

-0,15

Var1

-0,05 Var1

0,05

0,15

Normal(0,010;0,050)

Fig 3 Distribution functions of log-returns for LRT proxy and CNE data.

 Kurtosis is greater than 3 for CNE price and around 2.5 for LRT Proxy, thus density functions are characterized by the fatness of their tails comparing to the density of the Gaussian distribution N(0,1) As it can be seen higher kurtosis distribution have a sharper peak around the mean and longer, fatter tails, while a low kurtosis distribution has a more rounded peak and shorter, thinner tails. For Normal distributions excess kurtosis is cero. We can also say that this is an indication of infrequent extreme deviations, as opposed to frequent modestly sized deviations.  Coefficient of skewness is negative for prices of CNE and LRT Proxy indicating that there is an asymmetry of the probability distribution, namely data are left skewed, i.e. left tail is longer and the mass of the distribution is concentrated on the right of the figure an indication that the market gives higher probability to decreases than to increases in prices.

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4.3 Test of Normality In order to have a clearer picture of the nature of current distribution functions of gas prices in Spain we will use a formal test of normality to provide the foundation to accept o reject the normality distribution of the various functions being analyzed. This material will be used to better assess hypothesis embedded into energy models. To do this, we will be using the frequently used Jarque-Bera (JB) test as it is possibly the most powerful test when a large number of observations is given. The JB test uses the following statistic: 𝐽𝐵 = 𝑛 [

𝑆 2 (𝐾 − 3)2 + ] 6 24

Where S and K are skewness and kurtosis respectively, i.e. the third and fourth moments of the variance. For normal distributions S= 0 and K=3 and hence JB=0. If the JB statistic is sufficiently large, i.e. greater than 6 at 5% significance level, the null hypothesis is rejected. The test interpretation is as follows:  H0: The variable distribution from which the sample was taken, follows a Normal distribution.  H1: The variable distribution from which the sample was taken, does not follow a Normal distribution. As for both CNE_AT and LRT distributions the p value is higher than the one at significance level of alpha=0.05, then the null hypothesis H0 needs to be rejected and H1 accepted. The results for CNE_AT, LRT proxy, NBP and SMP are shown below. Table 1 Jarque-Bera test of normality. LRT JB (Observed value) JB (Critical value) GDL p-valor alfa

CNE 42,446 5,991 2 < 0,0001 0,05

JB (Observed value) JB (Critical value) GDL p-valor alfa

3,157 5,991 2 0,206 0,05

JB (Observed value) JB (Critical value) GDL p-valor alfa

NBP JB (Observed value) JB (Critical value) GDL p-valor alfa

70,607 5,991 2 < 0,0001 0,05

SMP 0,514 5,991 2 0,773 0,05

In view of the results and as expected, we can conclude that both oil-indexed distributions, i.e. LRT proxy and CNE, cannot be regarded as Normal distribu48


tions. Interestingly, both the NBP gas price distribution and the SMP function can be accepted as following a Normal distribution reflecting a more variable pattern typical from true liberalized and liquid markets. This reveals in our understanding that although the oil-gas price link is possibly the main determinant of electricity prices in Spain, its aggregated distribution function is far from normal and therefore assuming normality for further price modelling would be wrong. This is a result to be expected somehow as the process of oil-indexed gas price formation is determined by a rigid set of oil and oil products linked formulas with little room for ‘gas market driven’ price variations. It has to be noted that on the contrary, NBP prices do reflect much better the true fundamentals of a very liquid and deep gas market in which oil-indexed gas contracts do not have until now a significant effect on resulting hub prices. Unfortunately NBP price benchmark is not really a good proxy for the Spanish wholesale price. From this analysis it is also interesting to point out that the rigid structure of oil-indexed gas contracts in Spain, as per analysis of LRT and CNE distributions, show that there seems to be very little impact of liquid hub prices into the formal Spanish gas price formation mechanisms. This result should be expected in a context of last years’ low demand and structural oversupply conditions of Spanish traders.

5 References Balanda KP and MacGillivray HL (1988) Kurtosis: A critical Review Am. Stat. 111-119. Black, Fischer and Myron Scholes, (1973) The Pricing of Options and Corporate Liabilities, Journal of Political Economy, Vol. 81, No. 3, (May/June 1973), pp. 637–654. Capitán Herráiz,A and Rodríguez Monroy C. (2013) Analysis of the traded volume drivers of the Iberian power futures market. Electrical power. Vol 44, p. 431-440, Jan 2013. Capitán Herráiz,A and Rodríguez Monroy C. (2012) Evaluation of the trading development in the Iberian Energy Derivatives Market .EP, Vol.51, p.973-984, Dec 2012. CNE. Informe mensual de supervisión del mercado mayorista de gas. June 2012. Darlington, Richard B. (1970), "Is Kurtosis Really 'Peakedness'?", The American Statistician, 24:2, pp. 19–22. Eydeland A and Kzysztof W (2003) Energy and power risk management.. John Wiley. García-Martos C. (2013).Modelling and forecasting fossil fuels, CO 2 and electricity prices and their volatilities Applied Energy 101,p.363-375, Jan 2013. Gileva T. (2010) Econometrics of Crude Oil Markets. Univertity Paris I Sorbone. Hamilton James D.(2008) Short-term predictability of crude oil markets: A detrended fluctuation analysis approach. National Bureau of Economic research. Hull J. (2012)Options, Futures and Other Derivatives.. Pearson 8th Edition 2012. Helyette G. (2008). Risk Management in Commodity Markets. Wiley. E.,Rockinger M. (2000) Conditional Volatilty, Skewness and Kurtosis. Existence and Perversion.HEC School OF Management. Morgan Stanley Research. (2011). Global Gas. A decade in two halves. Morgan Stanley Blue Paper. March 2011.

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Capabilities Generation Mechanisms in Alliances. Case Based Analysis Morcillo Bellido J1, Duran Heras A2 Abstract This study aims to identify mechanisms used by three large companies (Cisco, Philips and Eli Lilly) - leaders in their respective industries- to develop their alliance capabilities as a key competitive tool. Alliance capability development allows them to get successfully involved in a higher number of alliances; it is being used by these companies to become more agile and competitive in the market. This study attempts to infer a set of “Best Practices” on alliance management.

Keywords: Alliances Capabilities Development, Alliances Mechanisms, Alliances.

1 Introduction The use of alliances as a strategic priority in most dynamic companies has increased during the last decades (Kale et al, 2009). Although the crisis has led to a significant deterioration in the economic activity within Europe and the United States, the interest in alliances has not ceased to grow; it is one of the practices allowing companies to carry out innovative projects in many areas and increasing companies sustainability (Shymko and Diaz, 2012). For instance, new projects developed to improve energy management by applying collaboration models between companies to significantly reduce energy costs (Hansen, 2009) through energy process management integration between a company and its dedicated specialized supplier. Collaboration between organizations is not new phenomenon,

1Jesús

Morcillo Bellido ( e-mail: [email protected]) Escuela Politécnica Superior. Área de Ingeniería de Organización. Universidad Carlos III de Madrid. Avenida de la Universidad nº 30, 28911 Leganés (Madrid) 2Alfonso

Durán Heras ( e-mail: [email protected]) Escuela Politécnica Superior. Área de Ingeniería de Organización. Universidad Carlos III de Madrid. Avenida de la Universidad nº 30, 28911 Leganés (Madrid)

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but it is since the 1980´s that accelerated development of the different types of relationships that we consider alliances, grew faster. Factors such as: i) market globalization and technological development (Porter and Fuller, 1986), ii) the need to fulfill new customer requirements (Ohmae, 1989), iii) difficulties in being competitive on the entire organization value chain (García Ochoa, 2003) and iv) also relevant, scarcity and limited access to resources (Williamson, 1985; Cobianchi, 1994) are main launching factors for fast alliance growth. Spanish economy has not been an exception in this growing alliance relevance as shown in the studies by Menguzzato (1992), Casani (1995), Garcia Canal et al (1998), Rialp and Rialp (1996) and García-Ochoa (2012). However, studies show that between 30% to 70% alliances fail (Bamford et al, 2004); in other words, they do not achieve objectives they were created for and authors like Das and Kumar (2011) have tried to understand root causes.

2 Methodology In the current business environment, alliances are a valuable tool, widely used to improve competitiveness. However they have a very significant failure rate. It is thus particularly relevant to study cases involving companies that have developed a successful “way to manage alliances” and whose strategy is supported by a large amount of these relations, most of them successful. The objective is to identify the mechanisms underlying their alliance management, in such a way that it may be possible to induce and propose some specific practices leading to a higher success rate in alliances. However, their eventual adoption by other companies would require a specific analysis of their suitability for their specific circumstances and the most suitable process of adaptation/dissemination (Duran et al, 1998) Case studies, according to Eisenhardt (1989) and Rialp (1998), are adecuate for aspects that have to do with strategic corporate governance decisions. In fact, Yin advises to use cases where there are not obvious limits between the context and the phenomenon to be observed (1994). Since this paper describes the initial prospective phase of a wider research the case-based approach is particularly appropriate. Therefore, this study is based on the detailed analysis of alliance management mechanisms on three cases: Philips, Cisco, and Eli Lilly. All three companies are leaders in their respective sectors and are working on numerous alliances, which they consider as a pillar of their strategy. They have achieved notable success in this area. Therefore, determining the mechanisms they use may be highly valuable, considering its potential application to other companies.

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The study of these cases combines direct involvement in some of the projects being analyzed (action research) (Coghlan and Coughlan, 2008), with personal interviews and detailed review of the published information.

3 Alliance Capability Development To some authors, alliance capabilities are skills developed to lead them (Draulans et al, 1999) and are based on knowledge and experience accumulation system which converts them into rules and formal procedures. According to Kale et al (2002), alliance capabilities are defined as mechanisms or routines designed to accumulate, integrate and disseminate relevant information from current alliances to improve efficiency and success of the future partnerships. For Draulans et al (2003), those capabilities are defined as the generation of structures within an organization that establishing objectives, plan, control and evaluate each alliance, so that future alliances can be improved based on previous experiences. A study conducted by De Man (2005) - based on 1,390 companies both American and European - concludes that there were some very specific features in companies with the highest level of success in alliances, as indicated in Fig 1:

Companies with higher success on alliances are those with an alliance capability development system implemented (more than 20 points difference)

Formal alliance management systems is more frequently used in American than in European companies

More innovative companies (like Cisco, Microsoft and Sun) have implemented an alliance management formal structure as a part of their organization

Fig 1 Characteristics of successful companies regarding alliances. Source: De Man (2005)

For this author, the comparison between American and European companies leads to the conclusion that the first ones are more successful as a result of the availability of formal systems on alliance capability development.

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4 Philips, Eli Lilly and Cisco Case Studies It is worth highlighting the important number of alliances developed by the three companies considered in this study. According to De Man (2005), just in the period 1998-2002, they carried out: Philips (61), Cisco (56) and Eli Lilly (40). Philips entered into alliances with companies as diverse as those indicated in Table 2: Table 1 Philips alliances examples. Partner

Alliance

ASML LG Electronics Nike Douwe Egberg Beiersdorf (Nivea) TPV

Semi-conductors for innovative applications/products Joint venture to develop LCD technology Sportive range of products Coffee machines (new range) New electric shaver range Joint venture for television integral business

Source: compiled by authors

An analysis of the wide range of alliances set up by this company shows that alliances encompass most of its value chain, from new product development until searching for partners to enter into new markets or alliances to reduce its exposure to low profit businesses. An example of this would be its joint venture with the Chinese company TPV on television sets, where both have contributed with their assets and human teams - Philips also provided the brand - with the common goal of achieving a higher profitability through a very efficient approach in a very competitive market. Both are convinced that results will be better than acting independently, as they did in the past. In 2003, Philips decided to create its Corporate Alliances Office with the aim of achieving a more efficient management in order to improve alliance results. With this purpose, three levels of alliances were identified: corporate, strategic and business unit alliances, depending on the magnitude and impact in the organization. Thus, a strategic alliance involves several business units while a business unit alliance involves only one specific business within the whole organization, leaving the other business units unaffected. Those considered as corporate alliances involve the whole company. Corporate Office was created to support all types of alliances; it takes an executive role in those which are considered as strategic and corporate. When the company decides to enter into an alliance, a specific team is appointed and involved from the very beginning. This team coordinates all the contacts between organization and partner - or partners – in the alliance. Among others, its main activities are: i) to select the right partner, ii) initiate contacts for assessing the interest on 53


the deal by the partner, iii) formalize agreements, iv) appoint the head of the team, v) support and control the alliance. Alliances are so relevant to the company that the Corporate Office reports to a member of the Board of Management. For each alliance, a full time coordinator is appointed, who leads a team of specialists including people from all business areas related to the alliance activity. As for the case of Eli Lilly, a leader in innovation in the pharmaceutical area, the company itself indicates that a large part of its success is based on their alliances, having helped to improve their competitiveness through lower development and research costs and having shorter and faster development cycles than the competition. As in the case of Philips, they carried out alliances with organizations all around the world. Table 2 shows some alliances which are particularly relevant for Eli Lilly: Table 2 Some Eli Lilly alliances. Partner

Alliance

Research Group, Toronto University

Insuline (initial product)

Genentech inc.

New insuline (humalog)

Takeda Chemical Industries

Pioglitazone

Alkermes Inc.

Inhaled insuline

UK National Research and Development Council Source: compiled by authors

Antibiotics

In order to efficiently manage alliances, Eli Lilly had decided to create its Partnerships Office in 1999, which is proactively in charge of: i) identifying areas in which alliances could be desirable, always in close cooperation with the people directly responsible to the specific business unit within the company, ii) finding potential partners with high strategic and cultural fit (versus Eli Lilly), iii) developing agreements iv) monitoring results and taking corrective actions, if needed. This alliance process is supported by certain tools:

3D analysis: a tool used to analyze compatibility with potential partners through three pillars: partner strategic focus, working practices and cultural fit. Comprehensive analysis of the alliance: many items are analyzed and discussed, with the future partner, mainly those having relevance in the future relationship, ranging from the operating procedures to who takes decisions on each issue. Strategic analysis of the future alliance (supported by a specific tool): develops key alliance strategic plans, identifies predictable obstacles and establishes rules that will govern solutions to problems - or conflicts- in the future Voice of the alliance (VOA): this tool audits periodically the alliance situation adjusting any deviations and realigning it towards its objectives

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The primary objective of all this is to increase the likelihood of success on each alliance, reducing the risks that occur both in the start-up phase and in the day to day alliances management. All of the above tools, plus others, have been integrated into a capabilities management model called LAMP (Lilly Alliances Management Process). Eli Lilly believes that systematization is necessary for partnership improvement and that these management principles can be applied in all kinds of agreements, from those with large pharmaceutical companies to those carried out with small biotechnology companies. According to Eli Lilly’s director for alliances, most alliances fail because they involve a lot of people from two or more organizations, with different experiences and expectations, which tend to interpret agreements/objectives and the way to achieve them in a very different way. Eli Lilly considers that only a highly structured organization can handle a virtual scientific collaborators network comprising hundreds of people around the world. To avoid these problems, Eli Lilly has clearly set out functions and responsibilities within the alliances, as shown in Table 3: Table 3 Functions on Eli Lilly alliances. Function

Responsabilities

Global Alliance leader

Manager, from any of partners, with a results improvement target

Functional leader

Specialized people to work on specific areas

Alliance Director

Manager acting as supervisor and “alliance lawyer”, reporting to Alliance Office


With regard to Cisco case study, as the company itself indicates, “collaborative services” provide to their customers a wide range of excellent services, combining Cisco´s know-how with their partners strengths and resources. Customers benefit from a wide alliances network, all under Cisco´s coordination and control. The main argument Cisco uses in support of for this approach is its business vision of “extended enterprise” or supply chain network. It argues that final results achieved in a specific project depend, not only on the company´s resources, but also on those from customers and suppliers. Cisco therefore believes that its competitive advantage is strongly based on its ability to build up teams that collaborate as an extended enterprise in an efficient manner thus solving their customer´s needs. This new paradigm is allowing Cisco to develop - for its clients- strategic technology projects related to IT and communications integration. In the past, these areas were independently managed and now, in Cisco's view, they should be integrated with the aim of improving the productivity and reducing costs. Among its strategic partners, some significant alliances are indicated in Table 4: 55

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 4 Some references of Cisco alliances. Partner

Alliance

Accenture

Accenture Cisco Business Group, to develop process engineering turn-key projects. It can include sub-contracting solutions

IBM

Integrated solutions for specific sectors as financial services and telemedicine

Microsoft

Security, mobility and unified communications projects

Accenture & Personeta

Joint venture to offer added value services to communications companies


According to Cisco, no competitor is currently able to offer a range of solutions as broad and complete as them, because they have made alliances with the best partners in the market, thus establishing a competitive edge over the rest. The company has established a top level organization (lead by Alliance VicePresident), who has the mission to identify, organize, manage and control all type of alliances. To carry out its daily work, Cisco set up as many multidisciplinary teams as existing partnerships. Those teams, supervised by the Alliance Director, work intensely on each project ensuring performance and identifying deviations, conflicts or risk areas. These teams are specifically trained on alliance management techniques and count on support from the central alliances group. Who supervises, supports and controls the set of projects

5 Conclusions The three companies have established a structure within their own organizations whose specific mission is to identify, evaluate, negotiate, manage and control current and future alliances. Their objectives are fully aligned with the business and their results are evaluated according to the success of their partnerships. This structure reports to top management and has broad responsibilities in alliance management, from identification of alliance needs - along with the responsible person from the related business area - until its implementation and results monitoring during the alliance life cycle. The three companies have developed, with small differences probably attributable to their own corporate culture, a set of procedures and activities that have proved their added value in alliance generation and management. In addition the structure has been endowed with a strict process control system. Whenever an alliance opportunity is identified, it is evaluated by the abovementioned structure and when feasible - if it fits the strategy and culture of the company- negotiation process is started with the potential partner. 56


The three companies have developed a mechanism that supports alliance capability development. This is a fundamental pillar to manage the important number of alliances they successfully execute. This is the usual way of working in all these three companies, allowing them to carry out alliances without requiring an additional effort, which may stress the organization and distract organic business resources. The remarkable parallelism and similarity observed in the approach adopted for alliance management by the three companies analyzed, selected as “Best of Breed” in their respective sectors and specifically in alliance development, suggests that the common practices described here could be considered as Best Practices in this area. They could therefore be potential candidates for adoption by others firms, however companies considering adopting them should carefully assess their fit with their specific characteristics and circumstances.

6 References Bamford J, Gomes-Casseres B, Robinson M (2004). Envisioning collaborating: Mastering alliances strategies. San Francisco: Jossey-Bass Casani F (1995). Una aproximación empírica a la cooperación inter-empresarial en España, Información Comercial Española. Revista de Economía, octubre, nº 746, pp. 104-117 Cobianchi T T (1994). Relationships among strategic alliance factors and strategic alliance success. UMI Dissertation Service Coghlan D, Coughlan P (2008). Action Learning and Action Research (ALAR): A Methodological Integration in Inter-Organizational Setting. Systemic Practice & Action Research, vol. 21, nº 21, pp. 97-104 Das TK, Kumar R (2011). Regulatory Focus and Opportunism in the Alliance Development Process. Journal of Management, vol. 37, nº 3, May 2011, pp. 682-708 De Man A (2005). Alliance capability. Comparison of alliance strengths of european and american companies. European Management Journal Vol. 23, No. 3, pp. 315–323 Draulans J, de Man A, Volberda H W (1999). Alliances: searching a different way, Benelux Management Review, nº 63 pp. 52-83 Durán A, De Mora C, Peire J, Castro M (1998) Diffusion of Information Technology Management Capabilities in Global Business: a Comparison of Intra-and Inter-Company Experiences. 4th World Conference International Federation of Scholarly associations of Management (IFSAM). Eisenhardt K M (1989). Building theories from case research. Academy of Management Review, vol. 14, nº 4, pp. 532-550. García Canal E, López Duarte C, Rialp Criado J, Valdés Llaneza A (1998). Las estrategias de cooperación como medio de internacionalización. Experiencias de las empresas españolas. Barcelona: Ed. Del Centro de Economía Industrial. García-Ochoa y Mayor M (2003). Estrategia competitiva y tipos de alianzas entre empresas, XIII Congreso Nacional de ACEDE, Salamanca. García –Ochoa y Mayor M. (2010). Estudio empírico de la cooperación empresarial en España. Dirección y Organización nº 27, febrero 2012, pp. 139-147 Hansen, S (2009). ESCOs around the World. The Fairmont Press

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Jiménez P y Sánchez J D (2005). Tendencias de cooperación en sectores maduros: el caso del sector agroalimentario español. Ecos de Economía, nº 20, pp. 50-92. Kale P, Dyer J H, Singh H (2002). Alliance capability, stock market response and long – term alliance success: the role of the alliance function. Strategic Management Journal, vol. 23, nº 8, pp. 747-767 Kale P, Singh H, Bell J (2009). Relating well: Building capabilities for sustaining Alliance networks. P Kleindorfer & Y Wind Eds., The network challenge: Strategies for managing the new interlinked enterprise. Pearson Press, London Menguzzato M (1992). La cooperación: Una alternativa para la empresa de los 90.Revista de Dirección y Organización, nº 4, pp. 54-62 Ohmae K (1989): The global logic of strategic alliances. Harvard Business Review, March-April Porter M E, Fuller M B (1986). Coalitions and global strateg. En M. E. Porter /Ed. Competition in Global Industries. Harvard Business School Press. Rialp A (1998). El método del caso como técnica de investigación y su aplicación al estudio de la función directiva. IV Taller de Metodología. Sesión: Técnicas de la Investigación Cualitativas. Análisis de casos. La Rioja Williamsson O E (1985). The economic institutions of capitalism: firms, markets, relational contracting. Nueva York: Free Press Shymko Y, Diaz A (2012). A resource dependence, social network and contingency model of sustainability in supply chain alliances. Int. J. Business Excellence, Vol. 5, nº 5, pp. 502-520 Yin R K (1994). Case study research: design and methods. Berverly Hill, Sage.

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Best Practices in Sustainable Supply Chain Management: A Literature Review Mejías A.M1, Pardo J.E2 Abstract On the basis of a content analysis, this paper explores the evolution of the best practices from the traditional approach of cost efficiency in the supply chain management to the current context of sustainability. In this sense, the paper shows a comprehensive review of the best practices that supply managers will need to engage in to crease a sustainable supply chain. Our analysis suggest that the practices that lead to a more sustainable supply chain management are equal parts best practices in traditional supply chain management or slight modifications of existing practices and innovative practices.

Keywords: Best Practices, Literature Review, Logistics, Sustainable Supply Chain Management (SSCM).

1 Introduction As the new economic order unfolded, people recognized that profits and profitability were only one element in the long-term success of companies and the economies. Also important are the future of people and the future of planet Earth (Kleindorfer et al., 2005). These new legitimacy concerns are captured in measures as the triple bottom line. According to Carter ad Rogers (2008), the triple bottom line suggest that at the intersection of social, environmental and economic performance, there are activities that organizations can engage in which not

1Ana

Mª Mejías Sacaluga ( e-mail: [email protected]) Grupo OSIG. Dpto. de Organización de Empresas y Marketing. Escuela de Ingeniería Industrial. Universidad de Vigo. C/Maxwell 9, Campus Lagoas-Marcosende, 36310 Vigo. 2Juan

E. Pardo Froján ( e-mail: [email protected]) Grupo OSIG. Dpto. de Organización de Empresas y Marketing. Escuela de Ingeniería Industrial. Universidad de Vigo. C/Maxwell 9, Campus Lagoas-Marcosende, 36310 Vigo.

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only positively affect the natural environment and society, but which also result in long-term economic benefits and competitive advantage for the firm. Those new trends of thinking suffered a great development in more recent times. It was in the past decade of 2000 when concepts of Corporate Social Responsibility (CSR), Green or Sustainability and Supply Chain Management (SCM) began to be dealt with a joint way in literature. In this paper, the term sustainability (sometimes only “green”) is used as a synonym for corporate social responsibility (Stokes and Harris, 2012). According with Seuring and Müller (2008), we define sustainable supply chain management (SSCM) as “the management of material, information and capital flows as well as cooperation among companies along the supply chain while taking goals from all three dimensions of sustainable development (economic, environmental and social) into account which are derived from customer and stakeholder requirements”. However, although the literature of SSCM has been evolving fast, the most of the companies are still searching for the best way to implement sustainability principles into their supply chain. Likewise, Andersen and Skjoett-Larsen (2009) point out that despite many multinational corporations´ efforts to implement social and environmental issues in their supply chains, a gap exists between the theoretical application of sustainability in SCM in theory and the implementation in practice. For other authors (Gold et al., 2010), the literature on SSCM is still limited, focused on the study of the concrete fields (for example, the research is very limited on exploring the social dimension of sustainability), and scant in literature reviews. In this context, and taking into account that the question for companies has become not whether to commit to a strong environmental, health and safety record, but how to do so in the most cost-effective manner (Kleindorfer et al., 2005), the aim of his paper is to explore the evolution of the best practices from the traditional approach of efficiency in the SCM to the current context of sustainability. This paper conducts a comprehensive literature review from a holistic perspective, integrating the triple bottom line with all the logistics activities along the SC: purchasing, production, warehouse and transportation and reverse logistics.

2 Methodology A literature review is a systematic, explicit, and reproducible design for identifying, evaluating, and interpreting the existing body of recorded documents (Fink, 2005). Literature reviews usually aim at two objectives: first, they summarize existing research by identifying patterns, themes and issues; second, they may constitute and initial step in the theory development process (Meredith, 1993). From a methodological point of view, literature reviews can be comprehended as content analysis. Content analysis is a method for the objective, systematic, 60


quantitative and reliable study of published information, i.e. a suitable method for comprehensive literature reviews (Pasukeviciute and Roe, 2005). A process model for a content analysis is described in four steps (Seuring and Müller, 2008): Material collection: the material to be collected is defined and delimitated. Descriptive analysis: formal aspects of the material are assessed. Category selection: structural dimensions and related analytic categories are selected, which are to be applied to the collected material. Material evaluation: the material is analyzed according to the structural dimensions. This should allow identification of relevant issues and interpretation of results. According to Spens and Kovács (2006), content analysis can be used as an instrument for determining key ideas and themes in publications but also, according with our case, for measuring comparative positions and trends in reporting.

2.1 Sample and Delimitations of the Research The first step in content analysis is to determine the documents to be analyzed and the units of analysis. As this literature review aims at study the evolution of best practices in logistics activities that lead to a more SSCM, we selected logisticsrelated journals for the sample. The logistics journals selected are perceived as of highest quality and represent the state of the art of logistics research (in alphabetical order): European Journal of Purchasing & Logistics Management, Harvard Business Review, International Journal of Integrated Supply Management, International Journal of Logistics Management, International Journal of Operations & Production Management, International Journal of Physical Distribution & Logistics Management, International Journal of Production Economics, International Journal of Production Research, Journal of Business Logistics, Journal of Cleaner Production, Journal of Operations Management, Production and Operations Management, Purchasing and Supply Management, Supply Chain Management: an International Journal, Transportation & Distribution and other journals. The time period of the literature review was defined between 1990 and 2011. After a first quick content check, identified articles were included or excluded from the analysis. This first phase involved using the preliminary keyword “best practices” to guide the research by identifying the papers that explicitly included that keyword in this title, abstract and/or full text. The papers that did not meet the practical approach in conducting the literature review were excluded (i.e., mathematical models of SSCM, theoretical approaches related to different organizational theories, technical issues –minimizing CO2 emissions, … -, or case studies focused in specific fields - energy, oil and gas industry, … -).

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Taken the stated delimitations into account, a total of 105 papers were identified. The list of revised papers is available on request.

2.2 Categorization in the Coding Scheme Content analysis builds on a coding scheme that is developed on the basis of a theoretical framework. In order to derive patterns in the presentation and reporting of information, content analysis involves the codifying of information into predefined categories (Guthrie et al., 2004). The second phase of the research involved the application of the keywords listed below and different combination of them:  Cost (reduction)  Efficiency  Environment (al)  Green  Lean (operations, manufacturing)  Logistics (management, network)  Manufacturing  Operations management  Performance  Production (management)  Purchasing (management)  Reverse logistics (or supply chain)  Social Responsibility  Supplier  Sustainability (or sustainable)  Supply chain management  Transportation  Vendor  Warehouse (management)

3 Frequency Analysis As we stated before, 105 papers were identified in the literature review in the research period (1990-2011). While 1991 is the first year where papers about traditional best practices (economic efficiency approach) in Logistics/SCM were found, the greater number of publications of these practices is found for the time period between 1995 and 2001. Instead, the greater number of publications of sus62


tainable best practices is found since 2006. The distribution of the papers in the research period is shown in Figures 1 and 2.

4 Best Practices: from Cost Efficiency to Sustainability As a result of the content analysis, the best practices identified were classified into two broad categories: traditional (economic efficiency point of view) and sustainable. Then, for each category, the practices were sorted in four subcategories based on their application: throughout the supply chain, in purchasing management, in production management, in warehouse and transportation (W&T) management and in reverse logistics management. We show a synthesis of our findings due to reduction reasons. First, we list the traditional and sustainable best practices with general application throughout the entire supply chain. Then, we show in Table 1 the evolution of the best practices for each logistics area, identifying: traditional practices without and with continuity in the context of sustainability (TP-Discontinuity, TP-Continuity), sustainable practices which are modifications of existing practices (SP-Modification) and innovative sustainable practices (SP-Innovation). This is the list of traditional and sustainable best practices with general application:  Traditional practices: – Quality and environmental management systems implementation (under the international standards ISO 9000, ISO 14000 and Eco-Management and Audit Scheme of the European Union). – Coordination between buying and supplying organizations. – ICT implementation.  Sustainable practices: – Reporting on different standards (focused on codes of conduct, product/process-related or management systems and initiatives). – Collaborative behaviors with suppliers and customers. – Collaborating with nontraditional chain members (NGOs, Competitors, Trade groups,…). – Designing and managing processes to achieve transparency and traceability. – Addressing the governance structure for SSCM. – Benchmarking in sustainability. In Figures 1 and 2 the frequencies of the two broad categories occurrence are displayed.

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Fig. 1 Distribution of papers related to traditional best practices across the research period (Note: three relevant papers were founded and 1988 and 1989 were added to the research period)

Fig. 2 Distribution of papers related to sustainable best practices across the research period

Table 1 shows the evolution of the best practices for each logistics area. Table 1 Best practices: from efficiency to sustainability TP-Discontinuity

TP-Continuity

SP-Modification

SP-Innovation

Purchasing Supplier requirements Supplier selection to reduce cost annually

Long-term relationships Local suppliers develwith suppliers opment

Supplier requirements Supplier certification of warehouses

Codes of conduct

Reward systems linked to sustainability

Collaborating with sup- Traceability and collab- Transparency and ethics pliers oration with suppliers in purchasing Supplier development Ensuring supplier con- Reducing supplier risk tinuity

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) Best practices: from efficiency to sustainability TP-Discontinuity

TP-Continuity

SP-Modification

SP-Innovation

Production Relocation of facilities Just in time operations Sustainable products and process design (low labor cost) Layout optimization

Outsourcing

Postponement

Closed-Loop SC

Waste Management

Green manufacturing and remanufacturing

Source-Reduction and Pollution prevention

Lean production W&T Reduction of the num- Inventory reduction ber of warehouses Full truck deliveries

Environmnetal Conscious Design (ECD) and LifeCycle Analysis (LCA)

Cross-docking

Lean-Green synergies Lean-Green operations Inventory reduction and proper storage of hazardous materials

Donation of excess or obsolete inventory

Recyclable and reusa- Reverse logistics, minible packaging and con- mizing traffic and reductainers ing noise pollution

Intermodal transporta- Clean transportation tion/fuel efficiency

Reward systems linked to sustainability

Efficient delivery Extending JIT/lean ap- Economic+environmental (standardization in proach to warehouse +safety as a selection cripackaging and delivery and transportation teria of for-hire carriers units, …) Reverse Logistics Efficient management Just in Time in reverse Redesigning logistics Closed-Loop Supply of returns logistics networks to accommo- Chains date returns Systems of selected ICT as support of RL collection of materials value measurement

To integrate the financial impact of RL strategies

5 Discussion and Conclusions The confluence of the core-competency and process management movements caused many of the changes in the 1990s. As companies developed their core competencies and included them in their business processes, the tools and concepts of TQM and JIT, and afterward Lean approach, were applied to developing new products and managing the supply chain (Kleindorfer et al., 2005). But, the literature review of the best practices for effective SCM shows that inter-firm competitive advantage has been mainly focused in profit criteria. Over the past two decades, increasing pressures from governments, customers and other stakeholders groups have prompted firms to incorporate sustainability issues into their SCM schemes. However, these external pressures on a firm only lead to sustainable supply and production if both the individual firms and the sup65


ply chain as a total entity develop the necessary relevant internal resources as prerequisites for implementing SSCM (Bowen et al., 2001). In this context, the most of the companies are still searching for the best way to implement sustainability principles into their supply chain. Our analysis shows that the practices that lead to a more SSCM are equal parts best practices in traditional SCM or slight modifications of existing practices and innovative practices. However, to gain positive results, the firm must establish management systems and tools that integrate environmental, health and safety metrics with other process metrics within the company and across the SC. In this sense, Rothenberg et al. (2001) examined the links between lean and green and found some synergies but also found that harvesting them is not simple. SCM researches and practitioners are just beginning to face new challenges in integrating sustainability in their areas of interest.

6 References Andersen M, Skjoett-Larsen T (2009) Corporate Social Responsibility in global supply chains. Supply Chain Management: an International Journal, Vol. 14 No. 2, pp. 75-86 Bowen FE, Cousins PD, Lamming RC, Faruk AC (2001) The role of supply chain management capabilities in green supply. Production and Operations Management, Vol. 10 No. 2, pp. 174189 Carter CR, Rogers DS (2008) A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution & Logistics Management, Vol. 38 No. 5, pp. 360-387 Fink A (2005) Conducting research literature reviews: from the internet to paper. Sage, Thousand Oaks Guthrie J, Petty R, Yongvanich K, Ricceri F (2004) Using content analysis as a research method to inquire into intellectual capital reporting. Journal of Intellectual Capital, Vol. 5 No. 2, pp. 282-293 Kleindorfer PR, Singhal K, Van Wassenhove LN (2005) Sustainable operations management. Production and Operations Management, Vol. 14 No. 4, pp. 482-492 Meredith J (1993) Theory building through conceptual methods. International Journal of Operations & Production Management, Vol. 13 No. 5, pp. 3-11 Pasukeviciute I, Roe M (2005) Strategic policy and the logistics of crude oil transit in Lithuania. Energy Policy, Vol. 33 No. 7, pp. 857-866 Rothenberg S, Pil FK, Maxwell J. (2001) Lean, green and the quest for superior performance. Production and Operations Management, Vol. 10 No. 3, pp. 228-243. Seuring S, Müller M (2008) From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, Vol. 16, pp. 1699-1710 Spens KM, Kovács G (2006) A content analysis of research approaches in logistics research. International Journal of Physical Distribution and Logistics Management, Vol. 36 No. 5, pp. 374-390 Stokes P, Harris P (2012) Micro-moments, choice and responsibility in sustainable organizational change and transformation: the Janus dialectic. Journal of Organizational Change Management, Vol. 25 No. 4, pp. 595-611

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State of the Art of Challenges on International Operations Management for SMEs Martínez S1, Mediavilla M, Errasti A, Santos J, Mula J Abstract In the current global economy, the design and management of global production and logistics networks has become a crucial issue for all type of companies, especially for Small and Medium size Enterprises (SMEs). Consequently, many researches have been done about this topic, but it is not clearly classified or analyzed in depth. After reviewing the literature, it has been found that the most important challenges related to global operations configuration and management are: new facility implementation, global suppliers network development and multi-site production network configuration. This paper presents the state of the art grouped by the three main challenges exposed.

Keywords: Facility implementation, suppliers development, multi-site, internationalization

1 Introduction Until recently, the focus of Operations Management for SMEs was on domestic markets or regional areas, i.e. most production processes were performed within the borders of a country. Although some producers imported their raw materials, all production and related finishing processes were executed within the same country. Moreover, the majority of the products were consumed locally, which meant managers were rarely involved in processes that went outside of their national borders.

1

Sandra Martínez Miguélez ( e-mail:[email protected]) Dpto. de Organización de Empresas, Tecnun, Universidad de Navarra. Paseo Manuel Lardizabal, 13, 20018 San Sebastián *This research is being funded by the Ministry of Science and Education of Spain project, entitled ‘Operations Design and Management in Global Supply Chains (GLOBOP)’ (Ref. DPI2012-38061-C02-01).

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But nowadays, in addition to the multinational companies (MNEs), the SMEs are also engaging in international production. In this current global economy, with an increased international presence of all type of organizations in order to take opportunities that exist in the markets worldwide, the design and management of Global Operations Networks (GON) plays a vital role in organizational competitiveness: the GON need to cover multiple regions and cope with higher network complexity (Shi and Gregory, 1998), connecting markets to global supply and manufacturing sources beyond any geographical border. By the examination of the literature we found that the most important challenges related to the GON configuration of the industrial companies (specifically SMEs) could be summarized in the following three core issues: New facility implementation (Barnes, 2002; Abele et al., 2008; Kinkel and Maloca, 2009; Azevedo and Almeida, 2011); global suppliers network development (Leenders et al., 2002; Van Weele, 2005; Meixell and Gargeya, 2005); and multi-site production network configuration (Ferdows, 1997a; Vereecke and Van Dierdonck, 2002; Shi and Gregory, 2005; Vilana and Rodríguez, 2009; Rodríguez and Vilana, 2010; Feldmann and Olhager, 2010; Mediavilla et al., 2012). In order to contribute to the literature on the design and management of GON, this paper will define some core concepts and then will review the literature on international operations strategy and management, with a specific focus on the most important findings and research gaps on the three presented challenges for SMEs. The paper concludes by highlighting some future research opportunities and conclusions.

2 Literature Review As a result of the internationalization trend and in order to take the opportunities that exist in markets worldwide, companies have now a global presence (Veerecke and Veerecke, 2007); in fact, the globalization could be defined as “an emerging trend of global markets for consumer goods with a significant and unexpected magnitude” (Levitt, 1983). Other authors have mentioned “the reality of a global competition” (Prahalad and Doz, 1987) or (the) “new globalization era” (Barlett and Ghoshal, 1989). Consequently, to respond to this homogenization of markets worldwide, the internationalization is a strategic business decision (Root, 1994). The main factors driving the internationalization phenomenon are (Ferdows, 1997a; Farrell, 2006): off shoring, entering new markets, disaggregating the value chain and reengineering the value chain, and creating a new product and market. Concerning operations, its internationalization is understood as the deployment of enterprise resources beyond their home country, i.e. locating people and assets in order to carry out primary activities of the value chain. Thus, the internationalization of manufacturing networks means carrying out disaggregated value chain 68


activities (i.e. engineering, purchasing, manufacturing and distribution) beyond a company’s home country, which requires greater coordination in order to get acceptable levels of quality, flexibility and cost (De Meyer et al., 1989). Therefore, it is important to take into account that increased commitment abroad does not only promise opportunities, but it is also fraught with risk. The internationalization of operations can take different forms and includes the development of new configurations such as international distribution systems, networks of global suppliers, and multi-site and/or fragmented manufacturing networks. However, fragmentation of production processes and the multi-location of activities have gained a great relevance, especially for SMEs which have limited resources, limited market knowledge and limited use of networks (Kalinic and Forza, 2012).

2.1 New Facility Implementation When starting up business and operations overseas, the business managers usually try to reduce the implementation time, reduce one off expenses, reduce risk and avoid entry barriers by establishing strategic alliances with local partners (Joint Ventures). However, it is not always possible to find the suitable partners. In this case, the company can opt to settle down value chain activities by its own, such as the implementation of a new production plant starting up from scratch (Greenfield approach) (Meyer and Estrin, 2001). According to Barnes (2002), the implementation of a new production plant starting from scratch is the strongest step of any organization that seeks to internationalize. Besides the obvious economic investment, the establishment and subsequent management of the production facilities require a broad range of knowledge and skills related to operations management (Barnes, 2002): human resource management, purchasing and supply management, develop agreements with local logistics suppliers, post-sales services for local customers and global operations management. There is an alternative approach when establishing new productions plants abroad, which consists of establishment through acquisition of existing resources in the country of destination (Brownfield approach) (Hennart and Park, 1993; Meyer and Estrin, 2001). This implies a previous scanning of the resources through a process of Merger and Acquisitions (tasks such as audits, due diligences, etc.) and could involve the purchase of assets (buildings, means of production, etc.), the acquisition of part, all existing commercial networks or even an existing production unit (human resources included). In these cases, there might be a number of contingencies (Barnes, 2002): responsibility for agreements that may exist before, integration into the operation practices of the organization, differences in

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technology and production equipment purchasing practices and procedures, and incompatibility of the acquired information systems. As a consequence of all mentioned risks and contingencies, the implementation of new facilities and the suppliers network development requires a careful planning coordination and also different adjustments which can be costly in time and resources (Abele et al., 2008). Furthermore, the lack of coordination between involved agents causes ramp-up delays in time and volume, and production losses (Abele et al., 2008). In fact, companies, when assessing production locations abroad both with Greenfield and Brownfield approach, tend to underestimate the ramp-up times that are necessaries for securing process reliability, quality and productivity (Abele et al., 2008; Martínez et al., 2012). Moreover, new plants also need to take into account requirements as e.g. flexibility, scalability or agility (Azevedo and Almeida, 2011) in order to cope with the dynamic and volatile market environment. To sum up, several authors (Vereecke and Van Dierdonck, 2002; Shi, 2003; Kinkel and Maloca, 2009) stress the importance of: (1) managing accordingly the numerous risks and different circumstances that appear during the entire facility implementation –in order to avoid disadvantages during the process; and (2) building models or frameworks should be a focus of researches on operations and supply chain management. It could help practitioners to design and manage their production networks, especially when international operations are taking place.

2.2 Global Suppliers Network Development The development of competitive raw materials and components markets causes that the main producer must develop an outsourcing strategy. So, more and more main producers have a fragmented production system, where the suppliers network is composed by local or domestic suppliers and offshore suppliers. These offshore suppliers need the coordination of quality control, delivery time with a long lead-time gap between response time, and customer delivery time. Thus, justin-time (JIT) principles are not applicable in depth and a decoupling point could be needed. Furthermore, although the original suppliers networks where usually next to the main producer locations, due to the internationalization operations tendency multiple configurations are possible. Meixell and Gargeya (2005) state that the raw materials, components, manufacturing, and assemblies stages could be locally or globally configured. Therefore, the following question arises: Which part of the supply chain should be globalized or localized? Regarding the sourcing, the purchasing function has changed from a passive administrative role into a strategic function that contributes to creating a competitive advantage as other business functions do (Alinaghian and Aghadasi, 2006). 70


Van Weele (2005) defined global purchasing as “the activity for searching and obtaining goods, services and other resources on a possible worldwide scale, to comply with the needs of the company and with a view to continuing and enhancing the current competitive position of the company”. Moreover, the global purchasing management is one of the first steps to define and design a global supply chain development (Leenders et al., 2002). In the new purchasing function, it is necessary to provide a solution to the following challenges, risks and characteristics (Errasti, 2012): (1) define the purchasing strategy for each product family in the supplier market, (2) collect suppliers’ value-added proposals and develop appropriate suppliers, (3) define the contract management in the contract life cycle, (4) centralized or decentralized structure (5) relate supplier management to quality assurance in new product development, (6) reduce total cost ownership, (7) face the different supply chain configurations.

2.3 Multi-site Production Network Configuration Defining and managing the roles of individual plants is a critical component for optimizing the performance of GONs because this enables the alignment of the business strategy with operations across the network (Shi and Gregory, 2005; Vilana and Rodríguez, 2009). The optimization of a GON is dependent on the specialization of activities and capabilities that individual plants within the network develop (Ferdows, 1997a). It is therefore important to align the way in which each plant is managed with the requirements of the entire network. The questions that still remains unanswered in the multisite production configuration is how to deploy the operations strategy in a multi-location GON and, in particular, how to balance the different competences and responsibilities of individual plants within the network, taking into account that each plant could develop specific capabilities or used by the whole GON. Ferdows (1997a) proposed a model that identifies different strategic roles that plants within a GON can fulfill and provided a development path to increase the competencies of individual plants in pursuit of higher strategic roles. Whilst Ferdows’ work provides a useful starting point for designing or re-structuring the operations of plants within a GON there is little evidence of the application of the model beyond the work by Vereecke and Van Dierdonck (2002). This particular study discusses the application of Ferdows’ model to the decision making process of establishing and/or acquiring a new production unit. However, it does not look into how the competencies of the production units within the existing network can be developed to enable the adoption of a higher level strategic role. Then, Mediavilla and his colleagues (2012) made a contribution to current knowledge on global operations by extending the model proposed by Ferdows (1997a) and oper-

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ationalizing it to enable its application for the design and optimization of global operations networks. To generate new insights into the application of the model further empirical research is required (Netland, 2011). Furthermore, it is clear that more research is needed to understand the evolution and operations coordination of individual production units within a network of manufacturing facilities (Shi and Gregory, 1998; Shi and Gregory, 2005; Rodríguez and Vilana, 2010). Models and techniques to aid practitioners formulating and developing operations strategy when designing or restructuring a GON are lacking (Vereecke and Van Dierdonck, 2002) and the study areas are dispersed (Corti et al., 2009; Laiho and Blomqvist, 2010), which results in difficulties to renew competences and capabilities of individual facilities (Sweeney et al., 2007). In summary, the new paradigm in global operations strategy is the need for continuous reconfiguration of the manufacturing systems and operations of a GON to adapt to a dynamic environment. The questions that still remain unanswered in these regards are (1) how to balance the strategic roles, competencies and responsibilities of multiple plants within a GON and (2) how to deploy the operations strategy within a GON where individual plants require to simultaneously and continuously develop their capabilities to remain competitive.

3 Discussion The facility starting up process and the supply development are some of the most difficult decisions to make (Barnes, 2002) because it implies many risks (Kinkel and Maloca 2009) – not only MNEs but also for SMEs which resources are usually more limited (Kalinic and Forza, 2012). Almost every company is nowadays affected by at least some kind of international challenge. However, the results on this process are not always successful, as e.g. in 67% of the offshore facilities analyzed, the personnel rotation level is higher than in the headquarters and it depends on whether it is an emergent zone or not (Errasti and Egaña, 2009).Then, facing the management of a production logistics network in different countries requires a greater coordination. Operations strategy has to gain more effectiveness and efficiency over operations resources through defining and implementing suitable decisions, managing tangible resources, and developing operations capabilities to reach the performance objectives of the market requirements (Slack and Lewis, 2002). Whilst all type of organizations are facing significant challenges for managing increasingly complex global operations, current literature on GON is still limited in its scope (Corti et al., 2009; Laiho and Blomqvist, 2010). The question that still remains unanswered is how to deploy the operations strategy in a multi-location GON and, in particular during the new facility implementation, the global suppli72


ers network development and the multi-site network configuration (Ferdows, 1997a; Vereecke and Van Dierdonck, 2002, Shi, 2003; Kinkel and Maloca, 2009). Models and techniques to aid practitioners formulating and developing operations strategy when designing or restructuring a GON are lacking (Vereecke and Van Dierdonck, 2002) and the study areas are dispersed (Corti et al., 2009).

4 Conclusion Even though there are many researches related to the international operations management, it has not still found a specific state of the art about the main challenges that SMEs have to face. Hence, this study claims to be a reference in this topic for future research, which should be focused on one of the tree above mentioned challenges: new facility implementation, global suppliers network development, multi-site production network configuration. Moreover, to develop a framework that helps to cope these challenges would be very useful for industrial companies, especially for SMEs. Regarding to future research, the main issues are: (i) Operations and Supply Chain management researchers should pay attention to providing understandable frameworks of international manufacturing systems, which could help managers to design and manage their networks (Vereecke and Van Dierdonck, 2002; Shi, 2003); (ii) the frameworks for new production plants overseas should take into account the necessary requirements for the next generation of factories, which have to be modular, scalable, flexible, agile and to be able to adapt, in real time, to the continuously changing market demands, technology options and regulations (Kinkel and Maloca, 2009, Azevedo and Almeida, 2011); and (iii) more research is needed to understand how to design and keep the coordination of the global supply network with different delivery times and procurement reliability (Meixell and Gargeya, 2005; Abele et al., 2008).

5 References Abele E, Meyer T, Näher U, Strube G, Sykes R (2008) Global production: a handbook for strategy and implementation. Springer. Heidelberg, Germany Alinaghian LS, Aghadasi M (2006) Proposing a model for purchasing system transformation. Paper presented at the EurOMA 16th Conference, Glasgow, Scotland Azevedo A, Almeida A (2011) Factory Templates for Digital Factories Framework, Robotics and Computer-Integrated Manufacturing, 27:755-771 Barnes D (2002) The complexities of the manufacturing strategy formation process in practice, International Journal of Operations & Production Management, 22(10):1090 – 1111. Bartlett CA, Ghoshal S (1989) Managing across borders. The transnational solution, Harvard Business School Press, Boston, MA

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Corti D, Egaña MM, Errasti A (2009) Challenges for off-shored operations: findings from a comparative multi-case study analysis of Italian and Spanish companies, Paper presented in Proceedings 16th annualEurOMA Conference, Gothenburg De Meyer A, Nakane J, Miller J, Ferdows K (1989) Flexibility: the next competitive battle the manufacturing futures survey, Strategic Management Journal, 10:135-44 Errasti A (2012) Gestión de compras en la empresa, ediciones Pirámide, Grupo Anaya, p.280, Madrid Errasti A, Egaña MM (2009) Internacionalización de operaciones: estado del arte, Cluster de movilidad, logística y transporte, San Sebastián, España Farrell D (2006) Offshoring. Understanding the Emerging Global Labor Market, Mckinsey Global Institute, Harvard Business School Press Feldmann A, Olhager J (2010) Linking networks and plant roles: The impact of changing a plant role. Paper presented in Proceedings of the 17th EurOMA conference, Porto, June 6-9 Ferdows K (1997a) Making the most of foreign factories”, Harvard Business Review, March – April, pp.73-88 Hennart JF, Park, YR (1993) Greenfield versus acquisition:The strategy of Japanese investors in the United States. Management Science, 39:1054-1070 Kalinic I, Forza C (2012) Rapid internationalization of traditional SMEs: Between gradualist models and born globals, International Business Review, 21:694–707 Kinkel S, Maloca S (2009) Drivers and antecedents of manufacturing offshoring and backshoring. A German Perspective, Journal of Purchasing & Suppply Management, 15:154-165 Laiho A, Blomqvist M (2010) International Manufacturing Networks: a literature review. Paper presented in17th Conference EurOMA, Porto Leenders M, Fearon HE, Flynn AE, Johnson PF (2002) Purchasing and Supply Management. McGraw Hill/Irwin, New York Levitt T (1983) The globalization of markets, Harvard business review, 61(3): 92-102 Martínez S, Errasti A, Arcelus M (2012) Diseño de operaciones globales ayudado por herramientas de simulación: un estudio empírico, DYNA, 87(3):286-294 Mediavilla M, Errasti A, Mendibil K (2012) Value Chain based framework for assessing the strategic plant role and deploying an improvement roadmap in global operations networks: an empirical study, Production Planning & Control – Forthcoming 2013 Meixell M, Gargeya, V (2005) Global Supply Chain Design: A literature Review and A Critique, Transportation Research Part E., 41:531 Meyer KE, Estrin S (2001) Brownfield Entry in Emerging Markets. Journal of International Business Studies, 32(3):575-584 Netland T (2011) Improvement programs in multinational manufacturing enterprises: a proposed theoretical framework and literature review, Presented in proceedings of Euroma 2011 conference, Cambridge, UK Prahalad CK, Doz Y (1987) The Multinational Mission: Balancing Local Demands and Global Vision, Free Press, New York, NY Rodríguez Monroy C and Vilana Arto JR (2010) Analysis of Global Manufacturing Virtual Networks in the Aeronautic Industry, International Journal of Production Economics 126(2): 314-323 Root F (1994) Entry strategies for international markets, Lexington Books, London Shi Y, Gregory M (2005) Emergence of global manufacturing virtual networks and establishment of new manufacturing infrastructure for faster innovation and firm growth. Production Planning & Control. 16(6):621-631 Shi Y (2003) Internationalization and evolution of manufacturing systems: classic process models, new industrial issues, and academic challenges, Integrated, Manufacturing Systems, 14:385-96 Shi Y, Gregory MJ (1998) International Manufacturing Networks – to develop global competitive capabilities, Journal of Operations Management, 16:195-214

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Slack N, Lewis M (2002) Operations Strategy. Upper Saddle River, Prentice Hall, 2nd Edition Sweeney M, Cousens A, Szwejczewski M (2007) International manufacturing networks design A proposed methodology, Paper presented in EurOMA conference, Ankara Van Weele AJ (2005) Purchasing and Supply Chain Management. Thompson Learning, London. Vereecke A, Vereecke A (2007) Network relations in multinational manufacturing companies. Flanders DC and Vlerick Leuven Gent Management School Vereecke A, Van Dierdonck R (2002) The Strategic Role of the Plant: Testing Ferdow's Model, International Journal of Operations & Production Management, 22(5): 492-514 Vilana Arto JR and Rodríguez Monroy C (2009) Let Others Manufacture! Towards a New Manufacturing Network, Intangible Capital, 5(4): 347-369

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Economic and Financial Profile of High-Growth Firms vs. Normal Firms from New Industry in the Basque Country: a Discriminant Analysis Ruiz de Arbulo P1, Landeta B2, Basañez A3, Insunza G4, Gonzalez X5 Abstract Gaining knowledge about the profile that defines high-growth firms and distinguishes them from the rest is the purpose of this research work, in addition to helping to understand their differences in relation to other normal firms in the Basque Country (CAPV). To this end, an economic and financial analysis has been carried out by comparing them with other normal firms and, by using a set of quantitative variables that have a priori been considered potentially explanatory, a predictive discriminant analysis has also been conducted.

Keywords: High-growth Firms, Discriminant Analysis, Economic and Financial Structure, New Industry

1 Patxi Ruiz de Arbulo (e-mail: [email protected]) Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 2 Benat Landeta Manzano Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 3

Aitor Basañez Llantada Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 4

Gaizka Insunza Araceta Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 5

Xabier Gonzalez Lasquibar Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. *This work derives from the participation by its authors in the research project set in motion by the University of the Basque Country (UPV/EHU) titled "Determining features and factors of high-growth innovation companies in the Basque Country" NUPV 11/08

76


1 Introduction Throughout recent years, in-depth studies have been carried out into company growth and, in this respect, those firms which are able to maintain markedly higher growth rates than the rest – and the fact that they do so over an extended period of time - prove to be of special interest. Moreover, they are large generators of employment (ARDÁN, 2004) and provide high returns for investors and shareholders, in addition to greater satisfaction and motivation for their workers (Henrekson and Johansson, 2008). The first work on the subject was already published in 1993 in the United States (Birch and Haggerty, 1993). In Spain España, Cabanelas and Vaamonde published their work in 1995 for the Vigo Duty-free Zone Consortium, in which they analysed the main features of young high-growth firms in Galicia. Other works on a national level have emerged since then (Cabanelas and Vaamonde, 1996; Amat et al., 2000, 2010, 2011a, 2011b; ARDÁN, 2004; Galve and Hernández, 2007), using different selection criteria regarding this type of firm. The interest shown in political, academic and business spheres of activity in learning about those distinctive parameters which, combined specifically, determine the success of such firms is, if possible, even greater in the times in which we are currently living (Peña et al., 2009). The aim of this research work is to characterise the type of high-growth firm from New Industry in the Autonomous Community of the Basque Country (CAPV), based on a comparative analysis with other firms belonging to the latter, taking into account investments, solvency, indebtedness, sales and profitability. It has been agreed to confine research to the inclusive period between the years 2006 and 2009 – the end of the last economic cycle and start of the recession in Spain. The results should thus be deemed to be of special interest, insofar as they refer to excellent firms which, despite the serious prolonged economic and financial crisis, have managed to adapt to the times and grow in terms of both size (number of employees and amount of assets) and sales.

2 Source of Data used and Empirical Evidence In the study, which is an eminently empirical one, the evolution of investment in high-growth firms has been analysed based on their total assets, non-current assets, stocks and debtors between the years 2006 and 2009, in order to compare their evolution with other firms from New Industry in the Basque Country. These include industrial manufacturing firms and those providing services to industry (firms as a whole that provide services) (Baró and Villafaña, 2009). The economic and financial profile of both groups has then been studied and, lastly, the econom-

77


ic and financial variables that have the most influence on the classifi-cation of high-growth firms or normal firms via discriminant analysis. On the other hand, as far as sources of information are concerned, a list of firms has been obtained using the SABI data base (Iberian Balance Sheet Analytical System) run by the company Informa, S.A., which contains the data deposited in company registers in Spain and Portugal. Thus, a register of 56,444 firms belonging to the CAPV has been used, of which 2,131 are SMEs in accordance with Recommendation 2003/361/CE issued by the European Commission (2003) and from what is referred to as New Industry. Among these enterprises, 81 firms considered to be high-growth have been detected in accordance with OECD guidelines (2007).

3 Results Obtained

3.1 Evolution of Investment Table 1 shows how the composition of assets in high-growth firms has evolved in relation to other firms. It is noted that high-growth firms evidence 35% growth of total assets in contrast to the behaviour evidenced by other firms (6% growth). As for the composition of non-current assets, both groups of firm evidence show similar percentages. In contrast, high-growth firms show lower levels of stocks than the rest, from which it may be deduced that their operative management is better. Table 1 Evolution of investment Mean assets

Non-current assets

Stocks

Normal

Highgrowth

Normal

HighHighNormal Normal growth growth

2006 10,761.49

8,850.75

46.40%

45.36% 7.50%

15.17% 36.00% 29.67%

2007 13,811.94

9,530.23

49.38%

43.75% 7.58%

15.44% 31.91% 29.96%

2008 14,584.48

9,973.14

40.71%

46.74% 9.16%

14.81% 29.85% 24.51%

2009 14.563.86

9,377.26

49.57%

49.72% 7.23%

13.71% 25.06% 21.71%

Year

(thousands of Euros) Highgrowth

35% 6% Source: put together by the authors

78

Debtors


3.2 Financial Profile of High-growth Firms In this section we analyse the financial profile of high-growth firms, taking into account their solvency, turnover and profitability. Table 2 shows the short-term solvency ratios of high-growth firms in relation to other firms, measured as the quotient between current assets and current liabilities. High-growth firms evidence ratios higher than 1, in no year reaching 1.5. Broadly speaking, this ratio is considered to be an optimum value. If one takes into more specific consideration the behaviour of manufacturing firms providing services to industry, it can be ascertained that the solvency ratio in the case of the latter is considerably higher – values between 1.40 and 1.70 inclusive. Normal firms evidence better solvency ratios over the years being analysed, although if one focuses on industrial firms, these evidence better solvency than high-growth firms, unlike the case of those providing services to industry, which evidence poorer solvency. Table 2 Solvency ratio Solvency = current assets/short-term debts

Solvency of manufactur- Solvency of firms providing firms ing services to industry

Year

High-growth

Normal

High-growth

Normal High-growth Normal

2006

1.25

1.33

1.19

1.39

1.40

1.06

2007

1.22

1.41

1.12

1.44

1.50

1.28

2008

1.33

1.38

1.15

1.44

1.74

1.18

1.09

1.51

1.41

1.37

2009 1.21 1.48 Source: put together by the authors

Table 3 shows the evolution of indebtedness. The high-growth firms evidence greatly restructured financing over the period 2006-09 (46% of shareholder equity in 2009). The same occurs with the other firms. Both groups of firm would appear to have had solid financial structures during the period in question, as they have steadily reduced their short-term debts over the years (79% in 2006 as opposed to 76% in 2009). This is a high value, albeit not one to cause enough concern in principle for firms to tend to increase their proportion of long-term debts, as there are no liquidity problems – as can be seen in the solvency table. Lastly, financial expenditure in terms of sales in high-growth firms is not high – around 1.9% - except in 2008 when it increased up to 2.5%.

79

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 Indebtedness ratios Indebtedness = total debts/assets

Quality of debt

Financial expenditure = fi= short-term debts/total debts nancial expenditure/sales

Year

Highgrowth

Normal

High-growth Normal

High-growth Normal

2006

54%

56%

79%

73%

1.57%

1.48%

2007

53%

55%

78%

72%

1.87%

1.84%

2008

54%

54%

82%

72%

2.54%

2.65%

2009 54% 51% 76% Source: put together by the authors

67%

1.88%

2.25%

Table 4 shows the maturity cycles and cash cycles of high-growth firms in relation to other firms. On the one hand, high-growth firms slightly increased their stock periods, while on the other they improved collection and payment periods, resulting in a more efficient maturity and cash cycle in 2009 than in 2006. In contrast, the other firms evidence a considerably poorer maturity and cash cycle in 2009 than in 2006, and poorer in comparison to high-growth firms. Table 5 shows an analysis of turnover. The high-growth firms invoiced 891 million Euros during 2009. 58.3% refers to manufacture and the rest to firms providing services to industry. Mean turnover was 11 million Euros, although it should be taken into account that the mean turnover of manufacturing firms was 1.24 times greater than that of those providing services to industry. Mean turnover of normal firms was 6.7 million Euros in 2009. Table 4 Solvency ratio and indebtedness ratios Stock period

Collection

(1)

period (2)

Payment period (3)

Maturity cycle

Cash cycle

(1) + (2)

(1) + (2) – (3)

HighHighHighHighHighNormal Normal Normal Normal Normal Year growth growth growth growth growth 2006 53

91

176

125

119

77

229

216

109

139

2007 52

100

149

123

114

81

201

223

87

142

2008 63

94

128

105

85

56

191

199

106

144

2009 62 126 123 114 Source: put together by the authors

94

69

185

240

90

170

80

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 5 Total and mean turnover 2009 turnover Year

2006-09 turnover (% 2009 mean variation) Thousands of Euros

(Millions of Euros) Highgrowth

%

Normal

%

Highgrowth

Normal

Highgrowth

Normal

Industry

519.8

58.3%

11,889.0

86.9%

109.2

84.3

12,088

6,829

Services to industry

371.3

41.7%

1,792.2

13.1%

187.3

95.8

9,771

5,800

100.0% 132.2

85.6

11,001

6,674

Total 891.1 100.0% 13,681.2 Source: put together by the authors

Most high-growth firms had a turnover of less than 10 million Euros (63 out of 81) and five of them had a turnover of more than 50 million Euros. This means that the mean turnover (€11,000.91) was considerably higher than the average turnover (€4,346.07). Table 6 shows an analysis of profitability. High-growth firms showed positive profitability rates throughout the period analysed, although it should be pointed out that there was a major drop in 2009 both in terms of profitability over assets and in profitability over shareholder equity. In any event, all periods under analysis evidence positive financial leverage, i.e. economic profitability was higher than the mean cost of debt. Table 6 Analysis of profitability Economic profitability

Profitability of shareholder equity

Financial leverage

Year

Highgrowth

Normal

Highgrowth

Normal

Highgrowth

Normal

2006

2.09%

4.38%

8.45%

7.48%

3.67

2.10

2007

4.93%

5.19%

24.53%

11.90%

4.93

2.56

2008

6.53%

4.30%

25.07%

7.36%

3.82

2.01

7.92%

2.44%

1.82

1.44

2009 4.72% 2.07% Source: put together by the authors

3.3 Discriminant Analysis The following part of the study involves ascertaining which economic and financial variables have the greatest influence on the classification of a firm as being either high-growth or normal. To do this, a discriminant analysis has been carried out using the SPSS statistical programme. 81 high-growth firms have been taken in the analysis and a sample of 166 firms in total from among normal firms has 81


been taken from New Industry, applying single random sampling. The first variables to be introduced have been those that would appear to enable the different types of firm to be better discriminated. The variables initially used have been as follows: seniority of the firm (in years), Napierian logarithm (ln) of corresponding value added for the year 2009, ln (sales 2009), ln (total assets 2009), financial profitability 2009, employment growth 2009-2008, ln (value added 2008), ln (sales 2008), ln (total assets 2008), financial profitability 2008 and employment growth 2008-2007. Table 7 shows summarises the results of the ANOVA analysis, which shows that all the variables chosen - except for financial profitability - have discriminant power (p – value < 0.05) and therefore must be introduced into the analysis. The financial profitability variable has been removed from subsequent analysis. Table 7 Tests for equality of group means Wilks’ lambda

F

gl1

gl2

Sig.

Seniority

.931

16.620

1

225

.000

Ln (value added 2009)

.897

25.903

1

225

.000

Ln (sales 2009)

.912

21.783

1

225

.000

Ln (assets 2009)

.959

9.626

1

225

.002

Financial profitability 2009

.999

0.285

1

225

.594

Employment growth 2009/08

.946

12.822

1

225

.000


.936

15.291

1

225

.000

Ln (sales 2008)

.946

12.897

1

225

.000

Ln (assets 2008)

.969

7.131

1

225

.008

Financial profitability 2008

.996

.898

1

225

.344


.778

64.300

1

225

.000

Below are shown the coefficients for the discriminant function (combination function of those variables that best discriminate between high-growth and normal firms). Table 8 Tests for equality of group means Group High-growth

Normal

Seniority

.098

.026


4.430

4.553

Ln (sales 2009)

.708

1.250

Ln (assets 2009)

-.145

.284


-.004

.014


3.861

4.028

82

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 8 (continued) Tests for equality of group means Group

Group

High-growth

High-growth

Ln (sales 2008)

3.245

3.350

Ln (assets 2008)

-2.719

-3.319


-.017

.010

(Constant)

-35.462

-41.963

Lastly, table 9 shows the results of the classification based on the discriminant function. In it can be seen the correct forecasts and errors obtained in the classification made using the discriminant function that has been calculated. Of the 153 normal firms, 149 have been forecasted in that group (97.4% of correct forecasts), whereas 30 of the high-growth firms have been erroneously classified as being normal (59.5% of correct forecasts). In total, classification has been correct in 149 + 44 = 193 cases, which represents 85.0% of the total and means that the discriminant power of the independent variables taken into consideration is very high. Table 9 Results of the classification*

Group

Count %

Forecasted group to which each firm belongs

Total

Normal

High-growth

Normal

149

4

153**

High-growth

30

44

74***

Normal

97.4

2.6

100.0

High-growth 40.5 59.5 100.0 *85.0% of originally-grouped cases classified correctly. **13 out of 166 firms excluded owing to loss of at least one discriminant variable. ***7 out of 81 firms excluded owing to loss of at least one discriminant variable.

4 Conclusions Research into high-growth firms is important because their performance is considered to be an indicator of business success. In this work we have tried to identify those variables that best define the economic and financial profile of high-growth firms in relation to other firms. Following a descriptive analysis in the course of which it has been ascertained that high-growth firms that obtain higher turnover and investment figures evidence a better cash cycle and higher profitability, a discriminant analysis has then been conducted in order to ascertain which economic and financial variables have the 83


most influence on the classification of high-growth or normal firms. It has been noted that the potentially explanatory quantitative variables are as follows: seniority of the firm, ln (value added year x), ln (sales x), ln (total assets x), employment growth (x – x-1), ln (value added x-1), ln (sales x-1), ln (total assets x-1) and employment growth (x-1 – x-2), with financial profitability being excluded.

5 References Amat O, Hernández JM, Fontrodona J, Fontana I. (2000) Las empresas gacela en Cataluña: un estudio centrado en el trienio 1995 – 1997. Economía Industrial. Nº 334, pp. 55-70. Amat O, Fontrodona J, Hernández JM, Stoyanova A (2010) Las empresas de alto crecimiento y las gacelas. Profit Editorial. Amat O (2011a) Empresas gacela: inductores del crecimiento y análisis de su evolución. Partida doble. Nº 233, pp. 64-73. Amat O, Campa F (2011b) Perfil económico-financiero de las empresas de alto crecimiento. Revista Internacional Legis de Contabilidad y Auditoría. Nº 47 pp. 137-160. ARDAN (2004) Claves del crecimiento empresarial. Las empresas gacela de Galicia. Del diagnóstico a la acción. Consorcio de la Zona Franca de Vigo. Baró E, Villafaña C (2009) La Nova indústria: el sector central de l’economia catalana. Papers d’economia industrial, 26. Generalitat de Catalunya. Departament d’Innovació, Universitats i Empresa. Birch D, Haggerty AY, Parsons W (1993) Who’s creating jobs?. Cognetics. Cabanelas JY, Vaamonde A (1996) Las empresas gacela de Euskadi. Informe SPRI. EUROSTAT, OCDE (2007) Manual on Business Demography Statistics. European Commission. European Commission (2003) Recommendation of 6 May 2003 concerning the definition of micro, small and medium-sized enterprises. Official Journal L 124, 20/05/2003 P. 0036 – 0041. Galve C, Hernández A (2007) Empresas gacela y empresas tortuga en Aragón. Fundación Economía Aragonesa, FUNDEAR. Documento de Trabajo nº37/07. Henrekson M, Johansson D (2009) Gazelles as job creators: a survey and interpretation of the evidence. Springer. Small Bus Econ. 35: 227–244. Peña I, González JL, Martiarena A, Navarro M, Heras I, Larraza M, Irastorza N (2009) Actividad emprendedora vasca de alto potencial de crecimiento (2000-2005). Instituto Vasco de Competitividad – Fundación Deusto.

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High-growth Firms: Qualitative Analysis Via Case Study Insunza Aranzeta G1, Basañez Llantada A2, Ruiz de Arbulo López P3, Landeta Manzano B4, González Laskibar X5 Abstract This work, which forms part of more extensive research into highgrowth firms in the Autonomous Community of the Basque Country during the period 2006-2009, attempts to analyse the reasons for high growth firms by four firms identified within it. This growth will be discussed from a qualitative standpoint based on extensive literature regarding high-growth firms and using the case study as the main methodology. Interviews with managers from these firms together with a partial analysis of the context within which they were found during the period analysed (sectorial analysis, general economic context, etc.) enable us to interpret the results obtained using the SABI (Sistema de Análisis de Balances Ibéricos) data base in a more dynamic and contextualised way.

Keywords: High Growth Firms, Gazelles, Case studies.

1 Gaizka Insunza Araceta ( e-mail: [email protected]) Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain.

2


Patxi Ruiz de Arbulo Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 4

Benat Landeta Manzano Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 5Xabier

Gonzalez Lasquibar Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain.

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1 Introduction Company growth both in terms of results or turnover and in terms of employment is a phenomenon that has aroused a great deal of interest among the firms themselves and among the scientific community and university. With a view to approaching this phenomenon within the sphere of activity of firms from the Autonomous Community of the Basque Country (CAPV), the authors of this work have carried out a research project titled Determining Factors and Features of Innovative High-growth Firms in the CAPV, one of whose parts is presented in this work. This type of analysis started to gain momentum when D. Birch tried to point to those factors that determined the survival and growth of firms by focusing on the ratio between their initial size, age and growth rate (Birch, 1981). One of his main contributions was his classification of firms according to age and their impact on employment. Studies about industrial dynamics have proliferated since then, providing quantitative and qualitative elements of the dynamics of the company population, i.e. their birth, mortality and capacity for survival and growth, and also their effect on economic performance and industrial structure. Numerous studies carried out in developed countries point to the fact that the typical profile of a high-growth firm corresponds to one which introduces product or process innovations with high growth potential, as it is geared towards large, non-local markets (Malizia et al., 1999; Moreno et al., 2000). Other studies maintain that highly-innovating environments characterised by a large number of company entries and exits are the ones which are most favourable to the setting-up of high-growth firms (Audrestch, 1995; Doms et al., 1995). Others point out that it is more common to find firms of this type in sectors based on knowledge and on some services with high aggregate value (Schreyer, 2000). Where consensus exists is in the fact that such firms are noteworthy for their high level of competitiveness in relation to other organisations and are often indicators of competitiveness in a given region or country (Segura, 1993). From a theoretical standpoint, we can state that high-growth firms experience major growth over short periods of time. Owing to the great scope of growth, we might consider this to be a radical change – a revolution in terms of organisational life. Such rapid growth may take place under different circumstances. In the case of firms that have been recently set up, the firm is immersed in a process that seeks a minimum size so as to favour its survival (Barkham et al., 1996). In the case of already-established firms, growth derives from changes in their strategy, the courses of action they take and behaviour, etc. (Moreno et al., 2000). These more radical types of change also make growth possible over and above normal levels.

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2 Objectives The main aim of the work is to analyse the process pursued by those firms that experienced high growth during the period 2006-2009 from a qualitative standpoint using case study methodology. In short, an attempt is made to ascertain the causes of such growth in each case so as to then try and establish, where possible, some type of pattern common to them. An attempt is also made to ascertain the main features of the growth process pursued by each of the firms subject to study, and to try and determine whether these processes fit into the theoretical models referred to previously.

3 Methodology Although case study is a methodology that is becoming increasingly accepted by the scientific community in general, it is also true to say that there were many who questioned its validity until a few years ago. Below we refer to the definition given by Yin in 1989 which, in short, reflects on the importance of context when analysing the phenomenon in studies: “Empirical research which researches a contemporary phenomenon within its real context, in which the limits between the phenomenon and context are not precisely shown and in many sources of evidence are used” (Yin, 1989). Among the most common criticism of this we find the following: obtaining of inconsistent and biased results (Arias, 2003), fairly nonobjective and unreliable methodology (Bonache, 1999) and problems associated with generalisation due to the limited number of cases studied (Bonache, 1999; Arias, 2003; Gummerson, 1991; Hamel et al., 1999). However, this methodology is useful when one wishes to try and understand a real phenomenon by taking all the variables that have a bearing on it into consideration (Mc Cutcheon et al., 1993). For this reason, it is becoming increasingly accepted within the area of company management, in which an understanding of decision-making processes, implementation and organisational change cannot be analysed in sufficient depth via the quantitative study of a large number of observations (Rialp, 1998). As far as the work itself is concerned, the first step was to identify those firms subject to study for which the following criteria were used: Industrial firms and firms providing services in the CAPV with 10 or more employees at the start of the period under scrutiny and which had experienced an increase in annual turnover over the aforementioned period of at least 20%. The list of firms was obtained using the SABI data base, in which 81 firms were identified using these criteria. Once the pool of firms subject to study had been identified, the data from the SABI data base was then analysed. This work was followed up by a questionnaire sent via email to each of them, in order to confirm some of the information that had already been obtained and to complete other information. 87


Lastly, interviews were arranged with some managers from 5 firms selected from among the 81 identified, so as to study them in greater depth and carry out a study of each of them. We should draw attention to the fact that one of the cases proved not to be valid, given that the growth experienced was the result of mergers and takeovers of several firms – something which is not reflected in the SABI data base. In view of the fact that no growth had existed in absolute terms either in employment or in turnover or results, this option was not taken into consideration for the project.

4 Results For reasons of confidentiality, as the firms themselves asked us to do, names are not mentioned, although we do include some of their main features in Table 1 below. To complete this very brief description of the firms selected, we shall only comment on their shareholding and age. As far as their shareholding is concerned, mention should be made of the fact that diversity exists despite only 4 cases having been studied: firm A belongs to a larger corporation, firm D is a family business and firms B and C are the fruits of an initiative on the part of their managers and owners. According to their age, it should only be pointed out that except for firm D, which was set up in the 1970s, the other three have been in existence for around 10 years. However, it is fair to say that firm A belongs to a group with a longer tradition and therefore to a certain extent should not be considered as being such a young company. We might therefore draw a distinction between two groups of firm: the first could comprise the two that have been recently set up and the other could be made up of the two firms that have been established for longer. As we shall see below, this is reflected to a certain extent in the growth process experienced by each of them. Table 1 Firms selected for the case study Firm

Sector

Number of employees at the end of the period

A

Aeronautical Engineering

650

B

Computer Engineering

320

C

Biotechnology

75

D

Machinery repairs in transport and construction

62

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4.1 The Causes of Growth Although there are certain similarities in some aspects, it is true to say that the reasons for the success of these 4 firms over the period analysed can be considered different. Nonetheless, attention should be drawn to the fact that the influence of the economic situation in general or that of the sector in particular is a very important and common feature in the case of firms A, B and D, and therefore not so in the case of C. The case of aeronautical engineering can be summarised by the well-known phrase of making a virtue of necessity – in more business-like terms, we might say that they were able to transform the threat into opportunity. According to the firm’s own general manager, it had no alternative other than to grow if it wanted to avoid going under. As the work load of the group to which they belong declined, so did the orders that this provided to them. The only possible solution was to obtain orders from outside the comfort zone of the group itself and target the major international aircraft and helicopter manufacturers – which they managed to do. This case fits into the pattern of major growth associated with a strategic decision. The firm in question and its activity were already fully established prior to the period subject to study, although the decision to risk taking on new projects was the one that preceded the major growth experienced over the period 20062009. For its part, the growth of computer engineering was caused by the favourable economic situation at the time, as its main customers were none other than different public administrative bodies and major institutional clients such as universities, etc., whose investment budgets were genuinely significant during the period subject to study. Although this period includes the years 2008 and 2009, the truth of the matter is that the crisis had hardly got underway in the CAPV by then, to which should be added the fact that investment projects were awarded many months beforehand in some cases. This firm came into being a few years prior to the period under study, meaning we can associate its growth with its search for the optimum size that would enable it to carry out its activity efficiently. The case of firm D, whose customers belong to the world of construction, is easy to understand. This is a sector which, as is well-known, maintained extraordinarily high growth rates during the past decade. However, the case of firm C is different and can be considered a typical case of a high-tech company in its first few years of operation. At the beginning it received different public aid destined for the setting-up and development of innovating firms and its shareholding included a range of venture capital businesses. This is therefore a firm in whose DNA is engrained the will to grow so as to sufficiently remunerate the risk taken on by those investors who decided to place their trust in the project.

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4.2 Growth Strategies It would seem logical to assume that different causes gave rise to different growth strategies, although once again some similarities can be made out among the different cases. Growth took place in firms A and B mainly via the expansion of their respective markets. This expansion was achieved by winning new customers for those products and services they already offered rather than as a result of any variation in the latter. However, there is a huge difference between these two cases. Computer engineering, whose market chiefly comprised major institutional clients from the CAPV, expanded its business to this same type of customer, but from neighbouring autonomous communities such as Santander and Aragon, etc. and the main cities in Spain such as Madrid and Barcelona. For its part, aeronautical engineering channelled its efforts into internationalisation in order to meet the requirements of the main aeronautical constructors, moving to countries such as Brazil and the USA. Indeed and as its managers commented to us, maintaining a presence in the countries of origin of these manufacturers is almost mandatory. It should be taken into account that we are talking of a small number of customers with projects that cover large amounts in which trust is essential to even get the chance to supply. Added to this is the fact that in some cases manufacturers include public shareholding, and terms and conditions governing contracts involve contracting firms established in the countries concerned. However, attention should be drawn to the fact that the leap forward was to a certain extent the fruits of a specific event, as the firm was given the chance to take part in a technically very complex project in which the other competing firms had already failed. Thanks to the attitude of managers who were able to take on the risk and face up to the challenge, the project successfully took off to the extent that the firm managed to get right to the core of all the manufacturers. Yet we cannot attribute high growth to the fruits of a specific event – that would be underestimating the renewed strategy that was pursued despite the high risk involved. For its part, firm C attributes its growth to the continuous supply of new products with extremely high value added. To achieve this, it set aside a large proportion of its human and financial resources to research, without overlooking collaboration with other national and international agents. However, as in the case of firm A, internationalisation has without doubt been a key factor in understanding its success, even in setting up subsidiaries in Mexico and the United States. In the words of one its managers: “Specialisation and diversification of products has been one of the keys alongside R&D – this has enabled us to enter new markets and force international expansion, reducing the level of risk of dependency on a single product or single market.”

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Firm D represents a different case to the rest as, via a specific agreement entered into with a major international lorry manufacturer, it became an Official Repairs and Sale of Spare Parts Service Department for lorries made by the firm in question in the province of Bizkaia, and also providing the same service to neighbouring provinces. This provided them with a large volume of work, the fruits of which brought growth and, even more importantly, if possible, affected the way of doing things. Representing a well-known international trademark compelled them to meet all the demands imposed on them by their partner in many aspects and, in short, to maintain certain standards of high quality.

4.3 Human Resources These are firms from a variety of sectors, albeit with one feature in common – that they are sectors in which the job factor has a predominant weight in cost structure. Obviously, technology is an essential medium, although this does not prevent the need to have a large number of employees at one’s disposal to the extent that, as we were told by several firms, 80% of the cost goes on manpower hours worked. To this must be added staff skills which, except in the case of vehicle repairs, are very high and specialised. The four firms coincided in the importance of proper management of human resources in order to be able to meet customer demands in terms of quality, reliability and deadlines, etc. Obtaining skilled labour in sufficient amounts became one of the main problems associated with growth, together with difficulties related to the type of organisation and restructuring required.

4.4 Innovation Innovation is without doubt the basic factor in the biotechnology firm and also plays a major role in aeronautical engineering. In the other cases, although they maintain that this is an aspect to be developed for the future, it would not seem to have been a key factor in their growth. In the case of firm B, its managers admit that it was only when things had stagnated that the need was understood to innovate in all aspects, and the fruits of this can be seen in the fact that a spin off has recently been created from the company that provides IT services of a highly innovative nature, with which they have entered into a major commercial agreement and in which they have a shareholding.

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5 Conclusions The first conclusion of a methodological type to be drawn is that the data base may prove misleading as it does not reflect the reality of the situation in many cases, meaning that research needs to be continued. Without doubt, 4 cases are too few to draw far-ranging conclusions regarding the entire family of high-growth firms. Nonetheless, if some conclusions can be drawn from this work, they are the following: The importance of individuals in these types of firm: on the one hand, the 4 firms subject to study have proved to be very labour-intensive and, on the other, mention should be made of the fact that the problems deriving from their management are the ones that most affect the firm and that finding specialist, skilled labour in sufficient amounts is their greatest concern. Working proactively by developing strategies that facilitate this is essential if major growth rates are to be obtained. Growth would often seem to be the consequence of a specific or even casual event, although we might dare to suggest that this is not really the case. When a firm decides to devise a strategy aimed at attaining growth, a specific situation often tends to arise from this via which the firm starts to take off. Lastly, something obvious should be pointed out when referring to business growth – the socio-economic context in general and sectorial context in particular. It is no less true to say that there are firms that manage to grow in fairly unfavourable situations which would be worth studying in the future.

6 References Arias M. (2003) Metodologías de investigación emergentes en economía de la empresa, Papers Proceedings 2003, XVII congreso nacional XIII congreso hispano-francés AEDEM, Université Montesquieu Bordeaux IV, Bordeaux, pp.19-28. Audretsch D. (1995): “Innovation, growth and survival”. International Journal of Industrial Organization , 13 (4): 441-457. Barkham R., Gudgin G., Hart M. (1996): The determinants of small Firm Growth: An InterRegional Study in the United Kingdom 1986-90, London, UK. Birch D. (1981). Who Creates the Jobs? The Public Interest, 65, pp. 3-14 Bonache J. (1999) El estudio de casos como estrategia de construcción teórica: características, críticas y defensas”, Cuadernos de Economía y Dirección de la Empresa, nº 3 pp. 123-140. Doms M., Dunne T., Roberts M.J. (1995): The role of technology use in the survival and growth of manufacturing plants. International Journal of Industrial Organization, vol. 13, No 4. Gummesson E. (1991) Qualitative Methods in Management Research. Sage Publications, Newbury Park, California. Hamel G. and Prahald C.K. (1993) Strategy as Street and Leverage. Harvard Business Review, marzo-abril, pp. 75-84. Malizia E. and Winders R. (1999): The prospects of High-growth enterprises: A retrospective analysis of Georgia-based firms TVA Rural Studies Programme contractor paper 99-6.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Mc Cutcheon D. and Meredith J.R. (1993) Conducting case study research in operations management. Journal of Operations Management, Vol. 11, pp. 239-256. Moreno A. y Casillas J. (2000): High-growth enterprises (Gazelles): A conceptual framework. Departamento de Administración y Marketing, Facultad de CCEE, Universidad de Sevilla. Rialp A. (1998) El método del caso como técnica de investigación y su aplicación al estudio de la función directiva. IV Taller de Metodología ACEDE, 23-25 de abril, Arnedillo, La Rioja. Schreyer P. (2000). High-growth firms and employment, OECD Science, Technology and Industry Working Papers, 2000/3. Segura J. (1993): Sobre políticas macroeconómicas de competitividad. Papeles de Economía española, N. 56, pp. 348-360. Yin R.K. (1989): Case Study Research. Design and Methods, Applied Social Research Methods Series, Vol. 5, Sage Publications, London.

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Analysis and Characterisation of the Highgrowth Firm in the Basque Country Gonzalez X1 , Ruiz de Arbulo P2, Landeta B3, Basañez A4, Insunza G5 Abstract This work identifies those features that make the high-growth firm in the Basque Country (CAPV) stand out above the others, with a view to creating a profile or map of the best practices pursued by this type of firm. The results obtained from our study provide us with data that enable us to classify the following types of firm: young high-growth firm, small or medium size, job creator or not very innovating.

Key words: High-growth Firm, New Industry, Innovation, Employment.

1 Xabier Gonzalez Lasquibar ( e-mail: [email protected] ) Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 2

Patxi Ruiz de Arbulo Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 3 Benat Landeta Manzano Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 4


Gaizka Insunza Araceta Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. * This work derives from the participation by its authors in the research project set in motion by the University of the Basque Country (UPV/EHU) titled "Determining features and factors of high-growth innovation companies in the Basque Country" NUPV 11/08

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1 Introduction Firms tend to be viewed as main players in the economic development of society, perhaps even more so in times of economic repression and depression. The growth of the firm has been studied in depth over the past few years, and continues to be studied now in these times of quite a major economic crisis when the issue takes on even more importance among stakeholders (Freeman, 1994) from the business community – i.e. political leaders, academic agents, strategic consultants and investment and entrepreneurial companies, among others (Peña et al., 2009). This research proposal attempts to pinpoint the features and factors that distinguish more dynamic firms from the rest from the standpoint of New Industry in the Basque Country (CAPV) - i.e. industry comprising manufacturing firms and those providing services to industry – and that determine their competitive advantage. From this the aim is to draw conclusions that may enable references to be provided about their strategies and thus help to improve the competitiveness of the Basque industrial firm and, ultimately, of the Basque economy.

2 Conceptual Framework The number of works that focus on company growth has increased in recent years. Among firms that are growing, those that grow rapidly and continually have taken on a special importance: namely, high-growth firms. The study of high-growth firms is of vital importance as, according to many authors (Birch, 1981 y 1987; Storey, 1994; Henkerson and Johansson, 2010; Amat, O. et al., 2010) they promote the economic development of a region or country and are a powerful source of employment. They are characterised by the fact they are very dynamic and are indicators of competitiveness in a given region or country. The notion of high-growth firm has been evolving since the time in the 1980s when D. Birch (1981) developed pioneering research in which he attempted to identify the determining factors of company survival and growth. In his work titled “Who creates jobs?” D. Birch referred to the importance of new firms in job creation. Using longitudinal data bases to study the birth, demise and growth of firms of different sizes and age, he came to the conclusion that “of all jobs created between 1969 and 1976, two thirds were created by firms with less than 20 employees” and that “80% of new jobs were created by firms that were 4 years old or less” (Birch, 1981: 7-8). Another significant contribution from Birch was his classifications of firms according to age and their impact on employment, via which he refers to gazelles. According to Birch, the latter are responsible for most employment in the different 95


regions (Acs and Mueller, 2006). “The term gazelle is used in business jargon to refer to firms which grow exceptionally fast” (Amat, et. al., 2000: 18). Another work of note about gazelles, also by Birch, is the report published by Cognetics in 1994. This firm used the terminology proposed by Birch in considering gazelles to be those that double their turnover over a 4-year period. In the work, attention is drawn to the importance of gazelles in job creation (they are responsible for 70% of employment growth in the United States) and their involvement in innovation processes as a source of improvement and the volatility of their profits (Galve and Hernández, 2007: 11). Since then there have been numerous works that attempt to analyse the features of gazelles both on a national level (Amat et.al., 2000, 2010; Cabanelas and Vaamomde, 1996; Cabanelas, 2004; Checa, 2000; Galve and Hernández, 2007; Amat, et. al., 2000) and an international level (Malizia and Winders, 1999; Schreyer, 2000, etc.). Despite the fact that the conceptualization of gazelles coincides in all works on the subject, the selection criteria vary from one to the other, making it difficult to carry out comparative analyses of the results obtained. Nonetheless, consensus exists as to certain aspects of gazelles as follows: They are young firms that are experiencing major growth rates in terms of income and turnover over short periods of time. They are the main source of net job creation. They are noteworthy for the fact that they assume greater risks than the other firms studied, increasing their size using internal growth as a strategy. They make major investment in fixed assets in order to meet demand for their products, financed via short and medium-term debt and stockholder equity. They obtain higher levels of economic and financial profitability than those of other companies, having less financial and staff expenditure in terms of income (Galve and Hernández, 2007: 14). According to Amat et al (2000), one of the most important aspects of gazelles is their great capacity to be self-sustaining, i.e. gazelles do not grow as a result of capital contribution by partners (Galve and Hernández, 2007: 15-16).

2.1 Problems when Defining High-growth Firms and Gazelles One of the main problems noted in the works analysed about high-growth firms is the selection of the variable that determines whether the company being analysed is a high-growth firm or a gazelle. While some use inputs such as number of employees and their variation to explain growth, others prefer to measure this via the evolution of assets or by measuring outputs from the firm including variables such as sales or profits (Basañez et. al., 2012). Some establish a minimum number of employees attained by a certain time in the firm’s lifespan (Malizia and Winders, 1999; Schreyer, 2000). Definitions also exist that use sales growth (Eckhardt and 96


Shane, 2006) and level of profit or earnings (Amat, et al., 2000) while, lastly, others combine sales growth with employment (Delmar and Davidsson, 1998) or with growth in wages (Badger and Schott, 2002). The choice of variable via which growth is measured and the conditions established for the purpose of considering whether a firm is high growth are of vital importance, as they will determine the results obtained from the study. Such a relationship may depend on the information available, the socio-economic context or the objectives themselves set out by the study. The most recent contributions with regard to the definition of high-growth firms and gazelles have been led by Eurostat and the OECD (2008), and the main aim has been to homogenize selection criteria on an international level. These contributions establish a clear difference between concepts of high-growth firms and gazelles that have indiscriminately been used in recent years. In this study we have turned to the definition of high-growth firm provided by Eurostat and the OECD. We consider this definition to be both rational and appropriate, as it highlights the importance of a unified criterion in order to be able to compare different works.

2.2 Objectives Starting with a new concept of industry which embraces activities involving the provision of services to manufacturing firms and given the close technological and economic inter-dependence between both, an attempt is made to obtain some references on which management and entrepreneurs from the Basque business fabric might base themselves when designing their competitive strategies. To this end, the core objective of this work is to describe the features and factors that determine the success of firms classified as being high growth in the Basque Country (CAPV). Another of the objectives that emerge from the main objective is also to try and create a profile of good practices pursued by these types of firm in order for this to serve as an example for stakeholders within the business community, and as a guide in strategic decision-making.

2.3 Methodology The firms classified as being high growth have been identified by using the Iberian balance sheet analytical system (SABI) and based on the definition provided by Eurostat and the OECD (2008). These last-mentioned two transnational organisations define the high-growth firm as “that which experiences job or turnover 97


growth rates of at least 20% a year over a period of three consecutive years and has at least ten employees.” They also define a gazelle as “a high/growth firm that has not been in existence for more than five years.” This is the definition adopted for the purpose of this work. In this study we have turned to the last-mentioned definition, as we consider it important for there to be a unified criterion to be able to compare different works. As regards the variable chosen to measure growth, we have decided to opt for the number of workers, as we consider this variable to be more explanatory than sales or profit level within the context of crisis. 81 high-growth firms have been adopted using this first selection, and these make up the sample for our study. In the first phase, a descriptive study will be carried out of the features of such firms, ascertaining their size, age, number of jobs, activity, turnover and geographic location. Secondly, a qualitative study based on a structured questionnaire will be carried out in order to identify key growth factors. By way of a stage prior to the conducting of interviews, each of the firms selected was contacted so as to explain to them the scope and objectives of the diagnosis and to ensure that they take part in the research project. Once the process involving the compiling and review of data has been completed, the computerised processing of this data will then be carried out in order to enable the information to be treated and for the data to be contrasted with that contained in the literature reviewed.

3 Results obtained 3.1 Characterisation As regards the description of the general and demographic features of the firms selected, we have based out study on the data obtained from SABI.  The 81 high-growth firms represent 3.8% of industrial firms and those providing services to production in the Autonomous Community of the Basque Country (CAPV).  47% provide services to production and 53% to industry.  As for seniority, over 30% have been in existence for up to five years, in contrast to data from studies carried out along the same lines (Evans, 1987; Dunee and Hughes, 1994; Amat et. al., 2010), which state that young firms are the ones that grow the fastest.  The firms selected had a turnover of 891 million Euros during the year 2009. 58.3% are industrial firms and the rest are firms that provide services to pro98


duction. The fact should be taken into account that the average turnover of production firms is 1.24 times greater than that in firms that provide services to industry, with the firms that make up our sample experiencing growth in turnover of 132.32% over the period analysed.  The data shows that 58% of firms have less than 50 workers (small enterprises) and the rest (42%) employ between 51 and 213 workers (medium-sized enterprises). This finding is in line with observations made by Birch (1994) and Cabanelas (2004), that high-growth firms are noteworthy for their contribution to job creation. The firms analysed employed an average 62.9 workers in the year 2009. The number of jobs increased 2.21-fold over the period 2006-2009, rising from 28.5 to 62.9.  As regards the geographic location of the firms studied, 64.2% maintain their head offices in the historic territory of Vizcaya, 23.5% in Guipuzcoa and the rest (12.3%) in Alava.

3.2 Determining Factors The qualitative study carried out indicates that the 81 firms selected give priority to proper company management, development of innovation, total quality assurance and appropriate management of human resources as competitive factors. As far as environmental factors that either positively or negatively affect the firm’s competitiveness, from the data we conclude that those factors that hinder competitiveness are as follows: competition, relocation of production, governmental legislation and the economic situation. According to the authors of this study, the last-mentioned factor selected as an obstacle to competitiveness (economic crisis) may be due to the current situation (2012). In contrast, environmental factors that favour a firm’s competitiveness are as follows: a diversified customer portfolio, a good network of distributors at their disposal and a good pool of suppliers. From among the six strategic decisions that needed to be chosen, differentiation of product or service stood out over the rest. Likewise, attention should be drawn to the importance given by firms to leadership in terms of costs, expansion policies and the diversification of products and markets. As for investments, approximately half of the firms interviewed resorted mainly to self-financing (8 firms). The other half relied mainly on external funds (7 firms). The main customers of the firms interviewed are industrial firms and those providing services, followed by public administrative bodies. Most of the firms interviewed concentrate the bulk of their sales on three main suppliers (7 firms between 41%-60%, 3 firms between 61%-80%, 4 firms between 81%-100%).

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The most common commercial strategy among the firms interviewed has been to establish a new positioning for the product or service on the market (9 firms). Seven firms in turn highlight modification of design or presentation of the product. The firms analysed state that their operative market is concentrated on a regional/autonomous level (36%), closely followed by the national market (30%), with the provincial and European Union markets being the least used. 84% of firms point out that their sales depend on 25% exports, with the European Union being the most exploited area followed by the United States. If we scrutinize the imports of these firms, we can see that 58% of firms make 25% of their purchases on a regional/autonomous level, while 21% of firms state that 26%-50% of their purchases derive from local suppliers, and attention should be drawn to the fact that 11% make all their purchases from local suppliers. Most firms introduced some work organisation method for the first time during the period subject to study, with work team management being the most widespread among 60% of the firms interviewed. This is followed by the introduction of new responsibility-sharing systems (50%), department restructuring (45%) and the introduction of a rotation system (15%). A noteworthy point is that only 10 of the firms interviewed have established a proper R&D department, while 8 of them say they do not have one. However, only 6 firms say they have no workers who exclusively focus on these tasks. It has been demonstrated that firms employ more than 10 workers devoted exclusively to R&D in sectors in which this type of work is practically an obligation (biotechnology, aeronautics and electronics). 90% of the firms interviewed invest less than 10% of their turnover in R&D. Only 2 firms confirm that they spend over 10%. Logically, these are two of the firms that belong to the aforementioned sectors (specifically, biotechnology and aeronautics). As regards the result of research efforts, of the 18 firms interviewed only 4 obtained their own patents over the period under consideration, with only 2 having obtained international patents. The fact that a third of the firms interviewed have not obtained any type of public funding for their R&D activities should be deemed cause for concern.

4 Conclusions Results obtained from previous works that describe the profile of the high-growth firm have been referred to throughout this work. We have come to the conclusion over the course of our study that the highgrowth firms analysed in the Autonomous Community of the Basque Country tend

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to share a major influence on job creation, be fairly young and small or mediumsized (SMES) and, surprisingly, do not feature prominently in the area of R&D. The results provided in our work thus confirm the predetermined profile of the high-growth firm with which we were familiar.

5 References Acs, Z.; Mueller, P. (2006). Employment effects of business dynamics: Mice, Gazelles and Elephants. Max Planck Institute of Economics Discussion Paper 23. Amat, O. et al., (2000): Las empresas gacela en Cataluña: un estudio centrado en el trienio 1995 – 1997. Economía Industrial. núm. 334, pp. 55-70. Amat, O. et. al., (2010). Las empresas de alto crecimiento y las gacelas. Profit Editorial. Badger, T.y Schøtt, T. (2002). Growth of young firms. Determinants revealed by analysis of registries in Denmark. Paper prepared to the LOK Research Conference. Basañez Llantada, A et al., (2012). Las empresas de alto crecimiento. Un análisis de los principales trabajos en España. CIO.Vigo. Birch, D. (1981). Who Creates the Jobs? The Public Interest. Núm. 65, pp. 3-14. Birch, D. (1987). Job Creation in America. New York. NY: The Free Press. Birch, D. Haggerty, A. and Parsons, W. (1994). Corporate Almagnac, Cognetics Mimeo. Cabanelas J (2004). Claves del crecimiento empresarial. Las empresas gacela de Galicia. Del diagnóstico a la acción. ARDÁN, Consorcio de la Zona Franca de Vigo. Cabanelas, J. y Vaamonde, A. (1996). Las empresas Gacela de Euskadi. Informe, SPRI, Euskadi Checa, A. (2000). Aproximación al fenómeno de las empresas gacela en Andalucía. Boletín económico de Andalucía. Núm. 28-29. Delmar, F., Davidsson, P., 1998. A taxonomy of high-growth firms. In: Reyonlds, P.D., Bygrave, W.B., Carter, N.M., Manigart, S., Mason, C.M., Meyer, G.D., Shaver, K.G. (Eds.), Frontiers of Entrepreneurship Research. Wellesley, MA7 Babson College, pp. 399 – 413 Dunne, P. y Hughes, A.A. (1994). Age, size, Growth and Survival: UK Companies in the 80s. The Journal of Industrial Economics. Vol. 62, núm. 2, pp.115-140. Eckhardt, J.; Shane, S. (2006). Innovation and small firms performance: Examing the relationship between technological Innovation and the within –industry distributions of fast growth firms. SBA Small Business Research Summary. Núm. 272. Evans, D.S. (1987).The Relationship Between Firm Growth, Size and Age: estimates for 100 Manufacturing Industries. The Journal of Industrial Economics. Vol. 35, núm. 4, pp. 567-581. Freeman, R.E. (1994). The politics the stakeholder theory: some future directions. Business ethics Quarterly. Vol. 4, núm. 4, pp. 409-421. Galve, C. y Hernández, A. (2007). Empresas gacela y empresas tortuga en Aragón. Fundación Economía Aragonesa, FUNDEAR. Documento de Trabajo núm. 37. Henrekson, M. y Johansson, D. (2010). Gazelles as job creators: a survey and interpretation of the evidence. Springer. Small Bus Economics. 35: 227–244. Malizia, E.; Winders, R. (1999). The prospects of High-growth enterprises: A retrospective analysis of Georgia-based firms TVA Rural Studies Programm contractor paper 99-6. Peña, I et al., (2009). “Actividad emprendedora vasca de alto potencial de crecimiento (20002005)”. Instituto Vasco de Competitividad – Fundación Deusto. Schreyer, P. 2000. High-growth Firms and Employment. STI Working Paper 2000/2, Paris: OECD. Storey, D. (1994): Understanding the Small Business Sector, London: Routledge.

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The Delphi Method Applied for Validates the Regional Innovation Model. Case Study Applied in Central Region Romania. Moica S1, Ganzarain J2 Abstract This paper takes as its starting point the model of innovation system that was designed to build communication networks between the various factors involved in the innovation process in Central Region Romania. The framework presents the Delphi method and was chosen based on the principle that forecasts from a structured group of individuals are more accurate than those from unstructured groups. (Rowe and Wright, 2001). This has been indicated with the term "collective intelligence"(Hiltz, Turoff, 1978). This study was realized in order to validate the innovation model and the results revealed a triple imperative: it is necessary to implement immediate actions that need support through a national strategy. Also are welcomes the partnership, structured around three main areas: companies universities and research institutes; makers - experts in technological innovation; government - strategic external partners.

Keywords: Innovation, Delphi Method, Region, Model

1 Introduction The technological innovation model defined for the Central Region Romania requires the validation of innovation experts in order to start the implementation approach. This is the reason why was chosen this interactive method called Delphi with the objective of getting previsions from a group of experts in charge. These 1Sorina

Moica ( e-mail: [email protected]) Petru Maior University of Târgu Mures, Str. Nicolae Iorga, nr.1, Târgu Mures, 540088, România. 2Jaione

Ganzarain ( e-mail: [email protected]) Departamento de Mecánica y Producción Industrial, Goi Eskola Politeknikoa - Mondragon Unibertsitatea, Loramendi 4 Aptdo. 23 - 20500 MONDRAGON

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experts are answering to a set of questionnaires and are anonymous to each other and independent of each other. This method provides more accurate results than those offered by unstructured groups or even to quantitative methods. According to the "European Innovation Scoreboard, the Central Region of Romania is positioned well below the European average, while in Spain, Bask Country Region is located near the European average, in general terms of innovation, and on the leaders in Europe we find Finland. Given these positions, we determinate a model of technological innovation for Romania, which is based on the analysis of different regional innovation systems in Finland and Spain (Moica, 2012). Given these positions, the paper has defined the objective of validating a model of innovation proposed for Central Region Romania.

2 Regional Innovation Model It is common today to look at science and technology as a research or innovation model. This model is said to be composed of four main elements or sectors – universities, governments, industry and non-profit – and their interrelationships. The concepts of the Triple Helix and Regional Innovation Model have become popular frameworks in the literature for discussing such a system approach. Where did the frameworks come from? C. Freeman and B.-A. Lundvall, as prolific writers on National Innovation System, have suggested that F. List (Das Nationale System des Politischen Okonomie, 1841) was a pioneer of the approach. However, one would have difficulty documenting a tradition of theoretical research on the model approach arising out of List’s work. In a recent paper, Godin has documented what the model approach in science studies owes to national policy and the discussions conducted on this matter in industrialized countries beginning in the early 1960s. Over the same period, the model approach found its way into official statistics, which helped solidify the concept (Godin, 2009). However, we can go further back in time. And here national science policy is really at the heart of the matter again. The experience of World War I led to mobilization of the totality of scientific resources on a nationwide basis, what the American historian A. H. Dupree called the “great estates” of science in the country (Dupree, 1957), and to the demand to link universities with industry. In Great Britain, this started with efforts by the Board of Education (1915) to strengthen and redirect educational resources toward industry’s needs. The belief in shortages of research scientists, particularly scientists with expertise in both pure and applied science, and specifically industrial scientists, gave rise to the Department of Scientific and Industrial Research.

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3 Research Methodologies Delphi, in contrast to other data gathering and analysis method, employs multiple iterations created to develop a consensus of opinion concerning a specific topic. Iterations refer to the feedback process. The process was viewed as a series of rounds; in each round every participant worked through a questionnaire which was returned to the researcher who collected, edited, and returned to every participant a statement of the position of the whole group and the participant’s own position. A summation of comments made each participant aware of the range of opinions and the reasons underlying those opinions, indicates Ludwig (1994). Specifically, the feedback process encourages the selected Delphi participants to reassess their initial judgments about the information provided in previous questioner. In the original Delphi process, the key elements were (1) structuring of information flow, (2) feedback to the participants, and (3) anonymity for the participants. The interactions among panel members are controlled by a monitor who filters out information that is not related to the purpose of the group. The usual problems of group dynamics are thus completely bypassed. In this way Fowles (1978) describes the following ten steps for the Delphi method: Formation of a team to undertake and monitor a Delphi on a given subject. Selection of one or more panels to participate in the exercise. Customarily, the panelists are experts in the area to be investigated. Development of the first round Delphi questionnaire. Testing the questionnaire for proper wording (e.g., ambiguities, vagueness) Transmission of the first questionnaires to the panelists. Analysis of the first round responses. Preparation of the second round questionnaires (and possible testing). Transmission of the second round questionnaires to the panelists. Analysis of the second round responses (Steps 7 to 9 are reiterated as long as desired or necessary to achieve stability in the results.) Preparation of a report by the analysis team to present the conclusions of the exercise.

4 Innovation Model and its validation The model of innovation propose a collaboration that would be an enabling body—promoting the learning and practice of enterprise and the exploitation of our intellectual property and that the aim was to create an nationally renowned centre of excellence, to study and understand enterprise and to stimulate entrepreneurial activity so that the region will be known throughout the world as a centre 104


for technology transfer at the forefront of knowledge. The centre’s first business plan called for it to establish entrepreneurship education politics for students and academic entrepreneurs, professional training programmer for aspiring entrepreneurs in the area business community, and a scholarly research agenda around enterprise. The model consists of the following components: People are central to the model, as the engine of the whole system; Basic processes of innovation are composed of three elements: – Assimilation and application of knowledge, – Dissemination and knowledge transfer; – Generation of knowledge; The support of the innovation process, which facilitates and promotes innovation process, consisting of direct agents and agents such as companies and government support by the Structural Funds; Universities, companies and government agencies are the main generators of the innovation process, enabling them to generate knowledge chain movement; The interaction between universities, companies and government agencies may be technical, commercial, social, financial and legal; Economic and social results are the output of the innovation system they eventually leading to economic and social grow; Regional networks, national and international link with other innovative regions in Romania, and the global innovation system.

Fig. 1 The "Perpetuum symbiotic" model of innovation proposed for Central Region

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The name of the model symbolizes the continuous movement of the innovation system (perpetual) of the elements; they depend and interact with each other in a perfect symbiosis. It seeks the change of the solid boundaries and organizations are public and private companies, University and government agencies in a semi-permeable membrane, allowing easy movement between the innovation environment and internal processes Developed Research and Innovation. (Moica , 2012)

4.1 Delphi Method Implementation We use the Delphi process as data collection method applying two iterations. Theoretically, the Delphi process can be continuously iterated until consensus is determined to have been achieved. Individuals are considered eligible to be invited to participate in a Delphi study if they have somewhat related backgrounds and experiences concerning the target issue, are capable of contributing helpful inputs, and are willing to revise their initial or previous judgments for the purpose of reaching or attaining consensus (Pill, 1971; Oh, 1974). Our groups of people that were well qualified to be subjects of a Delphi study are divided in three categories: Top management decision makers from the Central Region Romania; The professional staff members from Regional Agencies Teacher from the study field The questionnaire was applied to each person interviewed face-to-face or by mail a total of 24 subjects was answering. To centralize the answers was compiled a database in Excel, and then was made the synthesis of the information. Questions posed were used to predict and define innovation model and in total was 16 for the first round. Conducting a Delphi study can be time-consuming. Specifically, when the instrument of a Delphi study consists of a large number of statements, subjects will need to dedicate large blocks of time to complete the questionnaires. For the first round the allocated average of time use to answer to the question was 15 minutes. Regarding data analysis, decision rules must be established to assemble and organize the judgments and insights provided by Delphi subjects. However, the kind and type of criteria to use to both define and determine consensus in a Delphi study is subject to interpretation. In the Delphi process that we apply, data analysis can involve both qualitative and quantitative data. Investigators need to deal with qualitative data which use open-ended questions to solicit subjects’ opinions, are conducted in the initial iteration. Subsequent iterations are to identify and hopefully achieve the desired level 106


of consensus as well as any changes of judgments among panelists. The major statistics used in Delphi studies are measures of central tendency (means, median, and mode) and level of dispersion (standard deviation and inter-quartile range) in order to present information concerning the collective judgments of respondents (Hasson, Keeney, McKenna, 2000).

5 Results In the study conducted to validate innovation model for the Central Region of Romania, a prospective study on the general issue of the innovation system. The study, based on consultation with expert opinion by the Delphi method, referred to the following key issues reflected in the design of the questionnaire administered: Definition of innovation system and the approach to its development in Romania; Assessing the current state; Identify actions required immediate release. The following are the conclusions and recommendations for measures and actions resulting from the two stages of mediation responses.

5.1 Results after Round 1 of Responses In the first round, the Delphi process traditionally begins with an open-ended questionnaire. After receiving subjects’ responses, investigators need to convert the collected information into a well-structured questionnaire. This questionnaire is used as the survey instrument for the second round of data collection. The information collected after the first round of response was classified in tree main category: The concept of innovation. Conclusions drawn are: The region need to implement a system of innovation in enterprises and institutions; Innovation is seen as a source of wealth in society; Production processes based on innovation strategies become priority for innovative companies; Vectors of technological innovation system are collaborative processes, education and development, intelligent position on the market; Concern for lifelong learning and organizational knowledge is acknowledged and assumed by everyone: governments, citizens, businesses; Interaction between the governed and those who govern becomes operative and effective. Choice of approach. The proposed model takes into account innovative approaches to European structures. The recommendation steps for compliance with the EU structures innovation. Given the enormous gap towards European countries structures, it is possible that proposed model to require additions adjustments. 107


Led aspects and emerging issues. The led aspects are: Creating a legal framework consistent with the trends of European and Euro-Atlantic area to stimulate creativity and develop innovative products and services; The reform and development of education and research; Development of national innovation system to achieve non-discriminatory access; Coherent policies to attract specific funding for innovation; Use consistent and effective social innovation. Emerging issues resulted are: The emergence and development of new products and services and changes in the structure of national income share for Innovation and Development (to be more than 3% of GDP); Changes in individual consumption by generating needs, leading to the necessity of new products; The emergence of new intellectual elite in all development sectors; Motivate staff working in research - development innovation.

5.2 Results after Round 2 of Responses In the second round, each Delphi participant receives a second questionnaire and is asked to review the items summarized by the investigators based on the information provided in the first round. Accordingly, Delphi panelists may be required to rate or “rank-order items to establish preliminary priorities among items. The study led to highlight, first, that the state has a decisive role and the importance of collaboration with Romanian firms and R & D institutions, universities, and especially their connection with international innovation systems. Manifestation of the active role of the state in developing regional innovation system aims to: Taking initiatives based on programs and projects; Provision of financial resources; strengthening the legislative framework; State as a partner and mediator in the development of the system of regional innovation, working. Business sector organizations can bring important improvements in the economic sector refurbishment projects and creating new products and services. Companies should develop long term strategies on technological innovation. Strategic foreign partners may be required to contribute to the collaboration with education, research and industry in the region, common interest objectives of the strategy and relevant national programs. External institutional factors may contribute to the development of regional innovation system in Romania through direct consultation with partners in the country, loans, consulting, technical assistance, monitoring, etc.

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6 References Adler M, Ziglio E (1996) Gazing into the oracle. Jessica Kingsley Publishers: Bristol, PA Dalkey N C, Helmer O (1963) An experimental application of the Delphi method to the use of experts. Management Science, 9 (3), 458-467 Delbecq AL, Van de Ven AH, Gustafson DH (1975) Group techniques for program planning. Glenview, IL: Scott, Foresman, and Co. De Propris L (2002) Types of Innovation and Inter-firm Co-operation, Entrepreneurship and Regional Development Dupree AH (1957) Science in the Federal Government, a history of policies and activities to 1940. Dyker D, Radosevic S (2001)Building Social Capability for Economic Catch-up: The Experiences and Prospectus of the Post-socialist Countries, Innovation. Freeman C (1995) The ‘national system of innovation’ in historical perspective, Cambridge Journal of Economics, 5-24 Fowles J (1978) Handbook of futures research. Greenwood Press: Connecticut Godin B (2009) National Innovation System: The System Approach in Historical Perspective, Science, Technology and Human Values, 34 (4): 476-501 Gordon TJ, Hayward H (1968) Initial experiments with the cross-impact matrix method of forecasting. Futures, December, 1968, 1(2), pp. 100-116 Hasson F, Keeney S, McKenna H (2000) Research guidelines for the Delphi survey technique. Journal of Advanced Nursing, 32 (4), 1008-1015 Helmer O (1977) Problems in futures research: Delphi and causal cross-impact analysis. Futures, February 1977, pp. 17-31 Henrekson M, Nathan Rosenberg (2001) Designing efficient institutions for science-based entrepreneurship: lesson from the US and Sweden, Journal of Technology Transfer Hiltz SR, Turoff M (1978) The Network Nation: Human Communication via Computer, Addison-Wesley, ISBN 978-0-262-08219-8 Hsu, Chia-Chien, Sandford, Brian A (2007) The Delphi Technique: Making Sense of Consensus. Practical Assessment Research & Evaluation, 12(10) Hynes Briga, Ita Richardson (2007) Entrepreneurship education: A mechanism for engaging and exchanging with the small business sector, Education +Training, 49, 732-44 Jacob Merle, Mats Lundqvist, Hans Hellsmark (2003) Entrepreneurial transformations in the Swedish university system: The case of Chalmers University of Technology, Research Policy, 32, 1555-68 Keeble D, Wilkison F (2000) High -Technology Clusters, Networking and Collective Learning in Europe, Ashgate, England Kevles DJ (1971) The Physicists: The History of a Scientific Community in Modern America. New York: Alfred K. Knopf Levary RR, Han D (1995) Choosing a technological forecasting method. IM, pp. 14-18 Ludwig BG (1994) Internationalizing Extension: An exploration of the characteristics evident in a state university Extension system that achieves internationalization. Unpublished doctoral dissertation, The Ohio State University, Columbus Ludwig B (1997) Predicting the future: Have you considered using the Delphi methodology? Journal of Extension, 35, 1-4 Lundvall B (1992) National Systems of Innovation; Towards a Theory of Innovation and Interactive Learning, London, Pinter Marks G, Scharpf F, Schmitter W, Streeck W (1996) Governance in the European Union, London, Sage

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Miller LE (2006) Determining what could/should be: The Delphi technique and its application. Paper presented at the meeting of the 2006 annual meeting of the Mid-Western Educational Research Association Columbus, Ohio Moica S (2012) Modelul de inovare regional, Editura Universitatii Petru Maior, Targu Mures Nelson R, Winter S (1982) An Evolutionary Theory of Economic Change, Boston Nyström P, Starbuck W(1984) To avoid organizational crisis unlearn, Organizational Dynamics Spring Oh K H (1974) Forecasting through hierarchical Delphi. Unpublished doctoral dissertation, The Ohio State University, Columbus Pill J (1971) The Delphi method: Substance, context, a critique and an annotated bibliography. Socio-Economic Planning Science, 5, 57-71 Rescher (1998) Predicting the Future, Albany, NY: State University of New York Press Rowe G, Wright G (2001) Expert Opinions in Forecasting. Role of the Delphi Technique. In: Armstrong (Ed.): Principles of Forecasting: A Handbook of Researchers and Practitioners, Boston: Kluwer Academic Publishers Turoff M, Hiltz SR (1996) Computer based Delphi process. In M. Adler, & E. Ziglio (Eds.). Gazing into the oracle: The Delphi method and its application to social policy and public health (pp. 56-88). London, UK: Jessica Kingsley Publishers Ulschak FL (1983) Human resource development: The theory and practice of need assessment. Reston, VA: Reston Publishing Company, Inc

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Regional Strategic Development Method as a Tool for the Emergence of New Industries at Regional Level Ganzarain J1, Igartua J.I 2, Markuerkiaga L3 Abstract How the regional industrial network diversifies to meet the needs of a new economy is one of the key issues for the longterm competitiveness of the region. Regions diversify into industries that make intensive use of the capabilities in which they are specialized. “Regional Strategic Development Method” is showed in this research as the innovative tool to develop the regional innovation systems in order to diversify the region. The development of the tool RSDM is the aim of this investigation study, which would allow us to define a Regional transformation which is based on the local skills and competences-knowledge

Keywords: Innovation System, Regional Development, Regional System of Innovation, Diversification.

1 Introduction Innovations are widely seen as the driving force of economic growth and competitiveness. The innovation environment is, however, facing remarkable challenges where regions have to maintain and develop their well-being in global competition

1Jaione

Ganzarain Epelde ( e-mail: [email protected]) Dpto. de Mecánica y Producción Industrial. Escuela Politécnica Superior de Mondragon Unibertsitatea. Loramendi 4, 20500 Arrasate-Mondragron. 2Juan

Ignacio Igartua López ( e-mail: [email protected]) Dpto. de Mecánica y Producción Industrial. Escuela Politécnica Superior de Mondragon Unibertsitatea. Loramendi 4, 20500 Arrasate-Mondragron. 3Leire

Markuerkiaga Arritola ( e-mail: [email protected]) Dpto. de Mecánica y Producción Industrial. Escuela Politécnica Superior de Mondragon Unibertsitatea. Loramendi 4, 20500 Arrasate-Mondragron.

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under the rules of absolute competitiveness (Porter 1990; Camagni 2002, Pekkarinen & Harmaakorpi, 2006). The innovation processes are increasingly embedded in normal social and economic activities (Kline and Rosenberg, 1986; Lundvall, 1988; Schienstock and Hamalainen, 2001). The source of innovation is often the interaction of different actor-networks comprising users, producers and related development organizations. Therefore, it seems a crucial task for regional innovation policies and strategies to promote innovation in a multi-actor environment to take advantage of locally bounded spillovers (Pekkarinen & Harmaakorpi, 2006). Depending on their context, they can be called “national innovation systems” or “regional innovation system” (Lundvall, 1992;Freeman, 1987). Confessing the importance of a regional innovations system, this study focuses on the concept of a regional innovation system. The structure of the paper is as follows. Section 2 briefly introduces the literature on regional innovations systems. Section 3 describes the Regional Strategic Development Methodology. Section 4 presents the main conclusions.

2 Regional Innovation System The theory of national innovation system is endebted to the evolutionary theory of technological change (Moulaert &Sekia, 2003). The concept of the national system, reflect that there are differences between nations regarding the structure of the production systems and institutions. The historical experience, the language and the culture make those differences in the next elements of the system: internal organization of firms, interfirm relationships, role of the public sector, institutional set-up of the financial sector and R&D intensity and R&D organization. Relationships among these elements are crucial for the success of the innovation (Lundvall, 1992). Innovation has to do with long-term relationships and close interaction among external agents of the firm, according to the Sappho-study made by Freeman in the 1970s (Rothwell, 1977). This constituted one important step toward national innovation system. The second step was to realize that the relationships between agents had to be non-price, being elements of power, trust and loyalty. The third step was to realize the differences of national contexts offer a lot of possibilities to establish organized markets and processes of interactive learning. However (Lundvall et al., 2002) defined the fourth element in the combination: institutions According to (Edquist, 1997) and (Lundvall, 1992), all the core elements of the RSI have been accepted that they can also be applied to other types of systems that operate at regional levels. As indicated (Doloreux, 2002) the accurate distinction between them is difficult to establish. In fact, not all the authors make the differences between these ideas, because some categorize as different concepts whereas 112


others see regional systems as a subset of the national systems. (Cooke, Uranga & Etxebarria, 1998) defined a RIS as a system “in which firms and other organizations are systematically engaged in interactive learning through an institutional milieu characterized by embeddedness”. As determined (Doloreux, 2002), RIS not only will be reproduced by the creation of knowledge by firms and institutions, but also it needs the interaction of these organizations. Three important facts should be noted about the concept of RIS. First, it is a social system. Second, it needs interactions between public and private sectors. And third, it is created to enhance the localized learning capabilities of a region. On the authority of (Doloreux, 2002) there are different mechanisms in Regional Systems of Innovation, which are divided in two groups: the basic elements and the relationships between them. The Regional System of Innovation has four basic elements: firms, institutions, knowledge infrastructures and innovative policy. Firms are the economic agents that have an important role by taking responsibility for generating and diffusing knowledge. Institutions are the next ones: governments, universities, industrial research and development institutions, etc. The collaboration between these elements is key in order to diversify regions into industries that make intensive use of the capabilities in which they are specialized in (Boschma, Minondo, and Navarro, 2013). In this sense the Regional diversification is high on the scientific agenda. Actually many regions are facing a severe economic decline, there is an increasing awareness that there is a need to develop new economic activities to compensate for the decline and losses in other economic activities (Boschma, Minondo, and Navarro, 2013). What determines regional diversification, and how do regions develop new growth paths is a fundamental question (Simmie and Carpenter, 2007; Fornahl, Henn, and Menzel, 2010).

3 Regional Strategic Development Method Regional strengths and potentials play an important role in creating future innovation for the region and sectorial strategies. In this study, the RSDM is presented as an organizational innovation for a regional innovation policy (Harmaakorpi and Pekkarinen, 2002; Harmaakorpi, 2004). The method helps to look for regional business potentials on which it is possible to build the future competitive advantage of a region. The idea of developing the RSDM has been the importance of the individual regional development paths in designing development strategies. The strategies are based on a thorough assessment of regional resources, capabilities and compe-

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tencies, and future opportunities leading to business potentials, which can give a region a competitive advantage. The RSDM can be seen as a network leadership tool helping the regional actors to interact during the development process, as well as helping to promote dynamic capabilities and creative social capital in a region. The RSDM uses the concept of a regional development platform as a tool for seeking regional business potential. The method is a useful tool in exploring existing business potentials in regional resource configurations. The concept of regional development platforms is related to the concept of clusters. Regional Strategic development method aim to describe the potentials that can form future regional clusters of the existing resource base rather than describe existing clusters and it can be defined as regional resource configurations based on the past development trajectories, but presenting the future potential to produce competitive advantage existing in the defined resource configurations (Harmaakorpi and Pekkarinen, 2003, pp. 8–9). The RSDM consists of four phases:  Diagnosis of the Region: Background study of the industries and areas of expertise in the region.  Measurement of the capacity of development of the region.  Analysis of key variables for the future development of the region. (Analysis of statistical and empirical information)  Assessment of future scenarios.

3.1 STEP 1: Diagnosis of the Region: Background Study of the Industries and Areas of Expertise in the Region A preliminary diagnosis was developed using Porter’s Diamond (Porter,2003), analyzing the demand conditions of the region as a demanding client enable the companies to discover needs in sight which promotes the innovation. The productive factors were also examined due to anticipate the needs of the region knowing its hereditary legacy, natural resources, touristic attractions, etc. The related industries or clusters are very important as considering the region as a whole is what will make each company successful. And finally the firms’ strategy, structure and rivalry of the enterprises require an environment where competitiveness led to innovation. Furthermore, the government or politics can also affect the region’s development as the result of their work and conditionates the companies’ activities having a bearing on the product’s competitiveness capacity and the services given. The institutions for collaboration were also analyzed as their main aims are to improve the region’s productivity, its profitability and the companies’ contribution to the added value for the clients, apart from providing information and technology 114


and promoting collaboration among different enterprises boosting joint initiative and projects.

3.2 STEP 2: Measurement of the Capacity of Development of the Region: Competency Tree Workshop The objective of this phase was to describe the current situation developing a diagnosis of the region so key variables could be identified. It’s necessary to know how the region was in the past, how it is nowadays to forecast possible future scenarios. That analysis is carried out with the help of the competency tree workshop. It consist on a basic analysis and assessment of the region’s technological, industrial, social, cultural, environmental, trading and productivity competences. There’s going to be developed a tree for each era, one for the past and one for the present. In both of them, the root represents the crafts, skills, resources and knowhow, the trunk represents the implementation, organization and applications of them, and finally, the branches represent the product and services lines and the market. The Competency trees workshop was held to visualize the changes and development in the area in terms of labour situation. The roots of the tree represent the resources and competences a region has. The trunk shows the equipment and infrastructures of the region. And on the top of the tree, the branches display the products or services sold in different areas along the World.

3.3 STEP 3: Analysis of Key Variables for the Future Development of the Region. (Structure Analysis (MIC MAC mation) Structural analysis of the system is important from various points of view. It’s an opportunity for a thorough presentation of the system under study and reduces the complexities of the system in simple understandable language. It can also be used in decision making to achieving the desired objectives and in forecasting, which is what prospective needs. The identification of key variables which could influence the future dimensions is necessary to evolve appropriate policies and strategies. The structural analysis is a tool that vertebrates the pooling of ideas. This form of analysis describes a system using a matrix which combines the constituent components of the system and identifies the main variables which are both influential and dependent: those which are essential to the evolution of the system.

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So, this phase consists in identifying the key variables, that is to say, those essential to the system's development, first by using direct classification, then through indirect classification (Godet ,2007). The methodology for identification of key variables based on direct as well as indirect inter-relationships (Impact Matrix Cross-Reference Multiplication Applied to a Classification -MIC MAC technique) which, often, may not be clearly visible is explained below. The classification of the variables in different types of roles being played by each one is also presented by using the driver-dependence matrix.

Fig. 1 MIC MAC matrix

Those essential variables identified through MIC MAC keep the system going, so it is relevant to identify them in order to identify actions that describr the new scearios to diversify. As shown in the figure, Input variables are very influential but not much dependent from the way the system works. Among them determinant and environmental variables are defined. The Output variables include the result and target variables. Finally the strategic axis embraces autonomous and key variables and regulating and secondary levers. It shows the variables that influence on the smooth running of the system and the strategic challenges of the system. Changing these variables has an evolution effect on the other variables depending on their driving and dependence level. So, depending on each variable result, a particular location on the driving power and dependence diagram and a particular characteristic on the region development system will be given. These categories differ from each another depending on the specific role the variables can play in the system's dynamics. The strategy axis is composed by the variables that have a higher enough to be important for the system operation combined with a dependency that make then subject to alterations on them. The strategy axis analysis is complementary to the one done on the subsystems, which clears up the relationship among the variables and let us know the way to follow with some of them, starting from the ones in the bottom-left till the ones on the right-top, the key ones.

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Once the situation of the region and the potential on it it’s known, the structure analysis started with direct related variables study and then the MIC-MAC method for the analysis. It was defined the list of variables or factors most significant of the system. On the questionnaires they were asked on the matters of demography, social, socioeconomic, economic, tax system, environmental, health, technology, energetic, transport, town-planning, territorial, infrastructure, educational, training and political-administrative issues, which are explained below: So, to find the region’s key variables among the ones defined, the agents were split in groups of three people. Each group had a list of ten variables that had to relate with all the rest to see the influence of them on the others. Using this tool, a direct relationship between different variables is quantified but the the filling-in must be qualitative. But to understand how all these variables act in the development process of the region it’s very important to know the non-direct relationship among them and this filling-in phase helps to pose variables, some of which would have been evaded if such a systematic and thorough investigation had not been carried out. This questioning procedure not only enables one to avoid errors, but also helps to organise and classify ideas by creating a common language within the group and allows for a redefinition of the variables and therefore tends to make a more accurate analysis of the system.

3.4. STEP 4: Assessment of Future Scenarios. Finally, after knowing who the region works and its results, possible future scenarios can be developed and making them the basis, fix a strategy to follow for the region’s development. A scenario has to be coherent, credible transparent and pertinence so the ones involved can feel as a part of it and act to make it happen. There are two types of scenarios: exploratory ones, which taking the past and present tendencies as a starting point lead to a probable future, and the anticipation one, which is based on different pictures of the future that could be desired or feared. But to set up a scenario the first thing to be defined is the basis. With all the results of the previous steps, competency trees and structure analysis the basis for the scenarios is set as it determines where to start and all the characteristic of the region. Then, it is necessary to mark the possibilities and reduce the uncertainty. Having the basis of the scenarios, and rounding it with some hypothesizes a big amount of possibilities will be defined. Uncertainty can be reduced considering probability of different future’s combinations’ happening, in a subjective way, using some expert’s methods.

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These different futures will be tuned in with the compatible development mechanism and the system key variables will be steered towards the way the region has to follow from current situation to the represented future in a coherent way. So far, a tendency scenario will be defined, which will be the most probable path to follow and then, two contrasted scenarios, one feared scenario and other strong-willed so that all the possibilities are covered. The most important stage on this point is to cover all possible fields of probable scenarios. This phase should be effectuated in interaction between the main actors of a region using future research methods, like Delphi method.

4 Conclusion Increasing innovative capability is a key factor in building regional competitive advantage under the present techno-economic paradigm. Regional innovative capability is formed by the innovative capability of the regional actors and their cooperation in innovation processes. In the present study, the RSDM was presented as an innovative method to explore and exploit the best business potentials in a networked regional development environment. This methodology is orientated to promote regional diversification based on key competencies of the different agents in the region.

5 References Boschma, Minondo, and Navarro, 2013 The Emergence of New Industries at the Regional Level in Spain:A Proximity", Economic Geography, 2013, vol.89,pp. 29-51 Approach Based on Product Relatedness Cooke, P., Uranga, M.G. & Etxebarria, G. 1998, "Regional systems of innovation: an evolutionary perspective", Environment and Planning A, vol. 30, pp. 1563-1584. Doloreux, D. 2002, "What we should know about regional systems of innovation", Technology in society, vol. 24, no. 3, pp. 243-263. Edquist, C. 1997, "Systems of innovation: Technologies, organisations and institutions", London: Pinter, . Fornahl, D.; Henn, S.; and Menzel, M., eds. 2010. Emerging clusters. Cheltenham, U.K.: Edward Elgar. Freeman, C., 1987. Technology Policy and Economic Performance: Lessons from Japan. Pinter, London. Godet, M. (2007). La Caja de Herramientas de la prospectiva estratégica. España. Kline S. and Rosenberg N. (1986) An overview on innovation, in Landau R. and Rosenberg N. (Eds) The Positive Sum Strategy, pp. 275–305. National Academy Press, Washington, DC.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Lundvall B.-A° . (1988) Innovation as an interactive process: from user–producer interaction to the national system of innovation, in Dosi G., Freeman G., Nelson R., SilverbeRG G. and Soete L. (Eds) Technical Change and Economic Theory, pp. 349– 369. Pinter, London. Lundvall, B.Å. 1992, "National systems of innovation: towards a theory of innovation and interactive learning", . Lundvall, B.Å., Johnson, B., Andersen, E.S. & Dalum, B. 2002, "National systems of production, innovation and competence building", Research policy, vol. 31, no. 2, pp. 213-231. Moulaert, F.&Sekia, F. (2003) Territorial innovationmodels: A critical survey, Regional Studies, 37(3), pp. 289–302. Pekkarinen & Harmaakorpi, 2006 "Building Regional Innovation Networks: The Definition of an Age Business Core Process in a Regional Innovation System", Regional Studies, Vol. 40.4, pp. 401–413 Porter, M. 2003, "The economic performance of regions", Regional Studies, vol. 37, no. 6-7, pp. 545-546. Rothwell, R. 1977, "The characteristics of successful innovators and technically progressive firms (with some comments on innovation research)", R&D Management, vol. 7, no. 3, pp. 191-206. Schienstock G. and Hamalainen T. (2001) Transformation of the Finnish innovation system. A network approach. Reports Series No. 7. Sitra, Hakapaino Oy, Helsinki. Simmie, J., and Carpenter, J., eds. 2007. Path dependence and the evolution of city regional development.Working Paper Series No. 197. Oxford, U.K.: Oxford Brookes University

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Costing a Product by Old and New Techniques: Different Wines for Different Occasions Ruiz de Arbulo López, P1, Fortuny-Santos, J2, Vintró-Sánchez, C3 Abstract The aim of this paper is to compare and contrast four different costing systems: Full costing, Activity-based Costing (ABC), Time-driven Activity-based Costing (TDABC) and Value Stream Costing (VSC). Companies around the world use different costing techniques for a variety of reasons and a particular plant may wonder which approach would fit better its needs. Since TDABC and VSC are new techniques, there are not many references in literature and not many companies have implemented them. For this reason, the comparison is done by means of a case study. Results given by the four methods may be more or less similar depending on the structure and organization of both the process and the company.

Keywords: Time-driven activity-based costing; lean manufacturing; value stream costing.

1 Introduction The need of companies for precise information on costs is out of question because an adequate knowledge about costs is a key factor to assure the profitability of businesses. In some industries, the selling price of their products is fixed by their customers and manufacturers cannot influence prices: the only one variable that

1 Patxi Ruiz de Arbulo (e-mail: [email protected]) Business Organization Department, Faculty of Engineering Bilbao, University of The Basque Country (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 2Jordi

Fortuny-Santos Business Organization Department, Technical University of Catalonia, Avda. Bases de Manresa, 61-73 – 08242 Manresa, Spain. 3Carla

Vintró –Sánchez Business Organization Department, Technical University of Catalonia, Avda. Bases de Manresa, 61-73 – 08242 Manresa, Spain.

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they can act upon is the manufacturing cost. This is especially important in the environment of international economic crisis that companies are currently facing. Besides, the costing system has to be able of capturing the effects on cost of the efforts placed on improving processes. In practice, different cost-accounting methods are applied: traditional costing systems such as full costing, more recent approaches like Activity-based Costing (ABC), or 21th Century wannabes like Time-driven Activity-based Costing (TDABC) or Value Stream Costing (VSC). Karmarkar et al. (1990) state that the reasons why companies use one or another costing system are not well known, but they, empirically, appear related to the manufacturing process (complexity, layout, number of products, and so on). In this paper, we try to shed light on that question by means of a comparison among four cost-accounting methods (Full costing, ABC, TDABC and VSC) in a case study. Different comparisons between accounting methods can be found in Balakrishnan et al. (2012) and Li et al. (2012, but there is no other previous comparison among these four costing methods in literature.

2 Research Methodology: a Case Study In order to facilitate the assessment on the major or minor complexity of application and the goodness of their results, we introduce a practical case that depicts the main differences among Full Costing, ABC, TDABC and VSC. We know of companies, in Spain, that have evolved from full costing to ABC and even TDABC (Ruiz de Arbulo et al., 2013a) but we do not know of any company that has implemented VSC so far. For this reason the research approach could not be a massive survey. When little is known about an issue, a case study is indicated due to its exploratory nature (Voss et al., 2002). Our example is constructed on a case study in previous literature (Ruiz de Arbulo and Fortuny-Santos, 2011) and it is complete enough to appreciate the techniques used by the different costing systems but also short enough for an easy comprehension. Table 1 Average time and production schedule for each product type. Number of parts in each type of knob

Time (seconds) Quantity (knobs /month)

Knob A

Knob B

Knob C

140

100

80

2,000

2,000

1,000

121

5,000

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1(continued) Average time and production schedule for each product type. Number of parts in each type of knob Parts

Knob A

Knob B

Knob C

Cost per part (€)

Part 1

1

1

1

0.25

Part 2

0

1

1

1.00

Part 3

1

0

1

1.20

Part 4

0

0

0

0.80

Part 5

0

1

0

0.60

The company manufactures and sells plastic parts for the automotive sector. The manufactured products are booth locking knobs used to open the booth of the car. The manufacturing process has three phases: Injection molding, painting and assembly but here only the assembly process is considered. This process is performed in a U-shaped cell where three different types of knobs (A, B, and C) are assembled. Table 1 shows the production schedule and the standard time (derived from work study) to assemble each knob. Knobs are made up of several parts (numbered 1 to 5), depending on the model (Table 1). In consequence, the cost of materials is different for every model.

3 Computing the Full Cost of the Products Full Costing classifies manufacturing costs as either direct or indirect. Direct costs are traced to manufactured products considering the consumption of each product. Indirect costs (overhead) are assigned using a two-stage allocation process:  •In the first stage, resources are allocated to cost centers (cost pools) and costs accumulated in auxiliary departments are assigned to main departments on the basis of the usage that main departments have of auxiliary departments.  •In a second stage, overheads are allocated to products. Usually volume-based cost drivers are used. In our example, direct labor hours would be the common allocation basis (Table 2 shows how indirect costs are allocated). This would entail that a greater proportion of costs would be allocated to products with bigger labor content. The overhead assigned to those products subsidizes (Cooper and Kaplan, 1988) the assumed profitability of the rest of products. Table 3 shows the resulting cost of the products. While products A and C are not much different, their costs are different because more overhead is allocated to knob A than to knob C.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 2 Allocation of costs in the auxiliary departments Material handling

Quality control

Cost pool (€/month)

3,000.00

4,000.00

Standard labor hours per month

155.56

155.56

Unit cost (€/LH)

19.29

25.71

Costs will be unreliable whenever the allocation basis is unrelated to the nature of the cost (in our case, there is no relation between quality inspection or replenishment and the time needed for assembly of one product). Errors will be greater in companies where overhead is greater than direct labor and material costs. This distortion may lead to decisions such as considering knob A unprofitable. Distortion caused by the allocation of indirect costs has been criticized since the 1980s (Cooper and Kaplan, 1988). For this reason, ABC appeared as a model that might overcome the pitfalls of traditional cost accounting. Table 3 Costing products using full costing (including overhead allocation) Manufacturing costs

Knob A

Knob B

Knob C

Raw material (€)

2,900.00

3,700.00

2,450.00

Direct labor €)

12,444.44

8,888.89

3,555.56

Handling (€)

1,500.00

1,071.43

428.57

Quality control (€)

2,000.00

1,428.57

571.43

Manufacturing costs (€)

18,844.44

15,088.89

7,005.56

Manufactured units

2,000.00

2,000.00

1,000.00

Unit Cost (€/knob)

9.42

7.54

7.01

4 Computing the Cost with ABC The philosophy of ABC relies on the idea of performing “activities”. Resources are assigned to activities and then activities to products. Manufacturing and some non-manufacturing activities can be assigned to products (or other object costs such as orders or clients) if there is a logic cause-effect relationship. The process was examined in detail. People from different departments were interviewed in order to obtain information on their tasks and the time spent in each one. That allowed the definition of several activities. The cost of an activity includes all types of resources necessary to perform the activity (Table 4). Data refer to one month.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 4 Costing activities using ABC: From resources to activities Activity

Part of time 1

Activity

Cost

Number

Cost

cost

Driver

of drivers

per driver

1602

18,75 € / replacement

156

160 € / LH

Taking parts to/from the assembly cell

15%

3,000 €

Number of times replenished

Assembly

100%

24,960 €

laborhours

Assembled 5,000 0,8 € / unit units 1 Proportion of their working time spent in this cell by people devoted to replenishment, assembly or quality control (the rest of their time is devoted to other tasks or departments). 2The parts of knob A are replaced 10 times per month (50 times, knob B; 100 times, knob C). Quality control

12.5%

4,000 €

From the information in tables 1 and 4, we compute the costs of the different models of knobs (Table 5). Now, the costs of products A and B are similar and C is the most expensive. However, due to the detail it requires, ABC is difficult to apply (especially in large companies) and, while the time figures indicated in table 4 are exact, in practice they would be estimated and therefore they might carry a certain error. Besides, an “activity” is just a cost pool and therefore, another way of allocating overhead to products. Table 5 Costing products using ABC: From activities to object costs Costs

Knob A

Knob B

Knob C

Material cost (€)

2,900.00

3,700.00

2,450.00

Direct labor (€)

12,444.44

8,888.89

3,555.56

Replenishment (€)

187.50

937.50

1.875.00

Quality control (€)

1,600.00

1,600.00

800.00

Manufacturing cost

17,131.94

15,126.39

8,680.56

Manufactured units

2,000

2,000

1,000

Unit cost (€/knob)

8.57

7.56

8.68

5 Refining the Cost with TDABC Kaplan and Anderson (2004) developed TDABC. There has been a certain debate whether TDABC is a simplified version of ABC or a completely new approach. In any case, TDABC may be more precise when ABC cannot model processes in detail (or it would be too complicated). The method relies in estimating the cost per time unit of capacity and them modeling tasks by means of time equations. In 124


our example, While ABC considered the replenishing activity equal for all the three knobs, the replenishing process depends on the type of knob considered: For knob A, the time is 15 minutes; for knob B, it is 10 minutes, and finally for knob C, the time is 5 minutes. Equation 1.1 gathers all this information (where X 1 would be 1 for knob A or 0, otherwise. In a similar way, X2 and X3 would act for knobs B and C). Replenishment (in minutes) = 15 X1 + 10 X2 + 5 X3

(1.1)

The time for performing the quality control of each knob depends on the number of points that have to be checked. There are 10 points in knob A, 9 in knob B and 8 in knob C. Equation 1.2 gathers all this information (where X is the number of checkpoints: 10 in knob A; 9 in knob B, and 8 in knob C). Time for quality control (in minutes) = 0.02 X

(1.2)

TDABC computes the cost per unit of time (minute) for the “group of resources” in charge of replenishment as shown in table 6. Following Kaplan and Anderson (2004), we consider that on the basis of 40 working-hours per week, the effective capacity is 80% of the theoretical capacity. In a similar way, not shown here, the cost of quality control results to be 4.34 € / min. Table 6 Estimating the cost per time unit in replenishment Capacity (per week)

40 h x 0.15 workers =

Effective capacity (4 weeks per month)

0.8 x 6 x 4 =

Total cost of resources Cost per minute

6.00 labor hours 19.20 labor hours 3,000.00 €/month

3,000 / (19.2 x 60) =

2.60 €/min

According to table 4, the parts of knob A are replaced 10 times in one month, 50 times in knob B and 100 times in knob C. The coefficients in equation 1.1, enable us to determine the time for replacement in each knob and the cost of replacement per unit of product, by multiplying the time devoted to each knob and the cost per unit of time and dividing by the production (units). Similarly (Table 7), using equation 2 we obtain the cost of quality control per unit of product (knob). Finally, we add the cost of replenishment and inspection to the cost of assembly in order to compute the total cost of production of each product in TDABC (Table 8).

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 7 Estimating the cost per knob (as a function of time) using TDABC Knob model

Time (minutes) for replacements of material

Unit cost of replacement (€/knob)

Model A

15 x 10 = 150

150 x 2.60 / 2,000 = 0.1953

Model B

10 x 50 = 500

500 x 2.60 / 2,000 = 0.6510

Model C

5 x 100 = 500

500 x 2.60 / 1,000 = 1.3021

Knob model

Time (minutes) for inspection

Unit cost of quality control (€/knob)

Model A

0.20 x 2000 = 400

400 x 4.34 / 2,000 = 0.8681

Model B

0.18 x 2000 = 360

360 x 4.35 / 2,000 = 0.7813

Model C

0.16 x 1000 = 160

160 x 4.34 / 1,000 = 0.6944

Table 8 Computing the total cost per knob using TDABC Knob model

Material (€/knob)

Replenishment (€/knob)

Assembly (€/knob)

Quality (€/knob)

Total (€/knob)

Model A

1.45

0.1953

(140/3,600) x 160 = 6.22

0.8681

8.74

Model B

1.85

0.6510

(100/3,600) x 160 = 4.44

0.7813

7.73

Model C

2.45

1.3021

(80/3,600) x 160 = 3.55

0.6944

8.00

In our example, TDABC can capture the complexity of the operations easily and better than ABC. This will be valid whenever the time is the right cost driver and if the study is accurate, because the group of resources is nothing else than a cost pool. Considering the shop floor as one single group of resources would have led us to the conclusions in table 3.

6 Computing the cost by value stream Since full costing motivates non lean behaviors such as overproduction and ABC entails a lot of non-value added tasks, Maskell and Baggaley (2004) created VSC to support lean companies. VSC assigns both direct and indirect costs to a value stream (Table 9) on condition that the company is organized by value streams with few shared resources amongst them, including non-manufacturing departments (Ruiz de Arbulo et al., 2013b). Raw material (2,900 € of material in product A, 3,700 € in product B and 2,450 € in product C in a month), labor, depreciation and other conversion costs are included, while costs outside the value stream are not.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 9 Computing the cost of the value stream Centers

Cost of materials (€/month))

Replacement Assembly

9,050.00

Quality Total

Labor (€/month)

Depreciation costs (€/month)

Other costs (€/month)

Total cost (€/month)

1,000.00

1,000.00

1,000.00

3,000.00

18,000.00

5,060.00

1,828.88

33,938.88

1,000.00

4,000.00

3,828.88

40,938.88

3,000.00 9,050.00

22,000.00

6,060.00

VSC is different from other approaches because it focuses on the value stream as a whole and is not interested in isolating the cost of a specific product. Its aim is to see how each step contributes to the cost of the value stream and how continuous improvement activities cut those costs. It is possible to compute the cost of products one by one the basis of the characteristics of the flow of products through the value stream chain. In Table 10, we consider that it would be possible to assemble 4,000 model A knobs in a month (155.6 working hours x 3,600 seconds per hour /140 seconds per knob), 5,600 model B knobs and 7,000 model C knobs. Since costing products with VSC only takes into account one feature of the product, related to the assembly time, results are distorted as in Table 3. Table 10 Costing each knob with VSC Knob

Material

Capacity

Conversion cost

Total cost

type

(€/unit)

(units/month)

(€/unit)

(€/unit)

A

1.45

4,000

31,889/4,000 = 7.97

9.42

B

1.85

5,600

31,889/5,600 = 5.69

7.54

C

2.45

7,000

31,889/7,000 = 4.56

7.01

7 Final Discussion and Concluding Remarks The aim of this paper is to explore how different accounting systems can model manufacturing processes and supply cost information. Full costing, accepted for reporting purposes, gives an idea of all the necessary costs to make a product in the long run, but overhead allocation distorts costs. ABC is considered a great innovation in the management accounting literature but it is difficult to implement and sustain. It can be very accurate and reveal the causes of costs -although it was not the case in our example-, which can be used for process improvement. TDABC can model processes where time is the right cost drivers. Because the activities of replenishment and quality control depend on the type of product, the cost computed using TDABC is more accurate than the average value obtained us127


ing ABC. ABC could be as accurate by using multiple drivers but it would be really complicated. Results show that TDABC is the method that best fits our example. VSC can only be implemented in lean plants. Because it is more concerned with process improvement than with cost measurement, costing products with VSC does not take into account all the characteristics of the products. In the future, this preliminary research will be enriched by a survey on the application of the new accounting approaches in (especially SME) Spanish firms.

8 References Balakrishnan R, Labro E, Sikavramakrishnan K (2012) Product costs as decision aids: An analysis of alternative approaches (parts 1 and 2). Accounting horizons 26(1):1-41 Cooper R, Kaplan RS (1988) How cost accounting distorts product costs. Management accounting 69(10):20-27 Karmarkar US, Lederer PJ, Zimmerman JL (1990) Choosing manufacturing production control and cost accounting systems. In: Kaplan RS (ed). Measures for manufacturing excellence. Harvard Business School Press, Boston. Kaplan RS, Anderson S (2004) Time-Driven Activity-Based Costing. Harvard business review 82(11):131-138 Li X, Sawhney R, Arendt EJ, Ramasamy, K (2012) A comparative analysis of management accounting systems’ impact on lean implementation. International journal of technology management 57(1-3):33-48 Maskell B, Baggaley B (2004) Practical lean accounting. Productivity Press. New York Ruiz de Arbulo Lopez P, Fortuny-Santos J (2011) Innovación en gestión de costes: del abc al tdabc. Dirección y organización, 43:16-26 Ruiz de Arbulo Lopez P, Fortuny-Santos J, Vintró Sanchez C, Basañez- Llantada, A (2013a). Aplicación de Time-Driven Activity-based Costing en la producción de componentes de Automóvil. Dyna Ingeniería e industria 88(2):234-240. Ruiz de Arbulo Lopez P, Fortuny-Santos J, Cuatrecasas-Arbós L (2013b) Lean manufacturing: costing the value stream. Industrial management and data systems 113(5). Voss C, Tsikriktsis N, Frohlich M (2002) Case research in operations management. International journal of management 22(2):195-219

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An Electric Taxi Fleet Charging System Using Second Life Electric car Batteries Simulation and Economical Approach Canals Casals Ll1, Amante B2 Abstract The industrial car manufacturers see in the high battery price an important obstacle for an electric vehicle mass selling, thus mass production. Therefore, in order to find some cost relieves and better selling opportunities, they look and push forward to find profitable second battery uses. This study presents a simulation and an economical approach for an electric taxi fleet charging system, using these “old” electric car batteries, implemented in the city of Barcelona. The simulation was done in order to optimize the number of stations and batteries per station according to the number of cars on the project. Even if it’s not economically reliable at the moment, it is an alternative to take into account if there’s a truly concern with the environment and the compromise to decrease the CO 2 and other emissions.

Keywords: Electric Car, Taxi, Second Use, Battery, Li-ion.

1 Introduction The automotive industrial world is slowly appreciating a change towards the electric car: the not so far to come European emission regulations expect a low limit emissions level that seems hard to achieve by only using the actual or even improved internal combustion motors and even suggest the use of electric or hybrid vehicles as an alternative (ECR, 2009). But still, the two main problems for selling 1Lluc

Canals Casals ( e-mail: [email protected]) GIIP. Dpto. Proyectos de Ingeniería. ETSEIAT (Escola Tècnica Superior d’Enginyeries Industrial i Aeronàutica de Terrassa. UPC Edificio TR5. C. Colom 11, 08222 Terrassa. 2Beatriz

Amante García ( e-mail: [email protected]) GIIP. Dpto. Proyectos de Ingeniería. ETSEIAT (Escola Tècnica Superior d’Enginyeries Industrial i Aeronàutica de Terrassa. UPC Edificio TR5. C. Colom 11, 08222 Terrassa.

129


these vehicles to most of population are the high price (mostly due to the battery costs) and the not so long displacement range (about 200km max.) (Broussely M, 2007). In order to solve the first one, the automotive industry is searching for second uses of the already used batteries trying to have some extra revenue and decrease the selling price (Kley F., 2011) , (Vilayanur et al, 2011). For the displacement range, fast 15 to 30 minutes charging stations are considered (Botsford C. et al, 2009), (Muñoa J.A. 2009) as first steps to permit longer drive trips. With this time, the batteries are charged until an 80% of SOC which is, by the way, the normal charge available for second use batteries (Kley F., 2011) .

2 Material and Methodology The idea of a charging system for an electric taxi fleet using recovered “old” batteries comes from unifying the two propositions in one project. The use of second life batteries reports a money income to the car manufacturer, which is a must considering the high prices from today (Broussely M, 2007) and the 15-30 minutes charge per taxi would permit the taxis to cover the whole day work medium range of a Barcelona Taxi service with just one charge during the day. It is considered that the medium km range per year of a Barcelona taxi is close to 42.000km (Amat C. 2010), (Zamora B. et al, 2012). That is, divided by 230 working days, 183km per day. It is close to the maximal range defined by some car manufacturers. For this simulation a 130km average range will be taken, considering that a 10-15% of security margin will be taken by the drivers before getting out of energy. That means that each car will surely have to stop once during working time and the next charge, in order to start the day with a full capacity, will be done at home while the car is parked and the driver sleeping in a slow charging mode. The use of second use batteries (“old batteries” from now on) for this system is thought because the normal fast charge stations presents enormous instant consumption, power and high voltage installations that might come with legislative and security impediments if implemented inside the city (Botsford C. et al, 2009). What is presented here is a system that charges at a low velocity rate, with a common 220V electricity installation, the “old batteries”. Then, when they are charged, its energy is trespassed to the ones in the vehicle in a fast charge mode. The interesting point is that this fast charge is done isolated from the grid, so no high power demand is necessary. The car batteries need a 6 to 8h charge (Botsford C. et al, 2009) on a slow charging mode, and so will do the “old” ones. If they need 6h charge, it means that almost four cars can be charged per day, on the contrary, if it’s close to 8h, that will correspond to 3 charged cars per day. This is important for the economic and 130


volumetric issues, as more cars are charged per battery, less batteries have to be placed per station. As a fast charge takes over 30 minutes to conclude (see considerations below) if a free spot is desired to be freed every 15 minutes, a minimum of two charging spots per station should be installed. And as the second use batteries are supposed to need 6h to be ready to transfer its energy to the taxis, and one should be ready every 15 minutes, at least 24 batteries should be placed per station. In figure 1 there’s a schema of what it has been just told. The black lines represent taxis entering and leaving the charge station. The yellow ones represent the stages of the second use batteries. When they are ready they are shown as “entering” into the station with a taxi and they give their charge to the taxi in the 1 st or 2nd charging spot for over 30 minutes. When the cars are charged the second use batteries are discharged and they change to the 6h slow charge mode (which is represented as the second use battery 6h charge box) until they are ready again to restart the cycle. Charged Second use batteries Incoming taxi

Charged Second use batteries Incoming taxi

Taxi charging 1st spot. 30min

Second use battery 6h charge

Taxi charging 2nd spot. 30min

Taxi goes back to work and home

Fig. 1 Schema of a single 2 spot station.

The simulation was done as described in figure 1 for a single 2 spot station. In order to eliminate queues, the taxi fleet should agree that each taxi should start working at a scheduled time (each hour, half an hour or per quarter of an hour). If all taxis start working at the same moment, the stations should be overdimensioned during most of the day in order to be able to have free spots when almost all cars come to charge. In all cases tested a whole week simulation was done in order to eliminate the first steps transitory effects. Although some analyses were done taking the 8h low charge rate, in this article only 6h will be discussed because it is considered that if it does not work economically in this way nor will it do with a lower charge rate (which is a worse optimized / optimistic model).

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Since beginning 2013 there’re no more working turns in Barcelona (taxibarcelona.cat, 2013), so the fleet can apply its own schedule in order to optimize the availability of charging spots and batteries. As it is impossible to apply a minute to minute schedule such as: a taxi will enter into work at exactly every 8 minutes, it is suggested (simulations were done so in this way) to establish a beginning to work timetable each every hour. A balance between cost and waiting time was done in the analysis. Considerations taken: 1. The average waiting time by taxis on the charging station for a free spot should not exceed the 10 minutes, 2. Almost no time was considered as allowable in waiting for a battery to be charged. Therefore, two extra second use batteries per station were added. It will also be useful in case of damaged or degradation of too aged batteries. 3. No more than an hour waiting for a free spot was acceptable as a positive result. 4. Cars entered into the simulation every hour with a 5 minutes standard deviation. 5. 6h with a 10 minutes deviation was considered as second use battery charge time. 6. 30 minutes discharge (or car charge). Even if in most of the cases the expected charging time would be less than 30 minutes (Botsford et al, 2009), some minutes were added because of the drivers needed time to disconnect and leave the spot free. 7. Because of the different driving characteristics (and electricity consumptions in consequence) a deviation of half an hour is added to the system to make a more realistic need to charge situation.

3 Results and Discussions The less expensive solution encountered taking the previous considerations into account was a 26 battery per 2 spots. The simulation result showed that each spot was capable of providing energy to an average of 42 cars per day. As the longest distance in Barcelona is from the airport to the other edge of the city and it is no more than 20 km, it is considered that a taxi will always be able to go to the next charging station without problems if the car gives an alarm when 15% of SOC is achieved (15% of 130km gives 19,5km). Note: If the stations have more than 2 spots, having less than 2 extra batteries per spot showed also good results. Anyhow, the extra cost of another battery per spot is of 24€/year per driver, so the money saved per year is not what makes de difference.

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With this disposal an 85% of the “theoretically” station capacity was used. Even so, as it can be appreciated in table 1, the queues attained an average of 9 minutes waiting for a free spot and a maximum waiting time of 57 minutes (almost an hour). To this waiting time it has to be added the 30 minutes charging, so the driver that took almost an hour and a half for refilling the battery will surely be annoyed. It can be also appreciable that sporadically some taxis have to wait for a battery to be charged. As it is such a low percentage (average around 0 to 1 minute) it is considered as a non-common situation and therefore not as relevant as to pay the over-costs to eliminate it. Table 1 Average and maximum queue waiting time Average (min)

Max. waiting time (min)

Total taxi queue

9

57

Waiting for battery

0-1

30

Waiting for a free spot

9

56

For the cost analysis, it was considered that the difference between the fuel cost and the electricity cost for transportation use would be maintained during the 8 years to come. Cost calculation assumptions: Electricity cost: 0,1509€/kWh, 1,822443kW/month(gasnatural, 2013). Fuel (gasoil) cost: 1,36€/l. Consumptions: 0,7l/km for a common diesel car and 0,15kWh/km for the electric taxi. 185km Km per day . Price per kWh to buy a second use battery = 100€/kWh (Neubauer J.S. et al, 2012), (Cready E, 2003). Price per kWh to sell a second use battery = 75,5€/kWh (Neubauer J.S. et al, 2012), (Cready E, 2003). 20kWh battery packs for the taxi fleet and second use batteries. 10.000€ per spot installation 16.000€ for a new diesel car. 3 28.000€ for an electric car (without subventions). With these assumptions, the cost analysis indicates that on consumption, the savings per year are about 3.030€ when using an electric vehicle against a common diesel one.

3

This car costs (points 8 and 9) are taken as an average of the market at the moment. The difference between one and the other is taken from the Renault Kangoo model, which is sold with both technologies with a 12.000€ difference (12.500€ diesel vs 24.575€ the electric version).

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If we consider 2 stations with two spots each, its price goes around 40.000€ to be amortized in 10 years, there will also have 52 second use batteries that do the main gross amount of money: 104.000€ per year. The second use batteries are expected to provide still 1000-1300 cycles before its definitive retirement to recycle (Cicconi P et al, 2012). As the batteries are working all year long doing 4 cycles per day, at the end of the year they will have done more than 1300 cycles and they will be mostly unable to charge enough energy to the coming taxis. They should be removed and changed. Per year, the total installation costs rises up to 108.000€. This should be divided by all the taxi fleet. The results of the simulated case indicate that it was dimensioned for no more than 168 cars, so it gives a final amount of 643€ per taxi per year. This cost analysis does not take into account the financial expenses. Including the system costs, the money saved has still a positive result by the equation (1), were “a” is consumption saving and “b” is the whole system costs: Year result = a – b = 3.030€ – 643€ = 2.387 €

(1)

But then four more points should be considered:  The first one is the car amortization. There are 12000€ difference to be distributed during its life-time. This will be referred as “d” in equation (2)  The car battery is supposed to last 160.000km or 8 years according to car manufacturers or 2000 cycles at most (Cready E, 2003). As detailed at the beginning, the taxis will charge twice per day. After 4 years they’ll have already achieved these two maximums (1.912 cycles and 170.200 km) and the battery should be changed (or the whole car). But it is known that diesel vehicles are able to do more than 300.000km. So that is 20.000€ plus for a new battery. “d” in (2)  The car battery could be sold at the end of its life, that makes something like 1.500€ per battery and 3.000€ after the 8 year comparison analysis. “o” in (2)  There are some incentives from the Spanish government for buying electric cars (RD 648/2011 ), in our case, it is 6.000€ discount. “i” in (2) So, using the equation (2) and knowing that the year result from (1) should be taken each year: Final result = (year result *8) - d – o + s + i

(2)

Final result = (2.387€ *8) – 12.000€ - 20.000€ + 3.000€ + 6.000€ = -3.904€ (2) For this cost analysis, at the end of the 8 years use, both cars are considered as retired.

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4 Conclusions The economical result is obviously negative, having a 3.904€ loss per car at the end of their useful time and a total amount of 655.872 € loss with the 168 car fleet project. It shows that, at the moment and not counting on institutional support for the project it does not seem a suitable business. There are some good points though, which might be interesting in the future to come if new battery prices get lower (as it is expected (Neubauer J.S. et al, 2012)). Indeed, this project can get bigger and bigger if the proportions of cars/stations and batteries are main-tained without individual extra cost. Therefore, it can be started with a small group of vehicles as a pilot project and grow if battery costs decrease or their life expectancy achieves similar characteristics of diesel vehicles. There is still one more positive point that might surely bring some interest in similar projects such as a touristic city fleet for example. If the new project is done comparing the results with gasoline internal combustion vehicles, because there is no need to do so many km per year and the projected endurance is about more than 6 years, the idea of using electric vehicles should really be studied. (Blázquez J, et al, 2010).

5 References Amat C. (2010) Anàlisi de l’eficiència del servei de taxi a barcelona. propostes de millora. Tesis UPC. http://hdl.handle.net/2099.1/9703 Blázquez J, Martín J.M. (2010) El vehículo eléctrico, Eficiencia energética en la automoció el vehículo eléctrico, un reto del presente. Economía Industrial-Vol.377. Pag. 76 – 85. ISSN 0422-2784 Botsford C, Szczepanek A. (2009) Fast Charging vs. Slow Charging: Pros and cons for the New Age of Electric Vehicles. EVS24 International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium. Broussely M. (2007) Industrial application of batteries. From cars to aerospace and energy storage. Chapter 4: Traction batteries. Elsevier B.V. ISBN: 978-0-444-52160-6 DOI:10.1016/B978-044452160-6/50005-X Cicconi P, Landi D, Morbidoni A, et al (2012) Feasibility analysis of second life applications for li-ion cells used in electric powertrain using environmental indicators. 2nd IEEE ENERGYCON Conference & Exhibition / Sustainable Transportation Systems Symposium DOI: 10.1109/EnergyCon.2012.6348293. Cready E, Lippert J, Pihl J, et al (2003) Technical and Economic Feasibility of Applying Used EV Batteries in Stationary Applications. Sandia National Laboratories SAND2002-4084 European Commission Regulation (CE) Nº 443/2009 from the European parliament and council, 23rd April 2009. CO2 emission requirements regulation. Gas natural / Union fenosa & Endesa. Tarifas de electricidad 2013. http://www.gasnaturalfenosa.es/es/inicio/hogar/gas+natural+y+electricidad/1285340342233/t arifas+de+gas+y+luz.html Kley F. (2011) New business models for electric cars—A holistic approach. Energy Policy 39 pages 3392–3403 DOI:10.1016/j.enpol.2011.03.036

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Muñoa J.A. (2009) Las infraestructuras de recarga para el vehículo eléctrico. Revista Ambiente. Neubauer J. S, Pesaran A, Williams B., et al (2012) A Techno-Economic Analysis of PEV Battery Second Use: Repurposed Battery Selling Price and Commercial and Industrial End_User Value. SAE World Congress and Exhibition. DOI:10.4271/2012-01-0349 RD 648/2011 Real decreto: Plan integral de impulso al vehículo eléctrico en España 2010-2014 BOE: http://www.boe.es/boe/dias/2011/05/10/pdfs/BOE-A-2011-8125.pdf Vilayanur V V, and Kintner-Meyer M. (2011). Second Use of Transportation Batteries Maximizing the Value of Batteries for Transportation and Grid Services. Transactions on vehicular technology, vol. 60, Nº.7 DOI: 10.1109/TVT.2011.2160378 Zamora B., Ollé E., Fornos S., et al (2012) El Sector del Taxi. UPF. http://hdl.handle.net/10230/16128. www.taxibarcelona.cat (2013)

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Decision Tool Based on Cloud Computing Technology Zabalza-Vivanco J1, Rio-Belver R2, Cilleruelo E3, Acera-Osa F.J4, Garechana G5 Abstract This article analyzes the design of a decision tool based on cloud technology whose main aim is to present different applications existing in the Software as a Service (SaaS) market and how these applications can help business priority areas meet their challenges. This tool is intended to be a driving force for cloud adoption, above all in Spanish Small and Medium-Sized Enterprises (SMEs).

Keywords: Cloud Computing, Technology Management, Decision Tool, Innovation, SMEs, Spanish SaaS Market

1 Introduction This paper describes the process of making a decision tool based on cloud computing technology. The article consists of five sections. Firstly, a definition of cloud is outlined. Secondly, the current status of cloud in the world related to its economic impact is presented. Thirdly, this section is devoted to the cloud situation with regard to Spanish SMEs describing the main characteristics, benefits, barriers 1

Juncal Zabalza-Vivanco ( e-mail: [email protected]) University of the Basque Country, SP-01006 Vitoria-Gasteiz, calle Nieves Cano 12 2 Rosa Rio-Belver ( e-mail: [email protected]) University of the Basque Country, SP-01006 Vitoria-Gasteiz, calle Nieves Cano 12 3

Ernesto Cilleruelo ( e-mail: [email protected]) University of the Basque Country,SP-48030Bilbao, Almed. Urquijo s/n 4

Francisco Javier Acera-Osa ( e-mail: [email protected]) Tecnalia, Parque Tecnológico de Álava, E-01510 Miñano-Álava, calle Leonardo Da Vinci 11 5 Gaizka Garechana ( e-mail: [email protected]) University of the Basque Country, SP48008 Bilbao, Elkano 21

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and concerns as well as the upcoming trends. Fourthly, the design of the tool itself is characterized. Moreover, the reasons for its creation and its design stages are defined. Finally, the fifth section contains the most important conclusions. Although there is no general definition of cloud computing (Grossman 2009, Voas, Zhang 2009), one of the most used definition is from the National Institute of Standards and Technology (NIST) which states: "cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction" (NIST 2011). In cloud computing IT service providers offer their services grouped into three categories, Infrastructure as a service (IaaS), Platform as a service (PaaS), and Software as a service (SaaS). In addition, there are four deployment models: Private, Community, and Public (Zabalza-Vivanco et al. 2012, Miller, Veiga 2009, Sultan 2010, Talukder, Zimmerman & Prahalad 2010). Globally, it is estimated that in 2014 cloud services will generate revenues of US$ 55,500 million with growth rates close to 30% and a market share of approximately 12% (IDC 2010). In addition, cloud is expected to be the main driving force behind IT sector development and SMEs will be the strategic market. Moreover, it is forecasted that 13.8 million jobs will be created in the 2011-2015 period (IDC 2012). North America is the largest opportunity for SaaS, as well as being the most mature of the regional markets (Gartner 2011). Furthermore, Gartner says that European cloud adoption will lag behind U.S. by at least two years. The main reasons for this statement are European privacy rules, multicountry business processes, a deep euro crisis and a lingering recession (Gartner 2012). The economic impact in Europe and Spain during the 2010-2015 can be translated into: a total economic benefit of roughly €763 billion, the implementation of new business development opportunities for existing companies (€127,000 million), the emergence of new businesses, especially SMEs (€215,000 million), cost savings (€140,000 million) and the creation of 2.3 million jobs (CEBR 2010).

2 Cloud Computing in SMEs in Spain Currently, Spanish SME competitiveness is achieved through enhancing key aspects such as marketing, internationalization, human resources recruitment, financial efficiency, level of technology implementation and so on. So cloud technology seems to be the right way to manage this improvement in competitiveness (ONTSI 2012). For this reason, it is necessary to determine the situation of cloud in Spain. For that purpose, ONTSI has conducted a survey with a sample of 1500 microenterprises and SMEs. The main results are presented below: 138


 Characteristics of deployed cloud computing solutions – 9.8 % of SMEs deploy some kind of cloud solution and 21% of enterprises aware of the existence of cloud admit to using it. However, 54.9 % of enterprises admit having no knowledge about cloud computing. – The most common form of implementation is the private cloud with 59.9%. Secondly, the public cloud accounts for 33.8%. Thirdly, the hybrid cloud reaches 13.9%. Finally, the community cloud stands at only 1.7%. – The preferred service model is IaaS (76.1%) outdoing storage services at 68.5% followed by backup services with 22.4%. With regard to SaaS, over half of SMEs deploy it. Finally, PaaS is the least used with only 18.8%. – 47% of enterprises use the cloud services in a cross-cutting way, instead of deploying them for a particular area. 35% of SMEs have used cloud in sales and merchandising areas (e-commerce, websites, client management solutions, and so on). Whereas 18% use it for production and 12% for finance management.  The significant benefits of using cloud services: time saving (71%), cost savings (63%) and the improvement of enterprise productivity (48%).  The main concerns related to cloud use: data security and confidentiality (55%), the loss of control over the process (26%), acquired dependence on the service provider (21%), problems with regard to availability (18%), and the integrity of the contracted services (17%).  The most important barriers when entering cloud computing: lack of knowledge concerning its benefits (63.1%), budget restrictions (30.5%), high costs with regard to recruitment (24.9%), difficulty of migration (18.2%), responsibility of the provider (17.8%), doubts about availability (14.2%), and dependence on the provider (4.3%). This introduction to cloud technology occurs in different ways and depends largely on company size, for example 100 percent of large companies are forecast to adopt it by 2015 (CB consulting 2012). Moreover, the largest increase occurs in SMEs reaching 69% in 2015, up from 13.9% in 2011 (CB consulting 2011). All experts agree on the fact that SMEs will focus on the public model and the demand will be for SaaS applications (ONTSI 2012).

3 Design of a Decision Tool Based on Cloud Technology It is clear that we can highlight that there is a huge lack of knowledge concerning what cloud computing is as well as its most significant benefits. In particular, 54.9% of microenterprises and SMEs confess to having no knowledge of cloud technology. This circumstance results in a loss of SME competitiveness, contrasted with the fact that this technology model is particularly beneficial for SMEs 139


(Nabil 2011, Kloch, Petersen & Madsen 2011). Furthermore, the lack of knowledge concerning its benefits (63.1%) is stressed as the greatest obstacle to entry into the cloud (ONTSI 2012). However, the largest increase concerning cloud adoption will happen in SMEs reaching 69% in 2015, up from 13.9% in 2011 (CB consulting 2012). For these reasons, a decision tool based on cloud technology has been designed. The main purpose of this tool is to provide the principal existing SaaS applications available on the market, which will help us in the management and enhancement of the most decisive areas within a company. Besides this tool, cloud knowledge in relation to SMEs can be complemented by other information sources specifically geared towards the business world (Marston et al. 2011, Hugos, Hulitzky 2010). Turning to the question of methodology, it is clear that it is the section that describes the objectives of the experiment and the methods which are expected to achieve. Consequently, the methods of data collection should be described. In addition, materials, participants, duration of the investigation and the procedures for its implementation should be included. The methodology used in the research summarized in the following flowchart:

Fig. 1 Methodology

Below we describe in more detail the elaboration phase of the decision tool itself, which can be divided into two distinct stages: the development of the decision tree and its implementation.  Stage one: the elaboration of a decision tree (Quinlan 1986, SPRI 2010) which is a diagram that shows conditions and actions in a sequential fashion. Furthermore, this method allows us to show the relationship between each condition and the set of possible actions associated with it. Moreover, it provides a graphical view to aid the decision making process, indicates the variables that are assessed and what actions should be taken as well as the sequence in which decision-making must be executed. Additionally, decision tree is characterized by only one path that will be followed depending on the variable´s value. In this case, our decision tree is aimed at providing cloud solutions to develop major business strategies particularly for SMEs. To this end, the decision tree is made up of three levels. Firstly, the company type which refers to the num-

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ber of employees and business sector, in addition to the identification of business priority areas which is composed of two different approaches. The former of which, business strategy, consists of the following aspects: – Cost reduction and Time Saving with regard to the current process. – Growth: New Clients and/or New markets – Differentiation: Meeting Customers´ Needs And Developing new products and/or services The latter, relationships, included among which: – – – –

Clients: Better Client Management. Providers: Improve Provider Management. Human Resources: Optimize Human Capital Management. Other Agents: Government and/or banks and financial institutions.

Secondly, these actions must be carried out in order to improve the previous business priority areas. What is more, this stage contains the decision tree conditions which are constituted by three priority stages: high, medium and low preference. Finally, the cloud tools allow SMEs to execute the preceding actions by means of their implementation. As a consequence, the expected benefit is achieved. We would like to stress the fact that a key element of this decision tree was the creation of a collection of cloud tools which is known as documentary database and that consists of a set of 51 SaaS applications that were analyzed and classified (SaaSDirectory 2012). To this end, several cloud applications available in the SaaS market were examined. The result was a set of SaaS applications which are grouped into the subsequent sections: Online Billing, Online Accounting, Personal Management, Project Management, Backup and Storage, Document Management, Content Management System (CMS), Customer Relationship Management (CRM), e-commerce, eMailing Marketing, Social Networking Management, Feeds Management, e-learning, Event Organization, Collaborative Platforms, Web development, Video, Communication, Business Intelligence, Production Management, Warehouse Management, Diagrams, ERP, Quality Management, and Customer Service and Support.  Stage two: the development of the decision tool using the decision tree. The decision tool was implemented by deploying LimeSurvey which is a free, open source online survey application written in PHP based on a MySQL, PostgreSQL or MSSQL database, distributed under the GNU General Public License. Designed for ease of use, it enables users to develop and publish surveys, and collect responses (Schmitz 2012). The surveys include branching (conditions), templates, token control and provide basic statistical analysis in order to process the results. The tool is structured as follows: initially, the size and sector of the company will be indicated. Then the company will have to 141


identify those areas which have high, medium or low priority in order to improve the company situation. In the next step, some recommended actions will be shown which will improve those areas that have been designated in the previous step. Finally, SaaS applications which allow the company to implement these actions will be suggested. The following images show the whole process graphically:

Fig. 2 Company size and sector, and the identification of priority areas

Fig. 3 Recommended actions to enhance priority areas

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Fig. 4 The set of SaaS applications in order to implement the recommended actions

The resulting benefit of accomplishing this decision tool by SMEs relies on the fact that companies obtain as a result, a number of cloud solutions or tools that will enable them to improve their priority areas indicated in the initial phase. As a consequence, by means of this set of cloud solutions, which fit the needs of each company, SMEs can reduce costs, improve the management of their customers, suppliers, employees and other agents such as the Administration and banks. Besides being an aid for growth toward new markets as well as enhancing the task of creating new products or services. Note that on the final screen the fundamental features of each cloud tool is shown. In addition, if you click on any tool´s name, you may be directed to its provider web page.

4 Conclusions In Spain the rapid expansion of cloud will occur in the near future. Furthermore, SMEs will be a strategic market for Cloud Service Providers. Although, it could be argued that this is now a reality, it is also a fact that a large number of SMEs are not yet aware of either the existence of cloud technology or its benefits for the business sector. Therefore, it is necessary to implement mechanism to overcome these problems which can be considered as impediments for cloud adoption. Consequently, a decision tool based on cloud computing has been created , the main objective of which is to show the different SaaS applications available on the market and how these applications can enhance and manage the business priority areas. It is clear that SaaS applications are deployed in a cross-cutting manner in the whole company rather than in particular areas. Moreover, we can emphasize commercial and sales areas along with others such as productive aspects, finance management, quality, human resources and innovation. On the other hand, the Spanish SaaS market is still in its infancy, particularly in comparison with American one. Furthermore, there is a reduced service catalog which is ill-adapted to solving specific business areas of the company. It is also a 143


fact that there are many bogus solutions within the cloud concept which create confusion in the market. It is important to remember that SaaS service offerings do not usually mention the migration process which they should be taken into account because of the difficulty. Thus it must be analyzed carefully. We can conclude by saying that cloud computing is especially beneficial for startup companies, SMEs, entrepreneurs and companies that need to make new investments or do not have a stable infrastructure. For these companies this technology leads to a significant saving, in addition to increasing flexibility and competitiveness.

5 References CB Consulting (2012). Cloud Computing y Virtualización en España 2012 – 2015. CB Consulting (2011). Informe sobre la situación del cloud computing en España. CEBR (2010). the cloud dividend: Part One the economic benefits of cloud computing to business en the wider EMEA economy France, Germany, Italy, Spain and the UK. Available via DIALOG. http://uk.emc.com/collateral/microsites/2010/cloud-dividend/cloud-dividendreport.pdf. Gartner (2011). Forecast: Software as a Service, All Regions, 2010-2015. Gartner (2012). Gartner Says Worldwide Software-as-a-Service Revenue to Reach $14.5 Billion in 2012. Available via DIALOG. http://www.gartner.com/newsroom/id/1963815. Grossman R (2009). The case for cloud computing. IT Professional, 11(2):23–27 Hugos MH, Hulitzky D (2010). Business in the Cloud: What Every Business Needs to Know About Cloud Computing. John Wiley & Sons, Inc. ISBN: 978-0-470-61623-9 IDC (2012). White paper: Cloud Computing's Role in Job Creation. IDC (2010). Worldwide and Regional Public IT Cloud Services 2010-2014 Forecast. Kloch C, Petersen E & Madsen O (2011). Cloud based infrastructure, the new business possibilities and barriers. Wireless Personal Communications, 58(1):17-30. doi:10.1007/s11277-0110286-7 Marston S, Li Z, Bandyopadhyay S et al (2011). Cloud computing - the business perspective. Decision Support Systems, 51(1):176-189. doi:10.1016/j.dss.2010.12.006 Miller H, Veiga GJ (2009). Cloud computing: Will commodity services benefit user long term?, IT Professional, 11 (6):57–59. Nabil AS (2011). Reaching for the “cloud”: How SMEs can manage. International Journal of Information Management, 31(3): 272-278. doi:10.1016/j.ijinfomgt.2010.08.001 NIST (2011). The NIST Definition of Cloud Computing. Available via DIALOG. http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf. . ONTSI (2012). Cloud Computing Retos y Oportunidades. Available via DIALOG. http://www.ontsi.red.es/ontsi/sites/default/files/1_estudio_cloud_computing_retos_y_oportunidades_vdef.pdf. Quinlan JR (1986). Induction of decision trees. Machine Learning, 1(1):81-106. doi: 10.1007/BF00116251 SaaSDirectory. Online Software and Applications. Available via DIALOG. http://www.saasdirectory.com/. Accessed 2 Jan 2013. Schmitz C (2012). LimeSurvey Project Hamburg, Germany. Available via DIALOG. http://www.limesurvey.org.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. SPRI (2010). Guía de Autodiagnóstico para Pymes en la utilización de las TICs. Available via DIALOG.http://www.emprender-enargon.es/medias/pdf/guia_de_autodiagnostico_para_pymes_en_la_utilizacion_de_las_tics.pdf Sultan N (2010). Cloud computing for education: A new dawn? International Journal of Information Management, 30(2):109–116 Talukder AK, Zimmerman L & Prahalad HA (2010). Cloud economics: Principles, costs, and benefits. In N. Antonopoulos, & L. Gillam (Eds.), Cloud computing (343-360) Springer London. doi:10.1007/978-1-84996-241-4_20 Voas J, Zhang J (2009). Cloud computing: New wine or just a new bottle?. IT Professional, 11(2):15–17 Zabalza-Vivanco J, Rio-Belver R, Cilleruelo E et al (2012). Benefits Related to Cloud Computing in the SMEs. Paper presented at the 6th International Conference on Industrial Engineering and Industrial Management XVI Congreso de Ingeniería de Organización.

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Productivity in Knowledge Worker Teams Moreno A1, Varanki H, Mahou A. Abstract The use of Information and Communication Technologies in work processes has not brought the expected productivity improvement. Some studies even suggest that the always-on model decreases productivity. This article proposes work teams as a new unit for knowledge worker productivity analysis in organizations. Organizations’ ability to adopt new analysis measures is analyzed in three case studies.

Keywords: Knowledge Worker, Productivity, Team, Commitment

1 Knowledge Worker Productivity Since Taylor's Principles of Scientific Management in 1911 (Taylor, 1911), organizational theory has provided a systematic review of the methods that can be used to arrange work activities. These methods have come to include psychological processes, social changes and technological changes such as the rise of the networked organization. As a discipline, the purpose of the organizational theory is to improve the efficient utilization of resources and establish performance standards regarding work activities. In fact, as the knowledge society has progressed the need for the standardization of the work processes and resources has increased. The traditional way of measuring productivity is based on the relationship between the input and the output, but when analyzing productivity of the knowledge worker the main problem appears to be the difficulty of identifying what is the output. It is impossible to create a standard way of measuring knowledge workers' activities due to their highly specialized and specific task environment. Besides, part of the knowledge workers' output is usually intangible which makes measuring these activities even more difficult. (Mintzberg, 1989)

1

Ana Moreno ( e-mail: [email protected]) Professor at the Department of Organization, Business Administration and Statistics at the School of Industrial Engineering in the Technical University of Madrid.

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As early as in 1999 Peter Drucker (Drucker, 1999) referred to knowledge workers' productivity as the great challenge of this century, identifying it as the true competitive advantage in a global economy. "The main economic priority of the developed countries is to raise the productivity of intellectual work and work in the service sector". In the new development model that Castells (Castells, 1998) denominates "informational", the source of the productivity lies in the technology for knowledge generation as well as for information processing and communicating the knowledge. In this environment the main problems for controlling the productivity are the information overload and the difficulties to remain focused (Drucker, 1999). On the other hand, the key to an effective management in knowledge networks might be a balance between free access and defined procedures or even more rigid workflows that limit workers' alternatives (Davenport, 2011). Teamwork and the interdependence between workers have increased enormously in the last decade, but, nevertheless, performance measurements are still done on an individual basis. Companies still calculate organizational productivity through economic data, industry ratios, through top management's goals and with individual performance measures. This article suggests that the team should become the unit for analysis, as the team can be seen as the link between the individual and organizational frameworks.

2 Model for Knowledge Team Analysis Traditionally the study of work has been centered on individual workers. The Human Resources management measures knowledge worker's individual productivity with different variables such as commitment and competencies. (Gil et al., 2008; Blumberg & Pringue, 1982 and Vroom, 1965) Commitment is one of the most widely used concepts regarding the management of knowledge workers. According to Mathieu and Zajac (1990), it is defined as the bond that an individual worker develops towards the organization and its members. Furthermore, the evolution of organizational structure and workflow theories result in a model for competence based management. Competencies can be defined as "parts of the underlying characteristics that lead individual to achieve a higher or more effective performance" (Boyatzis, 1982). However, the ever increasing complexity of the environment forces companies to find new ways of staying competitive. One response to these changes has been the use of teams in order to solve complex problems the difficulties of which exceed a worker's individual capacity, when the work environment is unclear, ambiguous or stressful, when quick and repeated decisions are required or when the decision-making requires a more collective vision and approach. (Salas et al., 147


2008 a) Therefore, the need to change the unit for analysis regarding the productivity measurements arises, and the knowledge team productivity must be considered as the base unit. A change in the mindset in organizations is required in order to understand that now it is important to measure the activities and tasks that contribute to the common goals and strategies, and realize that knowledge workers work with each other in an interdependent way and for that reason it is practically impossible to distinguish the contribution of each of them (Moreno, 2009). Furthermore, teams respond better to the new needs of the environment because they are ubiquitous and provide diversity in knowledge, skills and experiences (Salas et al., 2008 b). In order to understand and analyze how teams work, it is necessary to understand the context in which they are and take into consideration the diversity and skills of the individuals that belong to the team. According to Kozlowski and Ilgen (2006), teams are part of a multilevel system that consists of individual, team and organizational levels. Teams consist of individuals who possess different characteristics and behaviors. Then, the interaction between the team members creates new characteristics and behaviors typical of that team. On the other hand, teams and the team members belong to a wider context that is the organization. (Kozlowski & Bell, 2003) The organization sets the boundaries and marks the pace for teamwork and includes the difficulties and complexity that affects it (Kozlowski & Ilgen, 2006). Teams combine the factors affecting workers' individual productivity as well as the opportunities and the restrictions determined by the organizational resources. Therefore, teams can't be analyzed or studied in isolation. The individual influences affecting teamwork and the influences and rules set by the organizational environment must be considered. However, most of the studies on teamwork don't consider these multilevel aspects (Kozlowski & Bell, 2003).

3 Purpose and Methodology The purpose of this study is to analyze the productivity in teams in which most of the workers fit the profile of the knowledge worker. There is no unique model for studying the productivity of knowledge worker teams, so we propose a set of factors identified as relevant in the literature. Figure 1 gathers these factors.

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Fig. 1 The multilevel structure in organizations.

These factors have been selected taking into consideration the factors identified in literature as well as the indicators most commonly used in Human Resources policies and management. In order to study the impact of these factors for the team productivity, three case studies have been developed. The case studies analyze the information available at the organization for evaluating the factors, the utility of the resources at a group and individual worker levels as well as practices and tools used to improve the productivity. The following tables display the study results and present the model, which standardizes the mentioned factors. The expected outcome of this theoretical analysis and case study is the definition of a model for analyzing the productivity in knowledge worker teams. The model should include the identified key factors and allow a possible quantification of the factors in the future.

4 Case Studies The cases were chosen to cover different knowledge worker profiles, from those who work in consultancy projects and are therefore used to control their working hours since they are used as a billing unit, to those who have mainly procedural tasks close to industrial processes but with a significant knowledge work component. The chosen case studies include a small Spanish consultancy company dedicated to organizational management and two large companies from the Spanish energy sector. In one of the electrical companies the study was made in a group belonging to the human resources department and in the other company the study took place at the engineering project implementation department. This choice of case studies has two criteria: first, the workers in the chosen teams have to be 149


knowledge workers, and second, the organizations needs to be varied in order to be able to study different situations in terms of the organizational resources available in each company. Information available about the organization, teams to be studied and their members' activities and tasks were used in the study. The analyzed factors are: organizational resources for management by objectives (MBO), functional group analysis, competencies, commitment and the leadership style. The study results and the analyses are shown in the following tables. Table 1 Analysis of the case A. Description of the organization

Company A is a SME with 35 workers dedicated to organizational consultancy projects. The consultants’ profile fits the knowledge worker profile 100% with a high degree of flexibility.

Description of pilot case

The pilot case was developed to evaluate the usefulness of the consultant’s project control system in which 9 professionals took part. The project was developed under the leadership of the company’s partners.

Organizational resources for MBO

Management by objectives system 100% focused on quantitative data: billing, project profitability and future projects portfolio. No Human Resources department involved.

Functional group analysis

An internal project planning and control system. Computes consultants’ working hours.

Competencies

System for competence management doesn't exist.

Commitment

Company A’s culture is very participatory and supportive but there is no climate survey.

Leadership style

The leadership style varies depending on which partner is in charge of the department. Culture of support is created with mutually agreed adjustment mechanisms.

Productivity

Performance is measured through the financial profitability of the projects. This system, knowing the consultants working on each project and in each department, produces reasonably good estimate of the performance of each employee. The system is based on controlling the consultants’ working hours.

Table 2 Analysis of the case B. Description of the organization

Company B is from the energy sector with over 1,500 employees. It has implemented a management by objectives system, competence management system, their internal processes are defined according to EFQM standards, they have top level information and knowledge management systems, and they are at the leading edge of the corporate social responsibility policies.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 2 (continued) Analysis of the case B. Description of pilot case

The Human Resources Department has a program oriented to professional development in the organization. Five members of this department took part in the pilot case with the purpose of helping to improve the unit's productivity. The project was developed under the leadership of the department manager.


They have an MBO system with annual evaluation.

Functional group analysis

Functional-person analysis has been implemented on the manager's initiative. However, the sum of all individual objectives reached does not give clear information on group productivity.

Competencies

They have a competence management system, which includes individual competence profiles.

Commitment

Climate surveys are done but they don't provide information on individual or group commitment.

Leadership style

The company’s management style is highly project-oriented with traditional hierarchical relationships.

Productivity

Workers’ performance is measured through individual objectives. The company possesses powerful organizational resources and it could, therefore, be supposed that the productivity equation has all the information for all of its components. However, the workers had the feeling they were overloaded but the department manager did not have any specific tools to address this problem or to measure team productivity and distinguish between the individual productivities.

Table 3 Analysis of the case C. Description of the organization

Company C is a multinational in the energy sector with over 30.000 employees. It has implemented a management by objectives system, a competence management system, their processes follow the EFQM standards, they have information and knowledge management systems and they have highly developed CSR policies.

Description of pilot case

The pilot case was carried out in a department for infrastructure implementation with 54 workers, 9 of whom participated in the study. The project's purpose was to analyze the sizing of the human work force for the needs of the department's project. They also needed to adapt to a new work process management platform, and they also wanted to test whether the perceived work overload was due to erroneous calculations in the job sizing.


They have an MBO system with annual evaluations.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 (continued) Analysis of the case C. Functional group analysis

The department has five systems, which provide a detailed flow of all the work activities under the study. The homogeneity of the activities enabled to analyze the fulfillment of the team goals.

Competencies

They have a competence management system linked to a very detailed job descriptions and an internal job profile control system.

Commitment

No information available.

Leadership style

The company’s management style is highly oriented to engineering projects with traditional hierarchical relationships and a high degree of delegation at middle management levels.

Productivity

The data obtained from the personnel time estimate and control form has provided useful information to the organization. However, its usefulness for the workers is limited by the fact that their jobs are oriented to very standard procedures. Worker performance is measured through individual objectives. The workflow tools limit any risks of deviation of the tasks and the periodic job sizing helps to identify the existing time thieves.

The case studies show how companies measure productivity on an individual basis rather than taking into account the work teams and their outputs. However, especially the large corporations have means, such as information systems and procedures, for team based analysis. Finally, the leadership style is decisive in evaluating and implementing new approaches.

5 Conclusions The study is based on cases of companies that are concerned about the productivity of their teams and want to improve their existing tools and processes to enhance the team productivity. The model used in the study has allowed analyzing the subject from a different perspective, and it also has pointed out the importance for studying productivity from a multilevel point of view (individual, team, organization). How workers use the resources and take advantage of the processes that the organization offers, as well as the role of the team leader in the "administration" of these resources is the key to understanding the productivity. It is also manifested that in the team the clarity of the goals and purpose, commitment and analysis of competencies are key variables due to their impact on the individual and team productivity. 152


Despite the recourses and tools the organizations have to improve the productivity in the multilevel structure, companies don't have productivity measures for teams and they rely on individual performance measurement as well as on the company's overall productivity measurement. This study highlights the importance of the team productivity as one of the key variables for productivity analysis since it considers the individual factor and also the organizational factor. The future research on this topic should include a more detailed study of the multilevel structure in organizations in terms of productivity and identify the interrelationships of the factors at these levels.

6 References Boyatzis RE (1982) The competent manager: A model for effective performance. NewYork: John Wiley & Sons. Blumberg M, Pringue C (1982) The missing opportunity in organizational research: some implications for a theory of work performance. Academy of Management Review, 7-4: 560-569 Castells, M. (1998) La era de la información. Economía sociedad y cultura, 3. Fin del Milenio, Alianza Editorial, Madrid Davenport T (2011) Rethinking knowledge work: A strategic approach. McKinsey Quaterly, February 2011 Drucker P (1999) Management Challenges for the 21st Century. Butterworth-Heinemann, Oxford Gil F, Rico R, Sánchez-Manzanares M (2008) Eficacia de los equipos de trabajo. Papeles del Psicólogo, 29, 1: 25-31 Kozlowski S, Bell B (2003) Work Groups and Teams in Organizations. Handbook of Psychology, 12: Industrial and Organizational Psychology: 333-375 Kozlowski, B.; Ilgen, D. (2006) Enhancing the Effectiveness of Work Groups and Teams. Psychological Science in the Public Interest, 7, 3: 77-124 Mathieu J, Zajac D (1990) A review and meta-analysis of the antecedents, correlates, and consequences of organizational commitment. Psychological Bulletin, 108, 2: 171-194 Mintzberg H (1989) Mintzberg on Management: Inside Our Strange World of Organizations, The Free Press, New York, NY, 1989. ISBN 0-02-921371-1 Moreno A (2009) Adaptación a las nuevas tecnologías organizativas del trabajo en enthrones de red. Telos: Cuadernos de comunicación e Innovación, 81, ISSN: 0213-084X Salas E, Cooke NJ, Rosen MA (2008 a) On Teams, Teamwork, and Team Performance: Discoveries and Developments. Human Factors: The Journal of the Human Factors and Ergonomics Society, 50, 3: 540-547 Salas E, DiazGranados D, Klein C, Burke S, Stagl KC, Goodwin GF, Halpin SM (2008 b) Does Team Training Improve Team Performance? A Meta-Analysis. Human Factors: The Journal of the Human Factors and Ergonomics Society, 50, 6: 903-933 Taylor F (1911) Principles of scientific management Vroom VH (1965) Motivation in Management. New York, American Foundation for Management Research

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Return of Equity Issues in the Spanish Stock Market from the Investor’s Perspective, during the 1997-2012 Period Parreño J1, Ruiz F2, Roux F3 Abstract Is it profitable for an investor, from a risk-return perspective, to acquire a stake in a quoted company when a capital increase is announced? This paper analyses the return obtained from the investment in equity issues with cash contribution and pre-emptive rights, aimed at funding corporate activities: acquisitions, investments in new facilities and/or strengthening the balance sheet of the companies undertaking the equity issue. During the 16 years covered by the study, the results show a negative average excess risk-adjusted return of almost 5%, from the moment that the equity offer is announced until the completion of the preferential subscription period. To obtain this excess return, the difference between the nominal Internal Rate of Return (IRR) and the expected return, using the CAPM, is computed for each equity issue. The intention behind this method is to eliminate the effects of time and any other possible effect on the stock price during the period of the analysis. The results from this article are consistent with the Pecking Order theory for the Spanish Stock Market also six months after the preferential subscription period. However, there is a positive return after three months.

Keywords: Equity Issues Returns Pecking Order

1

Javier Parreño ( e-mail: [email protected]) Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid. José Gutiérrez Abascal, 2, 28006. Madrid. España 2

Felipe Ruiz ( e-mail: [email protected]) Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid. José Gutiérrez Abascal, 2, 28006. Madrid. España 3Félix

Roux ( e-mail: [email protected]) Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid. José Gutiérrez Abascal, 2, 28006. Madrid. España

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1 Capital Structure and the Pecking Order Theory The theory of capital structure has been widely studied by researchers and professionals, since it corresponds to one of the key financial decisions from the point of view of both academics and practitioners. The modern starting point of this theory was Modigliani and Miller’s 1958 paper which stated that, in perfect markets, financing decisions with either external or internal resources are irrelevant to the market value of companies. From this starting point, additional hypotheses to make the model more realistic (influence of taxes, market behaviour, etc.) have been included, resulting in more complete and explanatory theories to explain the financial preferences of companies. The Pecking Order theory of financing choices was originated some 25 years ago by Myers (1977), Myers (1984) and Myers & Majluf (1984), who stated that companies’ funding preferences are as follows: (i) firms prefer internal financing, (ii) they adjust their dividend policies to their investment opportunities; (iii) when external finance is required, they start with debt, followed by convertible securities and, as a last resort, using equity issues. The rationale for the Pecking Order goes as follows: (a) the investor knows that the management of the company’s information is superior to her/his; (b) the investor also knows that the management can time the equity issue so that it does not take place when the stock price, according to the management’s superior information, is undervalued; (c) therefore, the investor knows that when the management proposes the equity issue, the price of the stock must be either right or overvalued; and (d) a rational investor should then sell her/his shares at the issue price, the consequence being a drop in the price of the shares when the issue is announced.

2 Financing Companies in the Spanish Stock Market through Equity Issues with Cash Contribution and Pre-emptive Rights This study provides new evidence of the Pecking Order theory within the Spanish market. Numerous previous works have shown the hierarchy of financing resources through different methodologies like, without claiming to be exhaustive: Fernández, de Rojas and Zuliani (2004), Pastor-Llorca, M.J. and Poveda, F. (2004), Sánchez-Vidal and Martín Ugedo (2004) and Aybar, Casino and López Gracia (2001). As explained by Sánchez-Vidal and Martín-Ugedo (2004), Myers and Majluf (1984) analyses the North American stock market, where quoted companies mainly make equity issues on a firm basis, so they usually restrict pre-emptive rights for existing shareholders. In the Spanish stock market, equity issues with monetary contributions in which companies restrict pre-emptive rights are made when 155


an investor or an organized block of investors want to acquire a stake in the company, but this doesn’t mean that the company is seeking funding for expansion. The only type of equity issues whose aim is always funding corporate growth using the Spanish stock market are those with cash contribution and pre-emptive subscription. As a consequence, it seems reasonable to analyse for the Spanish market the return obtained by investors in this type of equity issue as a method of confirming the potential negative impact of this corporate funding criteria, guided by all the papers mentioned before and also in the paper published by Asquith and Mullins (1986), which investigated the effect on stock prices of equity offerings on the NY Stock Exchange. To summarize, there are several major practical reasons for the analysis of this type of equity issues: (i) the objective corporate purpose of the equity issue, (ii) The ability of the entire investor community to subscribe the equity issue (both institutional and domestic investors), (iii) greater systematic follow-up by the stock exchange commission (CNMV), (iv) longer periods to subscribe the equity issue, and therefore to analyse it and (v) the possibility of avoiding shareholder dilution.

3 Methodology The universe of equity issues analysed meet the following criteria: All companies are quoted in the Madrid Stock Exchange Market when the equity issue is made. Initial Public Offerings (IPOs) have not been considered. The period of analysis is 16 years starting from the beginning of 1997. This period involves two cycles of expansion and contraction of the Spanish economy. There is a monetary contribution in every equity issue considered. The Board of the Company recognises the pre-emptive rights of the existing shareholders. The capital increases are registered in the Spanish Stock Market Commission (CNMV). The methodology used to obtain the investors’ return follows three steps:  Internal Rate of Return of the equity issue ‘n’ (IRRn) is the IRR obtained by that investor who, once they know of the intention of the company to proceed with an equity issue, finally decides to invest in it. The stock price information has been obtained from Bloomberg. In this sense, it is important to mention that theoretical value of rights has been adjusted by Bloomberg in the stock price history once the pre-emptive subscription period is completed. IRR has been calculated for three different short term periods: (i) once the pre-emptive subscription period is finished, (ii) three months, and (iii) six months after the 156


forementioned period has finished. The main issue in calculating the IRR is the date of the first day the investor decides to acquire shares. The day when enough information about the equity issue is published in CNMV has been designated t=0. Usually, most of the information has been given when the Board of the Company announces the total amount of the equity issue (nominal + premium issue). The next step would be to schedule a General Meeting of the Shareholders in order to approve the equity issue and to delegate to the Board the faculty to carry out the issue. During the analysis of the return obtained by the investor, all dividends earned by the shareholder have also been considered as dividend cash flow. i

0 = O0

 j1

Si

Dj (1  IRR)

( tj  t 0 ) 365

(1  IRR)

( ti  t 0 ) 365

(1.1)

Where: O0: Outflow. Disbursement for the investor (t=0) Dj: Dividend received by the investor on the day j Si: Inflow. Sale of the investment on the day i  Expected return of the equity issue ‘n’ (ERn) that the investor should have obtained in each equity issue. It is calculated during the same period of time as the calculated IRRn. The expected return has been calculated with the “Capital Asset Pricing Model” CAPM method (Campbell and Viceira, 2002). The risk-free rates of return considered are three months and six months interest rates of the Spanish public debt, depending on the period analysed. The market premium has been calculated considering the difference between the real rate of return of IBEX with dividends Index (Bloomberg ticker: IBEX35TR) and the risk-free rate of return.  Excess risk-return of the equity issue ‘n’ (ERRn): it is obtained as the difference between the IRR and the expected return. ERRn = IRRn - ERn

(1.2)

By extracting the expected return from the IRR, the effect of time or any other possible effect on the stock price during the period is eliminated. The universe of stocks combined for this study implies 132 out of 137 (96%) of the total equity issues with cash contribution and pre-emptive right made by 68 companies. According to the sector breakdown provided by the Spanish Stock Exchange (Bolsas y Mercados Españoles, S.A.), 27% of the equity issues analyzed comes from companies within the financial services and real estate sector, 24% 157


basic materials, industry and construction, 21% consumer goods, 14% technology and telecommunications, 8% oil and energy and 8% consumer services. 14

13

12

12

12

10

10

10

8

10

8

8

8

7

7

7 6

6

6

5 4

3 2

0 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Financial services & Real Estate

Basic materials, industry and construction

Oil & Energy

Consumer goods

Consumer services

Technology & Telecommunications

Fig. 1 Equity issues per year considered by the analysis by sector

An average of 8 equity issues per year have been fully subscribed; 2001 was the year with the fewest equity issues (3) and in 2009 13 companies issued new shares. In terms of nominal and total value, equity issues fully subscribed during 2010 represented 25% and 20% respectively of the total universe analyzed. On the other side, 2001 was the least active year, representing less than 1% of the total analysis. The most active years in terms of corporate financing through these types of equity issues correspond with the most restrictive period on financing held by financial institutions (2008-2012).

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8,474,158 In Euros 000's

7,415,957

5,787,239

3,996,841 3,676,536

2,700,071

2,642,573

2,543,125

2,280,423 1,744,897 1,429,068

388,929

309,819

172,199

1997

40,916 1998

1999

2000

2001

2002

311,766 2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Fig. 2 Total value (nominal + premium) of the equity issues analysed

4 Results Obtained Those investors who have decided to buy shares in a company at the time that it makes public its intention to issue equity in the market have obtained, on average, a negative excess return, both at the end of the preferential subscription period and six months after in terms of the mean and the median. However, the mean after three months shows a positive return. When calculating the median value of the excess returns, one can observe a negative figure for all periods. 15% 10%

11.50%

5% 0% -0.52% -5% -4.93% -10% -9.61%

-10.71%

-15% -20% -25% -30%

-26.52% Just ended the preferential subscription period

3 months after Average

6 months after Median

Fig. 3 Average and median excess returns (ERRn) of the equity issues analysed (for those equity issues made during the second semester of 2012, only the first period has been taken into account)

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If made a grouping of stocks according to their betas, the following average excess returns shown in fig.4 are obtained: 100%

80%

75% 60% 45% 40% 32%

29% 14%

20% 19%

-20%

-40%

15%

13% -5%

0%

-2% -3% -4%

-9%

-18% -19% -32% -32%

-31%

Just ended the preferential subscription period 0.1 < Beta ≤ 0.5

0.5 < Beta ≤ 0.75

3 months after 0.75 < Beta ≤ 0.9

6 months after 0.9 < Beta ≤ 1

1 < Beta ≤ 1.25

Beta>1.25

Fig. 4 Average excess returns (ERRn) according to different groups of betas

Those companies whose betas are between 0.75 and 0.9 higher than 1.25 obtain an average positive excess return. If a grouping of stocks according to the total amount funded in the stock exchange market (nominal + premium) is made, the following results shown below are obtained. 120%

100%

102%

80% 60% 40%

53%

47%

20% 0% -20% -40%

29%

19%

2%

5% -4% -5% -6%

1% -26% -28% -29% -38%

-13%

-21%

-60% Just ended the preferential subscription period

3 months after

6 months after

0 < Amount ≤ €20.000.000

€20.000.000 < Amount ≤ €35.000.000

€35.000.000 < Amount ≤ €90.000.000

€90.000.000 < Amount ≤ €150.000.000

€150.000.000 < Amount ≤ €250.000.000

Amount > €250.000.000

Fig. 5 Average excess returns (ERRn) according to the amount funded in the equity issues

Neither the total amount of the equity issue nor beta affect the excess return obtained. There is no proven correlation between these two parameters and the excess returns obtained.

160


4.1 Industry Split As shown in figure 6, one can observe the main differences between industry weights in terms of average excess returns during the study period: Basic materials, manufacturing and construction is the only sector that has a positive average excess return from the moment that the equity issue is announced until its completion. 100% 88% 80% 55%

60% 40%

16%

20%

10% 2% 0% -1% -12% -23%

9% -11%

0% -21%

-20%

-11%

-23% -40%

-29%

-39% -52%

-60%

-67%

-80%

Just ended the preferential subscription period Financial services & Real Estate

Basic materials, industry and construction

3 months after

Oil & Energy

6 months after

Consumer goods

Consumer services

Technology & Telecommunications

Fig. 6 Average excess returns (ERRn) according to sector

5 Conclusions The results of this study demonstrate that the announcement of equity issues in the Spanish stock exchange market destined for corporate growth provides a negative excess return for those investors who decide to subscribe them from the moment they are announced. The average excess return obtained by these investors is -5% and is statistically significant. Other significant results from this study include: (i) There is no relationship between betas and size of the equity issue and the return obtained for each offering; (ii) according to the sector breakdown made by the Spanish stock market, the consumer services sector is the most unprofitable sector for investors and the basic materials, industry and construction sector is the only profitable sector.

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6 References Asquith, P. and Mullins, D.W. Jr. (1985) Equity issues and offering dilution. Journal of financial economics. Harvard University, USA Brealey, R.A., Myers, S.C. and Allen, F. (2011) Principles of Corporate Finance. 10th edition. McGraw-Hill Campbell, J.Y. and Viceira, L.M. (2002) Strategic Asset Allocation: Portfolio Choice for Long Term Investors. Clarendon Lectures in Economics Fama, E.F., and French K.R. (2005) Financing decisions: Who issues stock? Journal of Financial Economics, 76(3), pp. 549 Fernández Ramos, M.Y., de Rojas, M.C. and Zuliani, G.D. (2004) Verification of the Pecking Order Theory: the case of the Spanish companies. Finance and accounting department, University of Valladolid, Spain Moreira da Silva, C.A. and Rodríguez Sanz, J.A. (2006) Contrast Pecking Order vs. Trade-off Theory for a sample of Portuguese companies. Faculty of Economics and Business, University of Salamanca, Spain Myers, S.C. and Majluf, N.S. (1984) Corporate financing and investment decisions when firms have information that investors do not have, Journal of Financial Economics 13, 187-222 Pastor-Llorca, M.J. and Poveda, F. (2004) Capital increases in Spain: an empirical study of equity issues rights. Department of Finance, Accounting and Marketing, University of Alicante, Spain Sánchez-Vidal, J. and Martín-Ugedo, J.F. (2004) Financing Preferences of Spanish firms: New evidence for the Theory of Hierarchy. Economics Analysis Working Papers, Vol.3, Nº 8. Spain

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Sustainable Balanced Scorecard: Practical Application to a Services Company Redondo A1, Pascual J.A2, Gento A3, Muñoz J4 Abstract We have developed, in partnership with a consulting firm, a tool that provides two basic goals: 1) The integration of the planning of Social Responsibility (CSR) with the strategic and operational planning of the company (BSC), in our case based on a patented management model with 7+1 levels, and 2) Monitoring the management of the CSR according to the activity carried out by the organization. This has allowed us to evaluate/test the quality and adaptability of the developed tool, identifying their strengths and weaknesses, areas for improvement and future lines of research or work.

Keywords: Balanced Scorecard (BSC), Corporate Social Responsibility (CSR), Strategy, Management.

1 Project Justification Many are the changes that organizations are experiencing at the strategic and tactical levels of management, whether those companies are public/private,

1Alfonso

Redondo Castán ( e-mail: [email protected]) Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce 59, 47011 Valladolid. 2José

Antonio Pascual Ruano ( e-mail: [email protected]) Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce 59, 47011 Valladolid. 3Angel

Manuel Gento Municio ( e-mail: [email protected]) Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce, 59, 47011 Valladolid. 4Javier

Muñoz Sanz ( e-mail: [email protected]) Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce, 59, 47011 Valladolid.

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large/small, goods/services, etc.. And many organizations are questioning whether it even makes sense to talk about Corporate Social Responsibility (CSR), or whether, by contrast it should be another of their business pillars. In this line, the crisis (economic/social/values/etc ...) presents an opportunity for businesses. Our society highlights the need to build a more sustainable and responsible socioeconomic model, aligned with the concepts and vision pursued by CSR: economic models which integrate business development and societal concerns, searching for a balance between renovation and irresponsible consumption of finite natural resources, aligning the interests of all "stakeholders" towards an integral and supportive CSR, etc. By integrating this all, we will achieve a CSR that becomes a competitive element within the business framework, and that is able to generate greater profits for a company. In this context, two years ago, a service company suggested us to collaborate in developing a model that would allow the integration of the classical Balanced Scorecard (BSC) with CSR: Responsible Scorecard. This project aims to know the impact and the level of implementation and control of an existing CSR, through the development of a tool that allows to strategically manage all CSR indicators.

2 Scope and Planning According to the objectives stated on the abstract, the project was divided into three phases:  First, we had to analyze the strategic management model implemented in the company (7 +1 levels), emphasizing the identification of the most relevant indicators.  Later, taking as starting point a work by Muñumer, H (2011) which we had previously directed, we set in context CSR in firms, from the strategic point of view, and considering the intended development of a sustainable management tool.  After the previous stages, we proceeded to develop and implement the sustainable management tool, characterized, strategically and from the point of view of CSR, by the business management of the Consulting firm. In this article we will focus on the latter stage, since it constitutes the central and practical core of the developed work.

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3 Development and Implementation of Sustainable Balanced Scorecard The design / development of the theoretical model, as a previous step before its application in the consulting firm, was carried out in three phases that we summarize below:

3.1 Phase I: Diagnostic This is a critical and laborious phase, which consists in analyzing and measuring the level of involvement, both for each of the dimensions of the CSR of the company, as well as for the indicators of each of the strategic perspectives (CMI) of the company. In order to carry out an internal scanning, the following steps were performed:

3.1.1 Classification of CSR Indicators Aligned with the Strategic Perspectives In Fig.1 we can see the classification of CSR indicators aligned with the strategic perspectives of the company.

Fig. 1 Classification of CSR indicators in strategic perspectives.

3.1.2 Diagnostic/Analysis of the State of the Indicators of the Company The analysis/screening was performed based on a set of templates specifically developed for that purpose, involving a huge amount of hours and meetings. This check / data capture allows us to know the level of commitment and the implementation status that each company may have with relation to its CSR, both in 165


dimensions as well as in prospects. Fig. 2, 3, and 4 shows, in "white": those indicators that do not apply to the company; in "gray": those indicators that apply and cannot be measured; and in "purple": those indicators that are currently applied and measured.

Fig. 2 Analysis of the state of the CSR indicators in the company.

Fig. 3 General diagnostic of the CSR indicators by strategic perspectives.

Fig. 4 General diagnostic of the indicators by CSR dimension.

3.1.3 Identification of Critical Indicators The preceding step is enriching, but unapproachable as a whole, so it is necessary to make a selection of those indicators which are key to the firm, also named criti166


cal indicators. That is, those indicators which are vital both for CSR management and for the management of the strategic perspectives. The tool so designed, based on correlation tables between indicators, allows us not only to select the critical indicators, but also to know their status, or, equivalently, to determine the percentage of improvement both by strategic perspective and by social dimension.

3.2 Phase II: Improvement Plan Now, the tool allows us to analyze the indicators that could be applied and are not currently measured by the company. Thereby demonstrating the capacity of improving the firm on CSR and its location (perspective/dimension), facilitating thus its Integral management (Fig. 5).

Fig. 5 Improvement Plan.

3.3 Phase III: Implementation and Monitoring The role of this third and final phase is to monitor and to control all the critical indicators, providing information about their evolution. This will allow us, on Phase IV, its integration with the Operating Plan.

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In short, it allows us to know the fraction of strategy goals effectively implemented (the advance on the fulfillment of the objectives of the operational plan that are related to CSR), as well as the advance achieved between different periods. This last section of the tool uses red and green colors to distinguish between the status of each perspective-dimension at a glance. Those indicators that do not meet the objectives are highlighted in white (see Fig. 6).

Fig. 6 Table for managing and controlling indicators.

This analysis can be extended further, making the tool more effective for management, both by an integration into the company's operating plan, a process that is developed later, as well as by the possible monitoring of each indicator. Fig 7 shows an example of the record sheet that can be performed for each indicator.

Fig. 7 Tracking card for indicator LA2.

3.4 Phase IV: Integration with the Operational Plan The final process of this tool is the phase of integration with the company's operating plan. It is very versatile, with high adaptability and vital to the establishment of relations with the previous phase of implementation and monitoring.

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The aim is its practical application to a "Service Company: Consulting", making evident not only its capacity for measuring and tracking, but also its ability to be adapted when classifying CSR indicators for each management area of the company, whatever the degree of complexity of its operational planning. The studied company uses a complex integrated management system based on a patented model with 7 +1 levels. The result is shown in Fig 8.

Fig. 8 Integration of CSR indicators with the operational plan of the company.

After a thorough analysis (available in Muñoz, J. (2012)), the conclusions drawn from its integration into the operational plan are as follows in Fig. 9.

Fig. 9 Achieved goals for critical indicators.

4 Final Syntheses The proposed model, which has been tested in a consulting firm, but which can be applied/adapted to any other company, allows: 169


 To perform an internal review of the company with relation to CSR, according to its indicators of interest, and to integrate new indicators. This makes the management of each individual indicator easier, providing information about monthly and annual evolution, rate of progress towards objectives, trends, new objectives, estimated cost and time, scope, etc.  To identify the strategic CSR indicators for the company, allowing it to focus their strategic and operational efforts. Controlling the critical indicators for each management area, and its corresponding margin for improvement.  To assess the monitoring of these indicators as currently undertaken by the company, classifying them according to their CSR dimension or strategic perspective, and checking the improvement ratio for each dimension and perspective.  To evaluate the CSR by the desired level or perspective: by areas or corporative levels of the operational plan, by strategic lines or CSR dimensions; For strategic or operational decisions, watching their evolution over time; it allows the introduction of new critical or general indicators.  To diagnose the analysis and evolution of CSR in the company, checking the degree of implementation of the strategy, and, thus, to establish corrective measures.  A model adaptable to any type of operational planning in order to perform a scanning of the effectiveness of CSR at each management level of the company. In conclusion, it is a tool that allows the introduction, implementation, analysis and evolution of CSR in a company, facilitating the establishment of operational and strategic CSR lines, and integrating the BSC.

5 Future Lines of Research and Development Due to the scope of this study, the main future R & D lines are addressed towards an integral automation of the tool, looking for its full integration into the enterprise. It is necessary to create an interface that allows managing the tool in harmony with the rest of applications implemented in the company, so that data treatment can be carried out with the greatest possible traceability and integrity.

6 References García Vílchez, Emilio José (2010) “Desarrollo del modelo de Sostenibilidad Integrado (M.S.I.) para la medida de la gestión sostenible de una industrial de procesos: Aplicación al sector de fabricación de neumáticos”. Tesis Doctoral, Universidad de Valladolid.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Muñumer, H. (2011) “La Responsabilidad Social de la Empresa. Actualización del Sistema de Gestión Ética (SGE21:2008) e Integración de los criterios de la Guía de Responsabilidad Social ISO26000:2010” Proyecto Fin de Carrera, E.I. Industriales, Universidad de Valladolid (Winner of the UVA RSU 2011). Muñoz Sanz, J. (2012) “Cuadro de mando responsable: aplicación práctica en la consultora 1A Consultores”. Proyecto Fin de Carrera, E.I. Industriales, Universidad de Valladolid (Awarded with a special mention in the Organization section, in “X Premios Michelin Valladolid a los mejores Proyectos Fin de Carrera sobre Innovación, Calidad Total y Organización” (2012).

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Applying Cluster Analysis to Renewable Energy Emergent Sector at Local Level Larruscain J1, Río-Belver R2, Cilleruelo E3, Garechana G4, GavilanesTrapote J5 Abstract This paper aims to provide a brief overview of state-of-the-art methods of cluster analysis and to acknowledge their limitations when applied to local level in renewable energies. This emergent sector is becoming increasingly important within the field of Industrial Organisation, with technological and industrial innovation being essential for the competitiveness of future “smart cities“. An understanding and analysis of the clusters formed by the different participating actors (public administration, centres of research and knowledge, and businesses) will be the key to safeguarding economic development, especially in their initial stage. As a conclusion, Social Network Analysis (SNA) tools together with Competitive Advantage Analysis (CAA) seem to be the most recommended methods.

Keywords: Cluster Analysis, Renewable Energy, Network Analysis, Collaborative Networks, Management Models

1Jaso

Larruscain ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Nieves Cano 12, 01006 Vitoria, Spain 2Rosa

Río-Belver ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Nieves Cano 12, 01006 Vitoria, Spain 3Ernesto

Cilleruelo ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, alameda Urquijo s/n, 48030 Bilbao, Spain

4Gaizka

Garechana ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Elcano 21, 48030 Bilbao, Spain 5Javier

Gavilanes-Trapote ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Nieves Cano 12, 01006 Vitoria, Spain

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1 Introduction In the era of globalisation, the tendency to create local clusters is gathering strength as the key factor for the economic development of “smart cities”. This is particularly true in the renewable energy (RE) sector, not only in order to comply with sustainability requirements imposed by government organisations, but also to generate economic growth. The competitiveness of a sector can be measured by its clusters. These clusters in turn can be analysed by the numerous methods used by the scientific community. Whilst the majority of these methods are applied to geographical areas of nations or regions, there is a growing need to be able to apply them to more restricted areas, such as cities. The purpose of this article is to provide a brief overview of state-of-the-art methods of cluster analysis applied to local level in renewable energy sector. For that purpose, a research methodology is carried out based on three main steps: gathering information about this specific sector, analyzing general identification tools with specific network indicators, as well as highlighting limitations when applying to local level.

1.1 Renewable Energies (Sub)Sector The objective to increase the percentage of RE in the European energy mix to 20% by 2020 (European Commission communication 2011) has caused the scientific production in RE to double in size at European and worldwide levels between 2002 and 2007 (Romo-Fernandez et al. 2011) and also the boost of a new multidiscipline industrial sector. Nevertheless, the need to incorporate a greater percentage of different technologies (including not so well-developed ones such as wave, tidal and small wind energies) within the new structures of energy generation and distribution in cities makes local participation increasingly important in terms of industrial development. Investments in this sector will generate a multiplying effect in the economy, and the creation of new organisational structures such as local clusters will become necessary (Marques and Fuinhas 2012).

1.2 Local Clusterisation According to Porter (1998), an industrial cluster is defined as: “a geographic concentration of interconnected businesses and institutions in a particular field, creating a matrix crucial for increasing productivity”. Accordingly, clusters have a competitive advantage due to their co-localisation (Doeringer and Terkla 1995). 173


Modern clusterisation theories affirm that the experience and know-how shared by actors of a cluster are the greatest source of benefit, as a result of being close by and maintaining local innovation networks (Porter 2000). The type of industry is usually a factor that influences the typology of a cluster, which changes from a temporary phase to another, going through the embryonic, established, mature and declining stages. In the case of the RE sector at a local level, they are currently in the first phase and have a mixed typology (He and Fallah 2011) between the Marshallian, Hub-and-spoke, Satellite platform or Stateanchored form (Markusen 1996). Whilst national and regional clusters have been studied in detail by the scientific community, no specific studies have been carried out at a local level. At local level, the success of a cluster is largely determined by the growth potential of its small and medium sized industries. For instance, one of the main priorities for policymakers is to promote local enterprise and to allow SMEs to benefit from the availability of the cluster’s resources (He and Fallah 2011). The extensive and speedy evolution of RE enterprises shows that local clusters as well as industry based on knowledge will grow exponentially in the next few years. Clusterisation in this emergent RE sector is an industrial hallmark. Porter (1998) argued that although the role of localisation has been ignored in the era of global markets, lasting competitive advantages are to be found in the local characteristics that cannot be matched by far-off competition and that these characteristics, among others the relationships, will have to be studied and analysed in detail, especially in local new clusters (see Table 1). Table 1 Some examples of European Renewable Energy Local Clusters (2011) Cluster

Creation year

Phase

Members

Comments

(companies)

(Employment)

Hamburg (Germany)

2010

Embryonic

163

Local: 14.563; expected growth (2008-2015): 40%

Freiburg (Germany)

2009

Established

107

Region: 12.000

Copenhagen (Denmark)

2010

Embryonic

36

Local expected growth (20102013): +1000

San Sebastian 2009 Embryonic 85 Local: 1.800 (Spain) Source: http://en.erneuerbare-energien-hamburg.de/, http://www.greencity-cluster.de/, http://www.cphcleantech.com/, and http://www.fomentosansebastian.org/

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2 Cluster Analysis Tools Cluster analysis is an essential tool in the identification of areas of local-regional economy where there are comparable advantages in terms of the productivity and economic growth of a cluster. Comprehensive analysis of a cluster requires paying attention to concepts such as industrial structure, business strategy, competitiveness between industries and the relationship between knowledge and technology (Iammarino and McCann 2006). In general terms, most authors suggest an analysis that takes into account two aspects. On the one hand, the impact indicator (to measure the impact of the network on its members) (Newman 2001) and, on the other, the size of the network and its average path length (the average number of links between its members). It has been observed that businesses embedded in alliance networks, which show a high clustering impact and reach (very short lengths of links between businesses), tend to show high innovation performance (Schilling and Phelps 2007). With regard to its own growth, this will be directly related to the benefits obtained from being a member of the network, such as economies of scale (Doeringer and Terkla 1995).

2.1 General Methods Although literature relating to methods is varied and extensive, the methods can be grouped according to the origins of baseline data. Quantitative methods are used in the generic analysis of the properties of the network, both at the general and restricted levels (Bergman and Feser 1999). The most important methods in this group are: input-output (analysing an approximation of interdependencies between different areas of the network), cluster dependency (analysing the dependency ratios which can easily be visualised with the Fuzzy tool), and network analysis (together with the Graph theory used for visualisation only) (Stejskal and Hajek 2011). Alternatively, qualitative methods, which provide greater sensitivity regarding the relationship between the actors in the cluster (Doeringer and Terkla 1995), would be: expert opinion, surveys and industry research. A full analysis requires the use of both types of method. Social Network Analysis (SNA) will specifically provide information that enables possible actors to be aware of the existence, needs and ability requirements of others, including help to develop new alliances (Gulati et al. 2000). This becomes a key element in the study of relationships at an organisational level, inside and outside the clusters (Johannisson 1995; He and Fallah. 2011). Its objective is to detect and interpret patterns in the links between the different actors in the network, which are represented as vertices (De Nooy et al. 2011). In addition, attributes (characteristics of the actors, which are not based on their 175


structural position within the network, and calculated statistically) provide added value to the interpretation of the structure. The most important specific network indicators (De Nooy et al. 2011) calculated and visualised by means of certain types of software such as Pajek, Ucinet, Visone, Gephi or Vennmaker (Richards 2007), are:  Density: ratio between existing and possible relations  Cohesion: number of bidirectional choices in relation to the number of dyads  Multiplexity: share of multiplex relations on all possible relations  Degree of homophily: describes whether actors with similar attributes are more connected with each other than to actors with different attributes. The network typology of a cluster is critical from the first moment of its existence, as it will determine its success or failure during the later phase of expansion, growth and development. Analysis of this first phase is essential, particularly to identify the cluster potential (He and Fallah 2011).

2.2 Identification Methods and Limitations in RE Sector The emergence of a cluster can be attributed to historical circumstances, even before the appearance of the contributing industries themselves, or could even be due to chance or coincidence (Porter 1998). It may also be the result of a business opportunity, of the presence of a unique added value, an increase in the influence exercised by a business, an increase in the undertaking or even a change in the policies of a given sector (Su 2009). The latter applies to most RE clusters. There are numerous methods used in identification, such as: expert opinion, input-output analysis (trade-based and innovation-based), network analysis, surveys or Giniho coefficient of localization (Bergman and Feser 1999; Stejskal and Hajek 2011). However, the most widely used are explained below.

2.2.1 Location Quotients This method compares the fraction of the region’s variable in a particular industry cluster to the fraction of the nation’s variable in the same industry (employment, wages or other economic variable). An example is given in Fig. 1. It is suitable for the RE sector only as a first approximation due to the fact that although it provides local information, it uses only one analysis factor and it does not allow to predict the behavior of emergent cluster.

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Fig. 1 Tri-dimensional representation of the LQ method using data from 2001 to 2006 (Primont and Domazlicky 2008) to identify emergent clusters in Southeast Missouri.

2.2.2 Shift-Share Analysis It shows easily the influence of the industrial structure and changes in the regional economy on a given variable, categorising the actual changes into three percentage-effect groups: national, industry cluster and regional (Stimson et al. 2006). Although it is useful to compare a hypothesis of potential viability of an emerging RE cluster, it can not be corrected with factors dependent on economy (RE is not currently stable) and it is necessary a 5 year time-window.

2.2.3 Ellison and Glaeser Index of Agglomeration This establishes the degree of agglomeration of a specific industry within a region. In industrial areas, agglomeration occurs in the form of a cluster. The distribution of that industry and the size of the businesses within that sector are both taken into consideration (Ellison and Glaeser 1997). The lack of detailed information of companies’ inner field of activity (RE sector still remains very diversified in industrial activity since RE technology is not mature) complicates accurate results.

2.2.4 Competitive Advantage Analysis (CAA) This is a mixed method (quantitative and qualitative) based on Porter’s Diamond, which calculates the competitiveness of the cluster environment and its components (Fig. 2) and requires the opinion of different managers of the most prominent actors (Stejskal and Hajek 2012). It gives useful results in terms of demand, sources, industrial branches and strategies, being sufficient to predict clusters behavior, but no specific studies have been carried out at RE local level. 177


Fig. 2 Competitiveness of RE industries in Germany compared with India and China, using Porter’s Diamond model adapted to the RE sector. (Dögl et al. 2010)

3 Conclusions In RE emergent sector, local clusters are currently in their first phases (embryonic, established) being their success largely determined by the growth potential of their small and medium sized industries. As concluded in this research, an analysis of these clusters formed by the different participating actors will be the key to safeguarding economic development. Among the varied and extensive cluster analysis methods studied and which can be grouped according to the origins of baseline data (Bergman and Feser 1999; Stejskal and Hajek 2011), identification methods appear to be essential and crucial (He and Fallah 2011) in RE sector where local clusters’ births are becoming increasingly important. As a result, the order of applicability efficiency of these could be said to be CAA, Shift-Share analysis and Ellison and Glaeser index of agglomeration (Stejskal and Hajek 2011). However, limitations appear in two senses. On the one hand, regarding the baseline data, there is still no consensus within the public administration on how to define the sector itself (lack of official and standardised data at local level owing to multidisciplinary diversified industrial activities in no-mature technology), no availability of long time windows (essential to accurate and comparable results) and a difficulty for companies’ managers to provide sensitivity information such as their relationships with others within the cluster. On the other hand, applying methods which are used in regions analysis, inaccuracies in several resultfactors might appear. To summarize, and taking into account these available tools and their limitations in RE sector, Social Network Analysis (SNA) together with Competitive Advantage Analysis (CAA) seem to be the most recommended methods. 178


4 References Bergman EM, Feser EJ (1999) Industrial and Regional Clusters: Concepts and Comparative Applications. West Virginia: Regional Research Institute, West Virginia University Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. A Roadmap For Moving To A Competitive Low Carbon Economy In 2050, COM 2011; 112, Brussels, 8.3.2011 De Nooy W, Mrvar A, Batagelj V (2011) Exploratory Social Network Analysis with Pajek. Cambridge University Press, New York. Doeringer PB, Terkla DG (1995) Business strategy and cross-industry clusters. Economic Development Quarterly 9:225-37 Dögl C, Holtbrügge D, Schuster T (2012) Competitive advantage of German renewable energy firms in India and China: An empirical study based on Porter's diamond. International Journal of Emerging Markets 7(2):191–214 Ellison G, Glaeser EL (1997) Geographic concentration in U.S. manufacturing industries: A dartboard approach. Journal of Political Economy 105:889-927 Gulati R, Nohria N, Zaheer A (2000) Strategic Networks. Strategic Manage. Journal 21:203–215 He J, Fallah MH (2011) The typology of technology clusters and its evolution. Evidence from the hi-tech industries. Technological Forecasting and Social Change 78(6):945-952 Iammarino S, McCann P (2006) The structure and evolution of industrial clusters: Transactions, technology and knowledge spillovers. Research Policy 35(7):1018-1036 Johannisson B (1995) Paradigms and entrepreneurial networks – some methodological challenges. Entrepreneurship and Regional Development 7(3):215–232 Markusen A (1996) Sticky Places in Slippery Space: A Typology of Industrial Districts. Economic Geography 72(3):293-313 Marques AC, Fuinhas JA (2012) Is renewable energy effective in promoting growth? Energy Policy 46:434-442 Newman MEJ (2001) Scientific collaboration networks: I. Network construction and fundamental results. Phys. Rev. E 64 016131 Porter ME (1998) Clusters and the new economics of competition. Harvard Bus. 76(6):77–90 Porter ME (2000) Location, Competition and Economic Development: Local Clusters in a Global Economy. Economic Development Quarterly 14(1):15–34 Primont DF, Domazlicky B (2008) Inudustry Cluster Analysis for the Southeast Missouri Region. Center for Economic & Business Research. Missouri State University Richards W (2007) Computer Programs for Social Network Analysis. http://www.insna.org/ Romo-Fernández LM, López-Pujalte C, Guerrero Bote VP et al. (2011) Analysis of Europe’s scientific production on renewable energies. Renewable Energy 36(9):2529-2537 Schilling MA, Phelps CC (2007) Interfirm collaboration networks: the impact of large-scale network structure on firm innovation. Manage. Sci. 53(7):1113–1126 Stejskal J, Hajek P (2012) Competitive advantage analysis: A novel method for industrial clusters identification. Journal of Business Economics and Management 13(2):344-365 Stimson R, Stough RR, Roberts BH (2006) Regional Economic Development: Analysis and Planning Strategy, 2nd edition. New York: Springer. 452 s. ISBN 978-3-540-34826-9 Su Y, Hung L (2009) Spontaneous vs. policy-driven: The origin and evolution of the biotechnology cluster. Technological Forecasting and Social Change 76(5):608-619

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Application of Reverse Innovation in SMEs Garcia Miranda I1, Duran Heras A2, Giraldo Casado E3 Abstract Reverse innovations are typically originated in the developing countries and later adopted in rich countries. This strategy is increasingly practiced by multinational enterprises (MNEs) that can access the market structure of the developing countries and can deploy all the company force to come up with innovations. Small and medium-sized enterprises (SMEs) increasingly face competition from products by new entrants located in the developing world, often applying frugal innovation, as well as from products developed by MNEs through reverse innovation. It is therefore critical that they defend their position by developing products using the techniques of reverse innovation; however, in doing so they face specific challenges. In this article we discuss these challenges, and how the application of reverse innovation in SMEs differs from that in MNEs.

Keywords: Reverse Innovation, Strategy, SMEs, Frugal Engineering.

1 Introduction The phenomenon of Reverse Innovation was first described by Immelt et al. in October 2009 in the article “How GE is disrupting itself”. Innovations are typically originated in rich countries and later downhill to the developing world. A reverse innovation is any innovation that is adopted first in the developing world

1Ivan Garcia Miranda( e-mail: [email protected]) Área de Ingeniería de Organización, Universidad Carlos III de Madrid, Avda. De la Universidad, 30, 28911 Leganés, Madrid, Spain. 2Alfonso

Duran Heras ( e-mail: [email protected]) Área de Ingeniería de Organización, Universidad Carlos III de Madrid, Avda. De la Universidad, 30, 28911 Leganés, Madrid, Spain. 3Esmeralda

Giraldo Casado ( e-mail: [email protected]) Facultad de Economía y Negocios (Universidad de Chile). Escuela de Ingeniería Comercial (Universidad Santo Tomás). Santiago, Chile.

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and after uphill to the rich countries. They are also known as Gandhian or Frugal innovations (Sehgal et al. 2010, Prahalad et al. 2010). Jeffrey Immelt, chairman and CEO of General Electric, stated: ”If we don’t come up with innovations in poor countries and take them global, new competitors from the developing world will”. Affordability and sustainability replace abundance and premium pricing as driver for innovation (Prahalad et al., 2010). Instead of simply cutting costs and offering lower-end models with fewer features, true innovations in terms of technology and process are necessary in order to satisfy the demands of developing markets. Successful companies from these environments often excel in this process, known as frugal innovation. Many multinationals establish R&D facilities in emerging countries. By 2007 nearly 70% of research intensive Fortune 500 companies conducted at least part of their R&D in India, a trend that is still increasing (Herstatt et al., 2008).

2 Background The issues, problems and solutions described by Govindarajan (Govindarajan et al., 2012) are going to permeate our home market. The so-called emerging giants (companies based in the developing world) want to expand their products and services in the well-established home markets, either with products with equivalent features offered at lower prices or with a new price-performance proposition. In this environment, it seems to be of high interest to study the processes and strategies driving the success of reverse innovations and their transference to developed countries in order to extract the best practices followed by multinationals and apply them in the SMEs. Many companies are setting a glocalization strategy implying a compromise between global scale and local responsiveness in order to achieve new markets in the emerging countries. Corporations optimize their products for the developedworld customer without sustainable competitive advantage. The reverse innovation strategy, however, has another logic, which is trying to obtain the best solution for the emerging-market customer. Reverse innovation begins not with inventing but with unlearning. Such a strategy requires internal resources and capabilities in the organization; however, SMEs often lack these requirements. "SME" stands for small and medium-sized enterprises – as defined in EU law: EU recommendation 2003/361. The main factors determining whether a company is an SME are number of employees and either turnover or total assets in balance sheet. According to the annual report on small and medium-sized enterprises in the EU 2011/12, Small and Medium-sized Enterprises (SMEs) form the backbone of the EU economy – accounting for 99.8 per cent of non-financial enterprises in

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2012, which equates to 20.7 million businesses. The overwhelming majority (92.2 per cent) are micro-enterprises, defined as those with fewer than ten employees. In employment terms, SMEs provided an estimated 67.4 per cent of jobs in the non-financial business economy in 2012, almost identical to 2011 (67,4 per cent) but up from 66.9 per cent in 2010, although SMEs provided a slightly smaller share of GVA in the EU in 2011 and 2012 (58.1 per cent). Both multinationals and SMEs are responding to current globalization with massive restructuring. Reverse innovation can be adopted by MNEs with international presence in emerging markets, but SMEs usually lack that structure abroad. The definition of SME inherently implies that SMEs have lesser human and financial resources at their disposal than MNEs. Developing new products and services using reverse innovation best practices, adapted to SME’s specific characteristics, could be considered as an effective line of defence. European SMEs usually operate under high overhead costs, such as labour costs, and find themselves faced with strong price-oriented competition from low-cost producers from emerging countries. Providing innovative products may help SMEs strengthen their competitive position in home as well as in international markets.

3 Application of Reverse Innovation & Implications

3.1 Reverse Innovation in MNEs To create a reverse innovation mind-set, MNEs must take three steps (Govindarajan et al. 2012): They must shift the center of gravity of their organization to emerging markets. They must bulk up on emerging market knowledge and expertise. They must change tone by taking highly visible and personal actions. All these actions imply an emerging country organizational structure, capital and an experienced management team. Some of these pieces may not be available in SMEs, who must therefore adapt the process as discussed below. MNEs try to shift the center of gravity shifting people, power, money and attention to where the growth is, rolling critical decision makers to emerging markets and increasing R&D spending in emerging markets focusing it on local needs. Other measures to manage emerging market knowledge and expertise will include changing the composition of the board of directors and the top management team to include leaders with deep experience in emerging markets or assign individuals to multiyear expatriate assignments in the developing world. In addition, MNEs has to set the tone about criticality of winning in emerging markets. 182


Reverse innovation is not only a product innovation but also a business-model innovation. Reverse innovation strategy requires new processes, new partnerships and even a reinvented value chain. MNEs have considerable advantages: technology, a global brand, supply networks, and manufacturing capacity.

3.2 Barriers to Innovation in SMEs Barriers to innovation in SMEs have been studied in numerous national and international research projects, e.g. Rodenes et al. 2002 in a province of Spain, Ylinenpää (1998) in Sweden, Rammer et al. (2006) and Tiwari et al. (2007a) in Germany. Comparing the findings of the above-mentioned references highlights that SMEs often face similar barriers to innovation. The most prevalent ones are listed in Table 2. Table 2 Barriers to innovation in SMEs Barrier category

Barrier

External barriers

Financial constraints Availability of Skilled Labor Bureaucratic Hurdles Difficulties in cooperations/partnerships

Internal barriers

Intellectual Property Management Project Management Internationalization Conceptualization of innovative products Marketing

Many SMEs have limited resources and lack know-how on international markets, which imply a significant barrier to innovation affecting international potential capacity. In this study we are focused on SMEs and their local markets, understanding that some of the SMEs have international outlook but not all of them. Understanding and overcoming these barriers is critically important to accomplish the reverse innovation strategy in SMEs.

3.3 Understanding Emerging Markets In countries like China and India a new consumer middle class of hundreds of millions of people is emerging. When we analyse these markets, we appreciate a 183


structure which is very different from that found in Europe. If we consider the market pyramid (Prahalad et al. 2003), at the top of the pyramid are a relatively small number of consumers who are responsive to international brands and have the income to afford them. Next, a much larger group of people who are less attracted to international brands. Finally, at the bottom of the pyramid of consumers is a massive group that is loyal to local preferences, habits and often to local brands. Below that is another huge group who are unlikely to become active consumers anytime soon. The extensive pattern of economic growth in these economies force MNEs to focus on satisfying new emerging middle class demands, competing with the booming local giants either entrepreneurs or companies who create more products with fewer resources. All these new entrants might spread their products to our home market, particularly aiming stagnant middle class consumer segments, which might be attracted by a new price-performance proposition. Govindarajan (Govindarajan et al. 2012) stated that there are five enormous gaps that separate emerging markets from rich countries: the performance gap, the infrastructure gap, the sustainability gap, the regulatory gap and the preferences gap. Consumers in big emerging markets are getting bombarded with global standards, but they are often unwilling to pay global prices. Consumers in the big emerging markets are far more focused on the price-performance proposition. Even when consumers in emerging markets want to buy the same products sold elsewhere, some adaptation is often necessary to reflect differences in use, distribution, or selling. Customization is the first response of the MNEs to its expansion to emerging countries strategy. The rich world has extensive infrastructure deployed but emerging countries do not. These infrastructure constraints can help developing creative products and services. Most of these new products and services are based in green solutions because they can adopt the green solution as the new one without incurring in change costs. In addition, innovation in the emerging countries enjoys the advantages of lower friction due to a regulatory gap with the rich countries. These different gaps become the path of the dynamics of reverse innovation so understanding them is crucial to SMEs to face the entrance of new competitors and develop products and services for dodging the competence at home markets. Eventually, outstanding SMEs with a brilliant price-performance proposition can afford to capture market share in developing countries by venturing overseas.

3.4 Reverse Innovation in SMEs For many managers of SMEs in rich countries, the answer to the entrance of new products from competitors located in the developing world is calling on the gov184


ernment to instate trade barriers, providing some other form of grant, becoming a subordinate partner to a multinational or selling out and leaving the industry. We believe there are other options for SMEs, however these require them to innovate. Not so many managers have posed several key questions to evaluate the risks: How strong are the pressures to globalize in your industry? How internationally transferable are your company’s competitive advantage? By understanding these answers, managers can better appreciate the actual risks. There are SMEs in which success turns on meeting the particular demands of local consumers with a well-established relationship with them. In some sectors, high transportation costs needed may discourage a global presence. Also, SMEs may have a local distribution network that would take years for a new competitor to replicate. Or they may have long-standing relationships with government officials. In all of these cases, SMEs may continue by selling only in their local markets. Any such asset could form a barrier to entry to the home market but that will only retard the demise of these SMEs, especially those oriented to middle-class markets. MNEs can have the same barriers and even others because of their resources availability. Their structure deployment in home markets let them introduce without friction costs the new reverse innovative products. Creating a reverse innovation mind-set in SMEs has to start by quelling fears about losing the positioning of the brands or cannibalization of the current products. Developing new products and services based on reverse innovation could partially cannibalize yourself, however if someone else comes with a new performance-price proposition they anyhow do it The innovation process can be simplified in 3 phases (Tiwari et al. 2007b): conception, implementation and marketing. Conception includes requirement analysis and idea generation. Implementation embraces development (prototype, construction) and testing. The last phase includes production and market launch and penetration. In this document we will focus in the first and second phases, specifying reverse innovation characteristics. After beating canibalization fears and overcoming innovation barriers, SMEs should create a clean-slate innovation unlearning price-performance curve and trying to determine a new proposition as MNEs achieve reverse innovation products. SMEs have to estimate customer needs as if they were emerging markets customer needs, similarly to the market research conducted by MNEs with overseas structure. Some marketing studies can be conducted within home markets but analyzing real needs and not local preferences. Usually SMEs are guided by actual customers requests about its actual products, which influence new developing process by technology push. Not forgetting the actual customers, SMEs should innovate for new consumption among noncustomers or the ones who would first change their mind to new competitor’s products or services. Regarding the idea generation, SMEs can achieve the twin objectives of offering a new price-performance proposition and a new idea conception by using open innovation networks (Tiwari et al. 2012). Open innovation is a paradigm that assumes that firms can and should 185


use external ideas as well as internal ideas, and internal and external paths to market, as firms look to advance their technology (Chesbrough et al. 2008). The cooperation may take place at any stage of the innovation process as a replacement for R&D resources shortage in comparison with MNEs. By the second phase (implementation), SMEs should develop a new priceperformance proposition by starting from zero, questioning all the elements used taking into account the infrastructure constraint experimented in emerging countries. In addition, they should explore the possibility of developing a new component with a new cost model and using a green solution. SMEs can increase the probability of offering an attractive price-performance proposition if they are able to connect their product development process with global innovation networks. MNEs will shift their resources on emerging markets, but SMEs have to manage to establish collaborative forms of product development and testing in the global network. This collaborative form can be taken place in the same country or beyond the national boundaries. This cooperation will also help to reduce the aforementioned barriers to innovation in SMEs. Most of the studies developed until now show MNEs examples of reverse innovation (Govindarajan et al. 2012) such as GE, P&G or PepsiCo, which prove that reverse innovation is a recent and successful strategy, however the approaches followed by these MNEs can not be directly applied by SMEs. SMEs can get more directly applicable hints by analyzing start-ups and entrepreneurs who are reinventing the idea of radical price-performance equation and in social innovators. One such example is Diagnostics for All (http://www.dfa.org), DFA is a nonprofit enterprise fusing biotechnology and development, dedicated to creating lowcost, easy-to-use, point-of-care diagnostics designed specifically for developing countries and hoping also to commercialize its idea in the rich countries. DFA has relied on strategic partnerships to reach its success using paper technology to create diagnostic devices. Another example (The Economist, 2012), Igloo Vision is a small British company and has managed to disrupt the events installations and projection solutions market. They have employed computer-games technology and cheap projectors for playing 360º videos and simulation software. They are still keen to develop formal partnerships with companies for new application deployment.

4 Conclusions In this paper we have analyzed the possibility and challenges involved in the application of a reverse innovation process in SMEs. The result of this analysis is summarized in Table 3.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 Application of reverse innovation in MNEs and SMEs Challenge

MNEs

SMEs

Strategy

Center of gravity to emerging markets.

Center of gravity to competition with products from emerging markets.

Knowledge

Emerging market knowledge and expertise.

Basic needs of consumers and new price-performance proposition.

Communication Criticality of winning in emerging markets.

Criticality of competing with new “far from home” competitors and MNEs applying reverse innovation.

SMEs should outline the criticality of the entrance of new competitors coming from emerging markets and of products developed by MNEs through reverse innovation. In order to face this new scenario we propose tailoring MNEs reverse innovation strategy and tools to SME’s specifics. Regarding the process of innovation and applying reverse-innovation best practices we propose that SMEs adapt their first two stages as shown in Table 4. Table 4 Application of reverse innovation in innovation process phases Phase Conception

MNEs

SMEs

Using emerging market knowledge and expertise. Generating ideas in R&D centers of emerging countries.

Extracting ideas based at home market eliminating all the unnecessary features. Questioning every step and simulating emerging countries gaps.

Implementation Development and testing in emerging markets.

Testing non-costumers for feedback. Using global innovation networks for developing and testing.

5 References Chesbrough H., Vanhaverbeke W., West J. (2008) Open Innovation: Researching A New Paradigm, Oxford University Press, Oxford. Ecorys – EU SMEs in 2012: at the crossroads. Annual report on small and medium-sized enterprises in the EU, 2011/12 – Rotterdam, September 2012 Govindarajan V., Trimble C., Nooyi I.K. (2012) Reverse innovation: Create far from home, win everywhere. Harvard Business Review Press. ISBN 978-1-4221-5764-0 Herstatt C., Tiwari R., Ernst D., Buse S. (2008) India's National Innovation System: Key Elements and Corporate Perspectives. East-West Center. January 2008. Working paper nº 51 Immelt J.R., Govindarajan V., Trimble C. (2009) How GE is Disrupting Itself. Harvard Business Review, October 2009, 56-65. Prahalad C.K., Liberthal K. (2003) The end of corporate imperialism Harvard Business Review (2003, 81 (8): 109-17, 142) Prahalad C.K., Mashelkar R.A. (2010) Innovation's Holy Grail. Harvard Business Review JulyAugust 2010 132-141.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Rammer C., Zimmermann V., Müller E., Heger D., Aschhoff B., Reize F. (2006) Innovationspotenziale von kleinen und mittleren Unternehmen, Centre for European Economic Research (ZEW), Mannheim. Rodenes Adam M., Montoro Rodríguez J., Onofre Montesa J. (2002) Análisis de Barreras a la Innovación Tecnológica en la PYME de la Comunidad Valenciana II Conferencia de Ingeniería de Organización Vigo, 5-6 Septiembre 2002. Sehgal V., Dehoff K., Panneer G. (2010) The Importance of Frugal Engineering. Economic Times Mumbai. 25 may 2010 – Issue 59 Tiwari R., Buse S. (2007a) Barriers to Innovation in SMEs: Can the Internationalizarion of R&D Mitigate Their Effects? Proceedings of the First European Conference on Knowledge for Growth: Role and Dynamics of Corporate R&D (CONCORD 2007) – Seville Spain Tiwari R., Buse S., Herstatt C. (2007b) Innovation via Global Route: Proposing a Reference Model for Global Inovation Activities. Proceedings of the Second International Conference On Management of Globally Distributed work, Bangalore, India, July 25-28. Tiwari R., Herstatt C. (2012) Open Global Innovation Networks as Enablers of Frugal Innovation: Propositions Based on Evidence from India. Die Unternehmung, 66(3): 245-274 The economist (2012) Shumpeter business and management blog: Frugal innovation – Battle igloo http://www.economist.com/blogs/schumpeter/2012/05/frugal-innovation (last visited March 8, 2013) Ylinenpää H. (1998) Measures to overcome Barriers to Innovation in Sweden, Paper EFMD European Small Business Seminar in Vienna, 16.09.1998.

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Analysis of the Electric Car Via Patents Fernandez de la Bastida E1, Gavilanes-Trapote J2, Río-Belver R3, Cilleruelo E 4, Larruscain J 5 Abstract The automotive sector is one of the most relevant economic activities in terms of generating prosperity and work. This activity is characterized by a strong competition with the tendency of multiplication of business alliances. In 2030 it is expected that the number of cars worldwide would double provoking a shortage and high cost of the sources of energy. Taking this into consideration a technological U-turn has to be made in order to guarantee the long term sustainability of mobility. The systems of electric propulsion and the car battery seem to be the most promising options. The present study tries to sketch the business and investigation outlook of the electric car via patents giving information to the interest of the Spanish agents involved.

Keywords: Patents, Innovation, Electric car, Citations.

1

Endika Fernandez de la Bastida ( e-mail: [email protected]) has obtained a degree in Industrial Management Engineering. 2

Javier Gavilanes-Trapote ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Nieves Cano 12, 01006 Vitoria, Spain 3 Rosa Río-Belver ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Nieves Cano 12, 01006 Vitoria, Spain 4

Ernesto Cilleruelo ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, alameda Urquijo s/n, 48030 Bilbao, Spain 5

Jaso Larruscain ( e-mail: [email protected]) Foresight, Technology and Management (FTM) Group. Department of Industrial Engineering, University of the Basque Country UPV/EHU, calle Nieves Cano 12, 01006 Vitoria, Spain

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1 Introduction The competitiveness of a nation is based on the capacity of its industry to innovate and continuously improve its products, services and processes. (Porter 1990). Nowadays one has to acknowledge that innovation does not exclusively come from companies but that we can find its source in the interaction with other organizations that present complementary resources: competitors, suppliers, clients, investigation centers or universities (Bayona et al. 2003), giving space to what is called a “Innovation and Development Network”, a context in which institutions the individual and the market collaborate creating a scientific technical knowledge flow that results in a technological innovation (Cunningham et al. 2006). The success, when it comes to innovation, is mainly dependent on the capacity of a organization to transform information into knowledge and afterwards let this knowledge circulate in a continuous flow through the whole organizational structure (Escorsa and Maspons 2001). Summing up we can confirm that the competitiveness of a company depends to a large part on its capacity to innovate and that innovation in the current context is primarily based on adequate management of knowledge obtained through analyzing information. The data bases of patents, to pay for or for free, are a very good source of information, Dou (2004). These patents are the main channel to learn about scientific progress that neither can be found in the form of publications nor anywhere else. The benefits gained from studying patents in the sector of research and development have been analyzed and demonstrated in several studies, Ernst (1998), Acs et al. (2002). In scientific literature numerous empiric studies analyzing technical fields or sectors based on patent studies can be found: the analysis of the sector of recycling of waste in order to find out about new technologies (Rio and Cilleruelo 2010), the understanding of the knowledge flow between science and technology in the Basque Country (Gavilanes-Trapote et al. 2011). The aim of this study is to analyze the sector of the electric car via patents finding out about the tendencies in the sector, the knowledge flow, the most important companies and researchers as well as the existing network of collaboration and the capacity of retaining and attracting knowledge from countries and facilitating the opening of new ways of technical and industrial diversification in key sectors of its activity.

2 Methods and Procedures The source of the information selected is the database Esp@cenet of the European Patente Office, one of the three most important databases in the world (Michael and Bernd 2001), together with American and Japanese Patent Office among them 190


they process 86% of the Patent Applications of the world (Trilateral Co-operation 2005). In order to search for the parameters we have done an advanced search with key words, IPC codes and ECLA codes. The IPC codes or International Classification Patent and ECLA codes or European Classification Patent help classify the register´s by technological areas. First records which the search came up with and returned were exported to an Excel sheet and there to the VantagePoint 7.0 program, which integrates all the necessary steps for the analysis of patent and their graphic representation. The indicators used in the study case are grouped under three criteria: that determine the size and characteristics of the scientific and technological production, that evaluate the impact of the publications by citation and that define the structure of the Science, indicators in relation with first and second generation (Escorsa and Maspons 2001). The indicators used are:  Number and distribution of patents by year application  Inventions productivity by country, applicants and researchers  Autocorrelation between applicants  Capacity indicators for retaining and attracting  Identification of technical knowledge flow between countries

3 Case Study The electric car is a great opportunity for Spanish Industry. Its implementation involves the development of new technologies, innovative activity, generating high added value, quality employment, possibilities of increasing exports, improving efficiency and energy savings, control of CO2 emissions and reducing dependence on oil and its derivatives. The technological development, the market development and policy support aimed at increasing hybrid and electric vehicles in the mobility of the future. The current market situation seems to confirm this outlook, still available in the market several models of hybrid vehicles with a large-scale production. Also, the most car manufacturers are developing electric vehicle models. The new developments involve technological innovations, fact that will be reflected in the application for patent documents. In addition, the electric vehicle will also favor an advance even of Information Technology and Communication (ICT) sector, which will invest in the development of smart grids and meters and other services. The realization of a technological analysis of the electric car through patents provides valuable information to the sectors involved, either to their current developments and to identify future research. 191


4 Data Analysis A total of 105,167 patents were downloaded until October 31, 2012, of which 32,035 patents were taken through a word search, 21.109 by the ECLA codes and 52.023 records through a combined search of the IPC code B60L11/18 and different ECLA codes. Once all the information was imported to VantagePoint, the data was cleaned, which means, eliminating the duplicated records, unify inventors or companies and so on. Those patents which carry the words: Locomotive; Railway; Hydrogen; Children; Bycicle; Trolley-Bus; Rail Road; Monorail are also eliminates. However remain those with the word "train" in its title, and which do not relate to the train as transportation but refers to the various devices making up the car. 56.506 records were kept after these actions were made. The first indicator was the activity that can be seen in the number of inventions by application date. In the aforementioned figure a nearly nonexistent inventive activity can be observed until 1992 as well as in the last two years when the number of patents decreased considerably due to the time passing from the application to the publication of the patent, which can be up to 18 months. That is why the analyses are limited to the time 1992-2010 and to the final sample to 50.852 patents. 10000

9000 8000

7000 6000

5000 4000

3000 2000

1000 0

Fig. 1 Total number of patents during the period of study

In the figure 1 we can divide the curve into three parts in function of its gradient: The first one between 1.992-2.003, coinciding with the impulse of Bill Clinton’s government to buy green cars and with the Zero Emission Vehicle Mandate legislation that developed California obliging the manufacturers to develop electric vehicles. The second one in 2003, the year in which, due to pressure from the automotive sector and the nearly nonexistent political strength of the Bush administration, the Zero Emission Vehicle Mandate was changed into the Zero Emission Vehicle Regulation, which was less restrictive and only obliged the manufacturers 192


to sell electric vehicles in case it was profitable for these companies. That is why the EV-1 and other electric vehicles that were put up for leasing before disappeared. The third period corresponds with the years 2.004-2.010. During this time the number of applications increased considerably due to the coming into force of the Kyoto protocol, the price of petrol as well as the sensitization of the public for ecology and the development of renewable sources of energy. This in turn lead to a change in the attitude of the automotive industry and governments again counting on the electric car, giving rise to more autonomous batteries and better features allowing the electric car to start becoming a reality. The following chart shows the transformation of applications by nationality of those countries represented most often including Spain. 3000 2500 2000 1500 1000

500 0

Japan

China

United States

Germany

Republic of Korea

Spain

Fig. 2 Total number of patents per country during the period of the study.

One can see how China overtook Japan as the country with the most applications for patents in the sector of electric vehicles worldwide reflecting the change of the geography of innovation before the leading countries were Japan and the USA. In Spain, however, the applications have stayed more or less the same over the years, clearly beaten by Germany. The following analysis gives information about the number of patents per applicant. The ranking shows the country of origin of the major automotive companies in Asia: Toyota Motor Corp, Honda Motor Co Ltd, Nissan Diesel Motor Co and Mitsubishi Automotive Engineering, all of them Japanese. The Japanese company Hitachi Chemical Ltd does, however, appear too though it has no direct relations to the automotive sector but also offers solutions for the energy management of electric motors. 193


The first European and German company, Bosh Corp. is to be mentioned here too, as it is not a producer of cars but the main supplier of electric motors and batteries for companies like Daimler Chrysler, BMW, GM and Ford. As far as the national area is concerned the company Acumulador Tudor SA So occupies the first place of the ranking with four patents. This company, located in Guadalajara, devotes itself to producing batteries for automobiles, motorbikes and industrial machinery and belongs to the group of companies called Exide Technologies (USA). Next a technological auto-correlation map was created in which shows the existing relations between applicants of patents related to the electric car, specifically those who own more than fifty patents. Due to the size of the map and the space limitations it could not be included. The aforementioned map showed that there is a big group of companies that works together – especially the Toyota Motor Corp and the Nissan Diesel Motor CO. Other companies as for example Ford Motor Co or GM Global Technology Operations Inc hardly interrelate with each other. On the other hand important companies as for example the group Peugeot&Citroen or the Siemens AG do not develop any patents with any other company. This same map on a national level shows how practically all patents are developed individually, except those specific cases in which there is a collaboration with the Technical University of Madrid, the Technical University of Catalunya, the Foundation Circe and the Foundation Robotiker. The analysis of the origin and the destination of the inventions is essential to determine the capacity, the retention and the attracting of knowledge of the countries (Escorsa and Maspons 2001). Spain has therefore a limited capacity of retaining knowledge given that their own country protects only 17% of the patents applied for by Spanish companies. Japan on the other hand has the highest retention rate, 90%, as well as high numbers of attraction, in Spain; there are 30% of patents protected in Japan. Finally the analysis of citations can show us the different flows of knowledge between countries (Jaffe et al. 1993) or the measurement of the quality of the patents (Harhoff et al. 2002). The Japanese patents have a high auto-citation rate that shows a good internal transfer of knowledge. However, in the Republic of Korea one can observe a higher diversification in the geographic origin of its sources of knowledge, dominating Japan as far as patents registered by themselves are concerned. Chinese patents stand out as regards to their nearly non-existing citations despite their large number. This could be partly due to their novelty and quality, which would show that its inventions are not of a high enough quality in order to achieve a knowledge flow from China to other countries. The Spanish patents are hardly ever cited by the other countries which show that Spain is mainly an importer and not an exporter of knowledge.

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5 Conclusions A major increase in patents can be observed from the year 1992 onwards which this is due to a change in legislation, the sensitization for the environment taking place in society and the increase in the price of petrol. Patent applications are mainly made to national offices as opposed to international ones such as the WIPO, EPO and EAPO. This is mainly due to the lower cost of translation, processing and validation of the documents. That is why it is advisable to create a single European patent as it reduces the cost of translation to German, English and French exclusively. Most patent applications are being made to national offices in Japan, China and the USA and the Republic of Korea being mainly due to the lower cost to be paid in these countries and because of the presence of big automotive companies producing electric batteries and motors (such as Toyota, Honda, Nissan and Hitachi Chemical in Japan; Hyundai and LG Chemical in the Republic of Korea; and General Motors y General Electric in the USA) and the stimulus based economic policy especially in China (Guangzhou et al. 2009). The ability of investment in research and development can be found centralized in only a few applicants mainly from big Asian companies, especially Japanese ones as these companies from the automotive and electric motor producing sectors are the leading organizations in research, development and innovation. With the help of autocorrelation maps, networks of collaboration between different applicants, mainly Japanese, can be discovered due to their commercial relations, the partaking of some companies in others or their country of origin. In Spain, however, the collaboration between companies is rather an exception then the rule and this is why it would be interesting to observe policies implemented by countries such as Japan and to try finding collaboration and synergies between companies and/or technological centers in order to improve innovative activities. For Spanish applicants, the inventors are more than companies due to lack of national companies in developing patents, so must find ways to effectively support the protection of intellectual property developed in Spain, especially for companies or research institutions which is a key element in its strategy and that because of its size have funding problems. Asian countries such as Japan and the Republic of Korea are those who patent most in relation to their per capita GDP. One of the main reasons lies in the industrial structures of the analyzed countries: Japan and the Republic of Korea dispose of big industrial companies that have to make a tremendous effort in R&D in order for them to survive, whereas in Spain for example this circumstance this is not the case. A good example for this is the comparative effort made by the public and private sector in the respective countries: in the Republic of Korea and Japan the major part of the money spent on research comes from the private sector while in Spain the share of the investment from private companies is far lower.

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The countries cited most often are the USA, Japan and Germany which corresponds to the extremely high level of industrial development of the electric car in those countries and the culture of protection of intellectual property where the USA and Japan are the major exporters of knowledge. Considering the retention of knowledge it is surprising that there are not many auto-citations in Spain which can be related to the lack of relevance of the patents or necessity to improve the existing system of knowledge management.

6 References Acs Z.J.; Anselin L.; Varga A. (2002). Patents and innovation counts as measures of regional production of new knowledge. Res Policy, Vol. 31, pp. 1069–1085. Bayona, C., García-Marco, T. and Huerta, E. (2003). ¿Cooperar en I D? Con quién y para qué. Revista de Economía Aplicada, Vol. 31, No. 11, pp. 103-134. Cunningham, S.W.; Porter, A.L.; Newman, N.C. (2006). Special issue on tech mining. Technological Forecasting and Social Change. Vol. 73, No. 8, pp.915-922. Dou H.J.M. (2004). Benchmarking R&D and companies through patent analysis using free databases and special software: a tool to improve thinking. World Patent Information, Vol. 26, pp. 297-309. Ernst H. (1998). Patent portfolios for strategic R&D planning. Eng Technol Manage, Vol. 15, pp. 279–308. Escorsa P, Maspons R (2001). De la vigilancia tecnológica a la inteligencia competitiva. Pearson Educación, s.a. Gavilanes-Trapote J, Rio-Belver R et al (2011). The connection between science and technology in the Basque Country. Analysis of patents in literature. 6th International Conference on Industrial Engineering and Industrial Management. Vigo. Harhoff D, Scherer FM et al (2002). Citations, Family Size, Opposition and the Value of Patent Rights. Research Policy, 32(8): 1343-1363. Jaffe AB, Trajtenberg M et al (1993). Geographic Localization of Knowledge Spillovers as Evidence by Patent Citations. Quartely Journal of Economics, 108: 577-598 Michael J, Bernd B (2001). Patente citation analysis: a closer look at the basic input data from patent search report. Scienciometrics, 51(1): 185-201. Porter, M.E. (1990). The competitive advantage of nations: with a new introduction. Harvard Business Review. Rio, R.M., Cilleruelo, E. (2010). Discovering technologies using techmining: the case of waste recycling. The 6th International Scientific Conference “Business and Management 2010”. Vilnius Gediminas Technical University Publishing House “Technika”. Trilateral co-operation (2005). Trilateral statistical report 2004. Edition Munich. Germany. http://www.trilateral.net/tsr/tsr_2004/ch2/

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Quality in a Small Service Organization and its Relation with Sand Cone Model Braga C1, Migowski S2, Libânio C3, Spindler G4, Duarte F 5 Abstract The present study is based on the analysis of economic and financial sustainability of a small business, which overcame the average period of bankruptcies of small companies in Brazil. For the study, it was tested the Sand Cone Theory in Nostro Sabore Restaurant, located in Porto Alegre, with reference of the competitive priorities pyramid suggested by the authors Ferdows and De Meyer (1990), who relate quality as basis and main competitive priority, able to allow sustainability or contribute with other priorities. In this sense, besides investigating what motivates the sustainability of the company, through a survey with the costumers, it was possible to know their characteristics, motivations and preferences. Of the approximate eight thousand customers monthly, the sample size was calculated to ensure a confidence level of 95% in the results and totaled 198 people. The interpretation of the survey data was aided by the SPSS Statistics software, version 18, which means the results can identify opportunities for improvements in the company aiming at customer satisfaction and business continuity as well as respond if quality is indeed the foundation of its sustainability, as proposed by the Ferdows and De Meyer (1990).

Keywords: Sand Cone, Restaurant, Quality

1Caroline

Freitas Braga ( e-mail: [email protected]) Centro Universitário UniRitter, Porto Alegre (RS) Brasil.

2Sérgio

Almeida Migowski ( e-mail: [email protected]) Centro Universitário UniRitter, Porto Alegre (RS) Brasil.

3Claudia

de Souza Libânio ( e-mail: [email protected]) Centro Universitário UniRitter, Porto Alegre (RS) Brasil.

4Giselle

Spindler ( e-mail: [email protected]) Centro Universitário UniRitter, Porto Alegre (RS) Brasil. 5Francisco Dias Duarte ( e-mail: [email protected]) Fundação Saint Pastous, Porto Alegre (RS) Brasil.

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1 Introduction Small and medium sized businesses are considered the supporting pillars of the Brazilian economy. These companies face, with greater difficulty, the obstacles imposed by the competition. For this reason, it is essential to have and make use of consistent and complete information from its sector for decision making. In Brazil, more than 1.2 million new formal enterprises are registered annually. Of this total, more than 99% include micro and small enterprises and Individual Entrepreneurs (IE), according to SEBRAE (2011). Micro and small enterprises have a significant role in the occupation of the Brazilian population. They are responsible for more than half of the formal jobs in the country. In addition, considering the occupation that entrepreneurs create for themselves, it is noticeable that the companies of micro and small businesses are responsible for two-thirds of all occupations in the private sector of our economy (Center for Studies and Research of SEBRAE - October/2011). Regarding to the economic aspect, micro and small enterprises (MSEs) play a fundamental role in the development of the country and, when compared to large organizations, present distinguished characteristics, such as versatility and flexibility, agility in business management and technology diversity. These are also responsible for absorbing most part of the formal labor force in the country, considered a strong alternative occupation, business opportunity, and besides, are valuable providers of employment and income generation, according to current information from ABIA – Brazilian Association of Food Industry (2012), which indicates that the sector encompasses two million establishments and employs six million people, with a revenue of R $ 65.2 billion in 2009. According to a survey released on April 10th, 2012 by Serasa, from January to March this year, the Serasa Experian Indicator for Bankruptcy and Recoveries pointed 449 bankruptcies requests across the country, against 437 in the first trimester of 2011. Considering the total requests in 2012, 253 were made by micro and small enterprises, 116 by medium and 80 by large. Economists from Serasa attribute the advancement of records bankruptcy to interest rates which are still high, to high consumer delinquency and to fluctuations in economic activity. Running a business in a sustainable manner way is certainly a difficult equation to be solved not only by the meaning of its terms, but also for its strategic representation in reducing unemployment rates, due to the increase in MSBs life expectancy. Within this scenario of high mortality, however, there are some small companies in the restaurants segment that remain sustainable by using different strategies. The pursuit by Brazilian consumers for bars and restaurants is driven both as a means of entertainment such as to meet the basic need, which is carrying out their daily meals. According Chacon (2011, p. 1), "The IBGE (Brazilian Institute of Geography and Statistics) and the Brazilian Association of Bars and Restau-

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rants realize that 25% of Brazilians’ spending with food are out of their houses and that this percentage may reach 40% in the next 15 year." Wheelwright (1984) once defined as the basic purpose of a strategy is to develop and support a durable competitive advantage, which may be able to answer the questions about the continuing activities of some companies over others. Based on the concept of Cone Sand Model, created by Ferdows and De Meyer (1990), which contains quality as the support base, it seeks to respond: why some small business segment restaurants are able to maintain their activities, while others do not have the same success?

2 Literature Review The food service industry is one that has shown significant rise, according to ABRASEL (2012). This is due to the increasing trend in the number of meals outside the home, as well as the number of establishments that provide varied options for lunch, happy hour and dinner, from the traditional "a la carte", self - service buffet, bars, deliveries and others. The research informs approximately one million food companies registered, distributed among bars, restaurants and similar activities, accounting for approximately 2.4% of Brazilian GDP. In the same publication, in 2008 the revenue of the sector was close to 25 billion dollars, an increase of 5% in the activities compared to the previous year and also indicates that almost 26% of Brazilian spending are outside of households, therefore approximately one quarter of the population usually have their meals in restaurants, bars and similar establishments. In this context, SEBRAE (2012) reports that the food industry away from home grew by 13.8% from 2007 to 2008 and according to the Household Budget Survey (POF 2008/09) made by the Brazilian Institute of Geography and Statistics - IBGE (2012), "in six years, the urban share of outside the home food in spending on food rose a quarter (25.7%) to one-third (33.1%), and the meantime rural increased from 13.1% to 17.5%."

2.1 Entrepreneurship In the last decades, in Brazil, the subject entrepreneurship has been frequently addressed by several authors that generate hypotheses related to natural aspects of human beings, as well as development of professional skills. For Dolabela (2008), the term entrepreneurship is known and referenced since many years, which means that is not innovation anymore. Considered an upgrade to business models, Dornelas (2005) argues that we are living in the era of entrepreneurship, while 199


other authors (Schramm and Litan, 2008) are limited to characterize the stage as the beginning of an entrepreneurial capitalism. People are attracted to the venture by numerous incentives or rewards that can be grouped basically into three categories: profit, independence and a joyful lifestyle (Longenecker, Moore and Petty, 2004). Entrepreneurship originated "primarily in the United States, a country where capitalism is the main feature” (Dornelas, 2005, p.17). Dornelas (2005, p.15) describes entrepreneurship as "the involvement of people and processes that collectively lead to the transformation of ideas into opportunities." With an economic scenario that is constantly in motion, new needs arise all the time, with strong appreciation to the ability of an entrepreneur to find opportunities and transforming ideas into business. The entrepreneur becomes a responsible player for generating income, moving the economy through the absorption of hand labor, innovating and diversifying the context in which it operates. On the other hand, some studies suggest caution with the common stereotype of the entrepreneur who usually emphasizes characteristics such as need for achievement, willingness to take moderate risks, and a strong self-confidence. Considering only these qualities, it should be noted that there is no scientific proof of the importance of these traits and that individuals who do not fit this profile, they can still succeed as entrepreneurs (Longenecker, Moore and Petty, 2004). It is common for entrepreneurs to feel attracted to the food sector due to the tradition of being a market that provides high short term profit and for being establishments able to provide service along with consumer items, taking advantage of strong trend and need of people perform their daily meals away from home (ABRASEL, 2012). In this sense, the concept of Fitzsimmons and Fitzsimmons (2000) can be pointed out by considering that the services are at the center of economic activity in any society. The authors also highlight the importance of restaurants because they belong to the group of social / personal services, which is essential to attend one of the main human needs, food. The fact is that economically, entrepreneurs are "eliminating trade and cultural barriers, shortening distances, globalizing and renewing economic concepts, creating new working relationships and new jobs, breaking paradigms and generating wealth for society (Dornelas, 2005, p. 6)." In this search for breaking paradigms, many companies question themselves over which area should be concerned about quality. Duran and Gryna (1991) stand for the idea that each specialized department is responsible for implementing its designated function, as well as the execution of certain business functions such as human relations, finance and quality. Thus, it is understood that in addition to the company intends to run, quality is a feature that should be inherent in any operation. So, the role of quality in business sphere enhances the concept that the quality of product and service is the gathering force of all departments, with a single goal: to meet the needs and expectations of customers (Falconi, 1999).

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2.2 Quality According J.M Duran and Frank M. Gryna (1991, p. 11), "quality is the specification of a product at the expense of customer needs, enabling satisfy them regarding to the product." Companies providing services and care to offer a quality service, measuring and exceeding customer expectations, are being effective in their activity. For Berry (1996), strategically, the role of quality services should support the principles of: Credibility (offering reliable services); Surprise (surprise customers and extrapolate their expectations); Recovery (if the service was poor, seek regain customer) and Integrity (respect between company and customer). As long as well defined, these fundamentals are important to strengthen the appreciation of service by the customer, and can even affect the perceived cost-benefit ratio for the same. For this, Las Casas (2000) aware of the need to set up a sequence of procedures that involve research, creating organizational culture, continuous training, creating an organizational climate, communication plan and process involved in the establishment of control mechanisms. For this reason, the fierce competition of operations has been characterized by the development of competitive priorities, driving companies to develop superior skills in different aspects.

2.3 Competitive Priorities Several studies have been developed to improve organizational performance. Among them, the model of cumulative priorities proposed by Nakane (1986) which provides a sequential development of competitive priorities in operations, in order to improve priorities antecedents serve to further aid without causing problems or limitations. Based on the practices of Japanese manufacturing companies that showed competitive advantage in a large amount of variables against their competition, Nakane (1986) proposed the following sequence for the development of competitive priorities: quality, timeliness, cost and flexibility. This model was reinforced by another very similar (Hall, 1987) which stated that the best priority sequence was prioritizing the base as a form of guarantee and improvement of improvements obtained in priorities near the top, like a pyramid. Important studies were done by Ferdows and De Meyer (1990), concluding data related to the European industrial organizations in 1988, but did not confirm the sequence of priorities suggested by that model. However, the data analysis of 1988 on the U.S. portion of this segment, by Roth and Miller (1992), indicated the following priorities: quality, delivery, market scope, flexibility and cost. This study aimed to find differences involving the priorities of leading companies (those that reach their full business goals) compared to companies that are followers (ones the part that reach just part of their business goals). 201


Contrary to the idea of focusing on a single gain competitive advantage or competitive trade-offs, Ferdows and De Meyer (1990) found that static method, compromising the monitoring of the dynamics of the external environment. To do this, create a new concept or model and named the Earl of Sand (Sand Cone). They have improved the study of competitive priorities cumulative model subsequently through a slightly different sequence. Ferdows and De Meyer (1990) believed that quality and punctuality should be based on priorities, serving as a starting point and further flexibility (and in his study, meaning responsiveness) and cost, as the latest improvement to be observed in operations. They called this pyramidal structure of competitive priorities Sand Cone. In general, studies involving the cumulative model has always been linked to tests that aimed to validate a sequence of development priorities, but without empirical validation of success recorded so far, making it the subject of discussions about its applicability due to noticeable stiffness that presents itself and its limitations. It is also known that such studies were limited to validate the ability to develop a set of two or more concurrent priorities in the same organization and is not considered synonymous with sequential development test by the authors. About rigidity aspect, Ferdows and De Meyer (1990) stated that unless a company is developing its operations below the levels of qualification in its field, it should maintain focus on priorities more problematic, in order to categorize these as paramount.

Fig. 1 Cone Sand (Sand Cone). Source: Carvalho, 2005, p. 32 adapted from Ferdows and De Meyer (1990)

Despite the difficulty of validating a model of cumulative priorities, this study aimed to find empirical evidence on the assumption that quality is the priority that underpins all other improvements. Once chosen and tested, the model can oppose or extend the model of competitive priorities Cone Sand Theory. This study may also remain without conclusive findings, as others already tested or come to the conclusion that more closely resembles a choice of this or that, with no trade-offs. Therefore, these are the following are hypotheses of this research: H1: the suggested sequence for the development of competitive priorities is the one proposed by Ferdows and De Mayer (1990); H2: quality is the first competitive priority to be developed, but does not follow the model proposed by Ferdows and De Mayer (1990), and 202


H3: There is positive reflection of competitive priorities model on economic performance and the sustainability of the company studied.

3 Methodology This chapter discussed the methodology used to collect data from this study, that according Thums (2000), should not be considered only a secondary knowledge, but the condition instrument of accomplishing something. It is understood then, that the method guides and facilitates the researcher to develop a search. For Thums (2003), the methodology is the form or manner of accomplishing something. Therefore, it was defined the case study as a research strategy, the preparation and data collection, analysis of their evidence and prepare a roadmap where it observes the need and relevance of large and deep issues, as proposed by Yin (2010 ). For the development of this case study, a qualitative study was carried out based on a semi-structured questionnaire with closed questions. This research was conducted through random interviews with customers of the restaurant, because according to Malhotra (2005), qualitative research with small samples takes place to able context understanding and comprehension in which it is inserted. As a support tool in the analysis of correlation of data obtained from surveys, the present study used the IBM SPSS Statistics software version 18, which is able to suggest if there is an association between the questions and answer choices that result in a Pearson coefficient of less than 5%. According to Roesch (1999), in the case of small and medium businesses, the definition of the target costumer, usually involves the entire organization in their restructuring proposals. The purpose of this study was to develop a market research, addressing the Nostro Sabore restaurant clients, aiming to know your main preferences, needs and motivations. Therefore, the survey was conducted using a sample of 198 respondents representing a population of 8,000 clients monthly object of study, located in Porto Alegre (Brazil). The survey instrument used was a questionnaire that consisted of 7 questions with several sub items seeking to relate the respondents' answers to the reasons that led them to attend the object of study. The sample size was calculated statistically inferred confidence level of 95% in the results.

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4 Results Presentation The tables below present the results of some of the questions in the questionnaire: Table 1 Correlation between questions 1 and 7 of the questionnaire 1 – How often do you come to Nostro Sabore Restaurant? x 7 – Come for the quality e variety of the hot dishes? Options No / Residual Adjust Yes Once a week 38 / 0,2 36 Twice a week 13 / -1,5 21 Three times a week 11 / -1,6 19 Four times a week or more 37 / 2,3 22 Total 99

/ Residual Adjust / -0,2 / 1,5 / 1,6 / -2,3 98

Table 2 Chi-square (χ2) de Pearson Test of Table 1 Value df Chi-square de Pearson Test 7,878ª 3 Probability Reason 7,964 3 Linear Association 1,227 1 Number of Valid Cases 197 a. 0 cells (,0%) count less than 5. The minimum value is 14,92

Bi-lateral Test 0,049 0,047 0,268

As the test of Pearson Coefficient shown in Table 2, there is an association between "How often come to the Nostro Sabore Restaurant and attend for quality and variety of hot dishes" because the p-value resulted in 0.049, the indicates that the association between the two variables. Even through the analysis of adjusted residuals, you can check that customers, who frequent the restaurant 4 or more times a week, do not do it based on the quality and variety of hot dishes. Table 3 Correlation between questions 1 e 4.4 from questionnaire 1 - How often do you come to Nostro Sabore Restaurant? x 7 – Come for quality and variety of meat? Options No / Residual Adjust Yes Once a week 61 / 3,1 13 Twice a week 18 / -2,3 16 Three times a week 16 / -2 14 Four times a week 42 / 0,2 18 Total 137 61

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/ Residual Adjust / -3,1 / 2,3 /2 / -0,2

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 4 Chi-square (χ2) Pearson Test of Table 3 Value df Pearson chi-square Test 13,856ª 3 Probability Reason 13,991 3 Linear Association 2,736 1 Number of Valid Cases 198 a. 0 cells (,0%) count less than 5. The minimum value is 9,24

Bi-lateral Test 0,003 0,003 0,098

Table 4 shows the intersection between issues 1 and 4.4 dividing the results by frequency band. The chi-square test presented in Table 29 was significant at 5% (p-value = 0.003), demonstrating that there is an association between the questions: How often do you come to the Nostro Sabore Restaurant? Do you come for the quality and variety of meat? The direction of the association is observed through analysis of the residue adjusted suggesting that those who attend the restaurant two or three times a week, they do so depending on the quality and variety of meats, while other attending only once or four times or more per week, do not take this fact into account. Table 5 Correlation between questions 1 and 4.8 1 – How often do you come to Nostro Sabore Restaurant?? x 4,8 – Come for nice and fast service? Options No / Residual Adjust Once a week 58 / 1,9 Twice a week 24 / 0,1 Three times a week 14 / -3,1 Four times a week or more 43 / 0,3 Total 139

Yes 16 10 16 17 59

/ Residual Adjust / -1,9 / -0,1 / 3,1 / -0,3

Table 6 Chi-square (χ2) Pearson Test of Table 5 Value df Pearson chi-square Test 10,373ª 3 Probability Reason 9,775 3 Linear Association 1,947 1 Number of Valid Cases 198 a. 0 cells (,0%) count less than 5. The minimum value is 8,94.

Bi-lateral Test 0,016 0,021 0,163

Table 6 lists the above questions 1 and 4.8, in order to verify whether there is an association between the questions: How often do you come to the restaurant Nostro Sabore? Do you come for nice and fast service? The Pearson coefficient obtained in Table 31 (p-value = 0.016) suggests a relationship between people 205


who frequent the restaurant 3 times a week and the service friendly and responsive, because the analysis of their respective adjustment waste. Table 7 Correlation between issues 1 and 7.4 1- How often do you come to Nostro Sabore Restaurant? X 7.4 – Come for the easiness due the location? Options

No

/ Residual Adjust

Yes

/ Residual Adjust

Once a week Twice a week Three times a week Four times a week or more Total

51 15 12 15 93

/ 4,8 / -0,4 / -0,8 / -4,1

23 19 18 45 105

/ -4,8 / 0,4 / 0,8 / 4,1

Table 8 Chi-square (χ2) Pearson Test of Table 7

Chi-square Pearson Test Probability Reason Linear Association

Value

df

26,636ª 27,513

3 3

25,348

1

Bi-lateral Test 0,00 0,00 0,00

198 Number of Valid Cases a. 0 cells (,0%) count less than 5. The minimum value is 14,09.

The correlation between the questions: How often do you come to the Nostro Sabore Restaurant? Come for the easiness due to the location? It can be seen in Table 8, with the division schedules. According to the resulting p-value (0.000), there is indication of a strong association between the location and frequency of those going four or more times weekly, in Nostro Sabore.

5 Conclusion This study was an opportunity to test a theory that values an important characteristic which is quality, analyzed from the consumer point of view. In considering whether there is a relationship between these features found in the questionnaire responses and priority competitive Cone Sand Theory, one could suggest that the base of the pyramid Cone Sand proposed by Ferdows and De Meyer (1999), find similarity to the study conducted at Restaurant Nostro Sabore Restaurant. The quality is perceived as relevant by customers who attend 2 to 3 times and appreciate the quality and variety of meats and hot dishes. The competitive priority relia-

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bility relates to the satisfaction of those who attend 1-2 times per week and highlight satisfaction with meals. The location is a major factor in deciding where to lunch, while cost efficiency does not seem to be relevant in choosing this property for 64.6% (128 people in the sample). There were no significant demands for fast delivery, in this case represented by the friendliness of the waiters and agility, as determinant of choice for this organization for 70.2% (139 people). For reasons of space, several tables were omitted from the analysis of this study. Thus, no relationship was observed between the order of competitive priorities (quality, reliability, speed and cost) established by the authors (Ferdows and DE MEYER, 1990) and the continuity of this restaurant, and the quality factor important association with its sustainability. Therefore, the Sand Cone model is validated by this specific case study for this organization. About the research hypotheses mentioned, we found that H2 and H3 were confirmed, and H2: "quality is the first priority competitive to be developed, but does not follow the model proposed by Ferdows and De Mayer (1990)" and H3: "There is a positive reflection of the model competitive priorities on economic performance and the sustainability of the company researched." Both were coherent with the results obtained in this work. It is suggested to continue the study, by conducting further research on investigative nature that enable monitoring and external market dynamics, opposed the idea of gain competitive advantage through a single competitive advantage or trade-offs, as encouraged by the authors Ferdows and De Meyer (1990) through the theory of Sand Cone.

6 References Abia (2012) Associação Brasileira Indústrias de Alimentação. Available at: < http://www.abia.org.br/default.asp>. Accessed in: May, 2012 Abrasel (2012) Associação Brasileira de Bares e Restaurantes. Available at: . Accessed in: May, 2012 Berry, L (1996) Serviços de Satisfação Máxima. Rio de Janeiro: Campus Carvalho, R (2005) Estratégias de operações na indústria metal-mecânica brasileira: formulação, implementação e impactos sobre o desempenho empresarial. Business Dissertation, Universidade Federal do Rio de Janeiro, RJ, 2005 Chacon, L (2011) Agito na cozinha reflete movimento intenso da rua. Available at: Accessed in: April, 2011 Dolabela, F (2008) O segredo de Luísa. Rio de Janeiro: Sextante Dornelas, JCA (2005) Empreendedorismo: transformando idéias em negócios. 2.ed. Rio de Janeiro: Elsevier Falconi, C (1999) Controle da qualidade total: no estilo japonês. Minas Gerais: Fundação Cristiano Ottoni

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Ferdows, K; De Meyer, A (1990) Lasting improvements in manufacturing: in search of a new theory. J. Operations Management. Vol. 9, n. 2, p.168-184 Fitzsimmons, JA; Fitzsimmons, M (2000) Administração de serviços – operação estratégia e tecnologia de informação. Porto Alegre, Bookmann Hall, R (1987) Attaining Manufacturing Excellence. Homewood: Dow Jones-Irwin Ibge (2000) Available at: . Accessed in: May, 2012 Las Casas, AL (2000) Marketing de serviços. 2ed. São Paulo: Atlas Longenecker, JG; Moore, CW; Petty, JW (2004) Administração de pequenas empresas. São Paulo: Pearson Malhotra, N et al (2005) Introdução à pesquisa de marketing. São Paulo: Prentice Hall Nakane, J (1986) Manufacturing Futures Survey in Japan, A Comparative Survey 1983-1986. Tokio, System Science Institute Paiva Jr, FG; Cordeiro, AT (2002) Empreendedorismo e o Espírito Empreendedor: Uma Análise da Evolução dos Estudos na Produção Acadêmica Brasileira. Anais do XXVI Encontro Nacional da ANPAD. Salvador Roth, AV; Miller, JG (1992) Success Factors in Manufacturing. Business Horizons, pp.73-81, v.35, n.4 Schramm, C; Litan, RE (2008) The Growth solution. The American, july/august, 32-38. Sebrae (2011). Available at: Accessed in: November, 2011 Sebrae (2011) Como gerir uma empresa familiar. Available at: Thums, J (2000) Acesso à realidade. Canoas: Ulbra Thums, J (2003) Acesso à realidade: técnicas de pesquisa e construção do conhecimento. Canoas: Ulbra Wheelwright, S (1984) Defining the Missing Link. Strategic Management Journal. V5, pp.77-91 Yin, RK (2005) Estudo de caso: planejamento e métodos. Porto Alegre: Bookmann

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CBA and CEA Analysis on Occupational Safety and Health. A New Proposal for Investment Decisions Cuervo MA1 Abstract Cost-Benefit Analysis (CBA) and Cost-Effectiveness Analysis (CEA) are currently the two analysis techniques most widely used for making investment decisions between alternative projects. However, results obtained from both types of analysis occasionally can be disparate and complicate the final decision. Occupational health and safety is an area where it is possible to apply CBA and CEA to optimize reduction of accidents. Quality of results achieved depends on reliability of the estimations of accidents cost and investment returns in terms of accidents reduction. Adopting Brody graphic model of costs, this article criticizes CBA and CEA methods and develops and tests an alternative way for decision analysis that seeks to surpass the previous two.

Keywords: Accidents, Cost, CBA, CEA.

1 CBA & CEA in the occupational health area In order to guide policy decisions about allocation of resources to projects to improve health level in workplace, mainly two types of analysis have traditionally been used: CBA and CEA. While there are other similar types of analysis, these two are definitely the most widespread in health field (Polindera S et al., 2011). The aim of both options is the most appropriate project selection, ie, more profitable or efficient, to invest between different alternatives. The CBA is a process for calculating and comparing economic costs and benefits of different projects, thus achieving the economic efficiency information of each one and providing the most cost-effective choice. On the other hand, CEA consists 1Miguel

Angel Cuervo Blanco ( e-mail: [email protected]) Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid.

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of obtaining for each project efficiency results in terms of reduced accidents rate versus claims, choosing the most efficient one. For the application of CBA it is unavoidable quantifying the economic benefits, that is, the reduction obtained in costs associated with workplace accidents. The application of the CEA presents fewer problems, as it only requires measuring relative reduction of workplace accidents. In the particular case of CBA, results are conditioned by the method used for measuring economic benefits associated with the reduction in accidents, so that using different methods may yield different results. In this regard, numerous studies point to the difficulty of quantifying such costs as they include hard-tomeasure concepts such as the value of human life or health. It´s noteworthy that authors such as JT Hamilton and WK Viscusi highlight the lack of rigor in many of the analysis conducted (Kuchler F, Golan W, 1996). So it seems indisputable that performance results obtained from this type of analysis should be at least taken with extreme caution. Consequently, conclusions drawn cannot determine whether the more profitable project is the most convenient in relation to their effectiveness in reducing accidents, as it does not provide such information. CEA does not suffer the problem of quantifying economic benefits associated with accidents, but otherwise it doesn´t determine which projects are economically profitable, a crucial issue in an economy with limited resources. Finally, it must be said that these analysis do not use to incorporate considerations about time horizon and sustainability of investments made, or even if they do, they do not take into account the variability over time of efficiency of the action taken and ROI obtained. In view of the disadvantages described is not surprising that conclusions drawn from CBA and CEA can easily be mixed or, as we shall see, even antagonistic.

2 Brody Graphic Model for Company Accidents Costs Most studies analyzing business costs involved in workplace accidents have simply tried to quantify them, assuming that reducing those costs is inevitably achieved by reduction in accidents. This seemingly logical conclusion is derived from considering only those costs incurred ex - post, ie caused by consequences of the claims incurred, regardless of ex – ante costs, ie those aimed at preventing accidents in the company. Brody et al. (Brody B et al., 1990), based on previous models form other authors (Oi W, 1986. Andreoni D, 1986), presented a graphical model for costs of company claims in which both types of costs, ex - ante and ex – post, were incorporated. Its main conclusion is that there is a non-zero level of claims for which the overall cost to the company is minimized to an optimal value.

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Brody graph model (Figure 1) has U-shaped curve representing total cost in relation to level of risk. Its morphology is based on certain assumptions set out below:  Ex – ante costs curve is an exponential curve, asymptotical to both axes, because when company risk levels are very high, small investments are enough to reduce them significantly and, conversely, when accidents rates are very low, investments must be extremely high to keep on reducing risk.  Ex - post costs curve has a fixed component, which involves insurance of human and material consequences of mishaps, and a variable component, due to indirect costs arising from the occurrence of claims (labor costs, property damages, lost production, etc.). Besides this variable component may present a positive slope increasing with risk, although authors suggest the possibility that it also may be constant.  As a result of this there is a theoretical optimal risk level in the companies that explains in practical terms their reluctance to invest in preventing accidents above a certain amount.

Fig. 1 Modelo gráfico de costes de accidentes laborales de Brody y colaboradores.

For CBA and CEA purposes, it is reasonable to interpret the level of risk in the horizontal axis as the accidents rate, as they are equivalent concepts at the aggregate level and accidents rate is more appropriate to derive costs from it.

211


3 CBA and CEA over Brody Model: a Contradictory Results Case Company resources optimization management on prevention of occupational risks requires employing these resources in those areas or issues where they are most effective for reducing accidents. So, formally, the problem that arises is to determine the right allocation of resources over time among various areas in order to obtain the maximum reduction in accidents. To illustrate a practical application of CBA and CEA techniques on Brody model, total and ex - ante costs curves for two business sectors are shown in Figure 2. A similar investment for risk prevention is applied for both sectors to verify what the effects obtained are and to determine which one is most suitable for such investment. It can be seen that, from the point of view of economic efficiency, sector 1 generates a significant economic return while for sector 2 there is an increase of the total cost, so according to CBA, sector 1 would be chosen as the recipient of the investment. But, on the other hand, we see that the same investment generates a significantly higher accident rate reduction in sector 2 than in sector 1, so according to CEA analysis sector 2 would be selected. It is clear that both assays are contradictory in their results. In addition, it must be added that neither time horizon nor returns produced are considered. Therefore, it is necessary to find an optimal solution which is consistent and takes into account time factor influence.

Fig. 2 CBA and CEA effects on two business sectors.

212


4 Formal Definition of Graphic Costs Model and Proposal on Decision Analysis This section presents the proposed investment decision analysis over a formally defined Brody model. For the sake of clarity in the representation of the model and in order to illustrate the problem statement, we will work on a model with only two elements, in this case business sectors. The aim is to properly allocate investments for a maximum reduction of accidents over time onto the two combined sectors. In order to achieve a further mathematical simplification of the model, it is assumed that ex - post costs curves show quadratic forms for both sectors. This particularity does not affect the validity of final conclusions, which will be similar for other forms of ex - post costs curves as long as their slopes are positive and increasing. Let it be a productive sector be and let y A be a curve relating the joint investment by companies belonging to this sector in prevention of occupational hazards with the level of claims (ex – ante costs). Let y B be a curve representing work accidents associated costs for companies belonging to the sector (ex – post costs). The total costs curve

yC

for workplace accidents results from the sum of the two

mentioned curves. The mathematical formulation of curves can be expressed as follows.

 x  yC    x 2   x

yA 

y B  x 2  

Suppose a set s of companies spread over two productive sectors a and b. Let

y a , yb curve

be the total costs curves for workplace accidents in the two sectors. The

ys

for total claims costs in s results from the sum of the two previous

curves. Accidents rates must be considered in absolute terms, so that overall rate is the sum of business sectors accident rates.

ys  ya  yb yb 

b xb

ya 

a xa

  b xb   b 2

213

  a xa   a 2


Let N be the total number of periods for which it´s required to optimize the distributive calculation of investment for the two existing productive sectors. Let n = 1,2,3, ..., N be each period. Let

Rn

be the available investment budget over the

period n to reduce accidents on s. The goal is to reduce to an absolute minimum the accidents ratios produced during the course of the N periods. To achieve this aim the various

Rn

should be properly distributed among sectors a and b.

To address the problem raised, different considerations must be made:  It is necessary to define the total number of periods N, as it will determine the final result of reduction of accidents and it will condition the distributive optimal allocation of

Rn

between a and b.

 It is possible to consider a constant budget allocation ratio between a and b for all periods or to introduce the possibility of variation of this ratio between different periods in order to achieve optimum results.  In order to calculate the available budget to invest in period n+1, it is possible to consider the return obtained in period n, or to consider a wider delay for applying the return. Let

Rna , Rnb be the allocated budgets in period n to a and b sectors respective-

ly, so that

Rn  Rna  Rnb . Let´s take sector a and let y nAai , ynAaf

be the initial

and final investment levels for this sector in period n, so that the investment is

Rna  ynAa  ynAaf  ynAai . Let xnai , xnaf be the initial and final accidents rates of sector a in period n.

y nAaf 

a

y nAai 

xnaf

a xnai

Rna 

a xnaf



a xnai

From this it follows that:

xnaf 

1

xnai Rna

a

xnai

Developing equations previously raised over time, the following expressions can be achieved, which determine accidents rate obtained after n periods and total reduction in accidents.

214


x naf 

1 n

x1ai Rna

a

x1ai n

xna  xnaf  x1ai  

Rna

a

1 n

x1ai

Rna

a

2

x1ai

In the above formula, a constant amount of investment taking into account a global investment

Rn

Rna

has been assumed

also constant and a fixed inversion

distribution ratio between sectors a and b. Assuming a variation in the amounts

Rna

invested, the formulas obtained are as follows.

x1ai

xnaf 

n

1

R

na

1

a

x1ai

In a similar way, values for sector b could be obtained. The problem becomes more complex and meaningful when it is stated that the amounts

Rn

invested are dependent on returns coming from previous periods, as

it occurs when past surpluses are used for new investments in the future. In this case, recursive equations are obtained since final level reached depends on investments made and, in turn, these investments depend on previously existing accidents rate. To make a mathematical formulation of the above, sector a will be taken to analyze how

Rna

are obtained based on investment returns achieved. These amounts

depend in turn on what happens in all sectors of activity, in this case only sectors a and b, among which available budget is distributed each period. For the purposes of this example, it will be checked if there is an optimal value of the distribution ratio of investment between sectors. It is posed that there is a constant budget allocation

R0

to invest in each period

in occupational safety for the whole set of sectors, and that investment returns that are payable in the immediately following period. To calculate these returns the difference between initial and final cost of s must be known. This difference will 215


depend on the amount of investment in the period and the distribution ratio between sectors. The cost value of the two sectors set is obtained according to the following formula.

y s  y a  yb 

a xa

  a xa   a  2

b xb

  b xb   b 2

And the difference in cost for each period or return on investment is as follows.

y ns  y nsf  y nsi 

a  2 2   a xnaf   a  b   b xnbf   b xnaf xnbf

   2 2   a   a xnai   a  b   b xnbi   b  xnbi  xnai  Operating the above equation and taking into account that

xnaf 

1

xnai Rna

a

xnai

It follows that

y ns  Rn   a x

3 nai

Rna

2

Rna

a

xnai

 a 1  Rna x  a nai

 b x

3 nbi

Rnb

2

Rnb

b

xnbi

 b 1  Rnb x  b nbi

Thus, the amount available each year for investment in risk prevention in the set s consists of the fixed component

plus the investment return y s ( n1)

R0

earned in the previous period.

Rn  R0  y( n1) s Depending on the distribution ratio,

Rn

will be distributed among the sectors a

and b ( Rna , Rnb ) and a new ROI will be yielded and applied to the next period. Applying the following equations, a final value of accidents rate for sectors a and b is obtained after n periods, and therefore for the whole set of sectors.

216


x1ai

xnaf  1

R

na

1

a

x1bi

xnbf 

n

n

1

x1ai

R

nb

1

b

x1bi

In summary, given the costs curves associated with accidents and the regular amounts of investment in risk prevention for the whole set of sectors, the above equations allow to search the optimal distribution of investment between the two sectors that will lead to a maximum cumulative reduction of claims. The example below shows the calculation of the optimal ratio for any couple N,

R0

so that the lowest possible total cumulative value of claims for all sectors is

achieved. Let a and b be two sectors with the following cost curves.

ya 

54000 2  xa  10 xa

yb 

6750 2  xb  50 xb

The following initial accidents rates are assumed.

x1bi  30

x1ai  40

Also, let N=100 be the number of periods considered to optimize the calculus. Different initial budgets

R0

are tested on the model. In the table below (Figure

3) the levels of claims accumulated over periods of 100 are shown.

x

100 f

  x100af   x100bf

The respective optimal distribution ratios for the two sectors are also shown in Figure 3. It is again, as in the theoretical approach, that investment returns earned during a period are applied to the next exercise. It can be seen that the higher the budget

R0 , the more significant the reduction

in accidents is. Similarly it is noted that the optimum budget distribution ratio varies as the budget A graph for

R0 does. R0 =50 included

in Figure 4 shows the accidents rate evolution

along the N = 100 periods considering different budget distribution ratios. As noted, different ratios (% a) imply different rates in reducing accidents. So that depending on N it would be selected a particular ratio (% a). Consider in the graphic in Figure 3 the series with assigned distribution ratios (% a) 0 and 95, respective-

217


ly. Initially and until n=45, first series provides a more rapid reduction in claims, but from that point the second series is the more effective.

5 Conclusions Throughout this article CBA and CEA techniques of analysis for making investment decisions have been criticized in occupational health area. Besides both techniques have important intrinsic shortcomings, when applied onto Brody model they may present even contradictory results. To overcome these difficulties it is proposed a methodology for analysis with two main features: the consistency of performance and the incorporation of timeline and foresight in the analysis. Once the formal development of the method has been detailed, it has been applied to a hypothetical case where two main points have been observed: the possibility of calculating the distribution of resources to invest among the alternatives analyzed, and the importance of considering timeline and investment returns in the analysis. Thus, the exclusive selection of projects to invest advocated by CBA and CEA is overcome by a distributive budgetary allocation between projects. 1) OPTIM AL BUDGET DISTRIBUTION RATIO 80 70 60

RATIO (%a)

50 40 30 20 10 0 1

2

3

4

5

6 SERIES

218

7

8

9

10


3) ACCIDENT REDUCTION 2) AGGREGATE ACCIDENT RATE

7000,00

Ro=2

6000,00

Ro=5

5000,00

Ro=10

(%a)=0 (%a)=95 (%a)=5 (%a)=10 (%a)=15 (%a)=20 (%a)=25 (%a)=30 (%a)=35 (%a)=40 (%a)=45 (%a)=50 (%a)=55 (%a)=60 (%a)=65 (%a)=70 (%a)=75 (%a)=80 (%a)=85 (%a)=90 (%a)=100

70

Ro=20

4000,00

Ro=50

3000,00

60

Ro=100

2000,00

Ro=200

1000,00

Ro=500

0,00 0

20

40

60

80

(% a)

4)

100

Ro=100 0 Ro=500 0

AGGREGATE ACCIDENT RATES

Series

Ro

Optimal acc. rate

Optimal %a

1

2

5045,76

20

2

5

4846,88

30

3

10

4569,22

40

4

20

4129,54

50

5

50

3283,08

60

6

100

2529,93

65

7

200

1812,19

65

8

500 100 0 500 0

1058,59

70

671,65

70

227,80

75

ACCIDENT RATES

AGGREG. ACC. RATE

8000,00

50

40

30

9 10

20 0

20

40 PERIOD n

60

80

100

Fig. 3 Accident reduction results obtained for N = 100. 1) Chart of optimal budget distribution ratio (% a) in relation to Ro. 2) Curves of the cumulative values of accident rates based on the ratio (% a) for different Ro. 3) Total accident reduction curves with Ro=50 and different ratios (% a). 4) Table of accident accumulated values obtained for different Ro.

6 References Polindera S, Segui-Gomez M, Toet H, Belta E, Sethid D, Racioppid F, F. van Beecka E (2011) Systematic review and quality assessment of economic evaluation studies of injury prevention. Accident Analysis and Prevention

219

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Kuchler F, Golan W (1996) Assigning values to life. Comparing methods for valuing health. Agricultural Economic Report No. 784: 37 Brody B, Letourneau Y, Poirier A. (1990) An indirect cost theory of work accident prevention. Journal of occupational accidents. Andreoni D. (1986) The cost of Occupational Accidents and Diseases. I.L.O., Geneva, Switzerland Oi W. (1974) On the economics of industrial safety. Law and Contemporary Problems, 38: 538555.

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New Technologies and Entrepreneurial Intention Martin-Cruz N1, Rodriguez-Escudero AI2 Abstract New technologies are considered a powerful tool to create, disseminate, articulate and exploit knowledge. Recently, some technologies are being used to promote the creation of new ventures. However, recent studies demonstrate that new technologies are not enough to enhance the process of venture creation. We use the fundamentals of the theory of planned behavior to understand the impact of new technologies on entrepreneurial intention. Empirical literature related to university students shows that entrepreneurial intention is depen-dent on attitude towards entrepreneurship, social norms and self-efficacy. Our aim is to evaluate an empirical model in a sample of students enrolled in the last academic year in the University of Valladolid (Spain).

Keywords: Entrepreneurship, Entrepreneurial intentions, New Technologies, Theory of Planned Behavior.

1 Introduction New technologies are considered a powerful tool to create, disseminate, articulate and exploit knowledge. Recently, they are being used to promote the creation of new ventures (Field, Elbert and Moser, 2012; Martin, Platis, Malita and Ardeleanu, 2011). However, the effect of new tech-nologies on entrepreneurial intention is still lacking. In this paper, we use the fundamentals of the theory of planned behavior to understand the impact of new technologies on entrepreneurial inten-

1Natalia

Martin-Cruz ( e-mail: [email protected]) Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Facultad de Ciencias Económicas y Empresariales. Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid. 2Ana

Isabel Rodriguez-Escudero ( e-mail: [email protected]) Grupo INSISOC Dpto. de Organización de Empresas y CIM. Facultad de Ciencias Económicas y Empresariales. Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid.

221


tion. In particular, we focus on two specific objectives: 1) verify the potential of the planned behavior theory based on the three dimensions –attitude towards entrepreneurship, social norms and self-efficacy- and some control variables, and 2) verify the impact of a positive attitude towards new technologies on entrepreneurial intention) To reach those objectives, we use two models. The first model includes solely the attitude to-wards new technologies, and in the second model, we add the rest of the personal features of the individual, as the upper echelon characteristics, education, personality or the family business background (Choy, Kuppusamy y Jusoh, 2005; Veciana, Aponte y Urbano, 2005; Li, 2007; Martin, Hernangomez, Rodríguez y Saboia, 2009; Engle, Dimitriadi, Gavidia, Schlaegel, Delanoe, Alvarado, He, Buame y Wolff, 2010). Once all those variables are controlled, we claim that attitude towards new technologies maintain its significance, therefore, that will mean this variable is important to identify individuals with a higher entrepreneurial intention. This observation will allow for promoting specific programs to those individuals from public and private institutions.

2 Theoretical Background The theory of planned behavior (Ajzen, 1991) has been applied to nearly all voluntary behaviors and it provides quite good results in very diverse fields (Azjen, 2011; Liñan, Rodríguez-Cohard, and Rueda, 2011). Accordingly, a narrow relationship would exist between the intention to be an entrepreneur and its effective performance. Therefore, intention becomes the fundamental element in explaining behavior Following this theory, three main elements constitute the explanatory variables of intention: self-efficacy, social norms and attitude towards entrepreneurship. Self-efficacy or entrepreneurial capabilities is defined as the perception of the easiness or difficulty in the fulfilment of the behaviour of interest, that is, the sense of capacity regarding the fulfilment of firm creations behaviours. Social norms measure the social value attributed to entrepreneurial behaviour. Finally attitude towards entrepreneurship refers to the degree to which the individual holds a positive or negative personal valuation about being an entrepreneur. Besides the three variables commented, different authors have identified additional features that may also explain entrepreneurial intention. In this sense, some demographic characteristics (such as gender and social class), the education (training, languages, academic performance), the existence of entrepreneurial tradition in the family and personal traits have been widely considered in the literature (Minniti and Nardone, 2007; Matthews and Moser, 1996; Kor et al., 2007; Rauch and Frese, 2007). Although planned behaviour theory seems to prevail in recent entrepreneurship research, other schools had an impact characterizing and explain222


ing why some individuals become entrepreneurs. The Great Person School focuses on intuition of the individual, and his/her with unique values and attitudes such as the need for self-fulfilment. From the psychological literature it has been argued that entrepreneurs have a higher propensity to take. The management literature has emphasized the capabilities for innovation and for organising re-sources, or the ability for leadership (Cunningham and Lischeron, 1991). Considering both streams of literature, the empirical analysis includes those variables to verify which ones have a stronger influence on the intention to startup. The model proposed is shown in Figure 1. Socio-demographic features (gender, budget) Education (Training, languages, academic performance) Entrepreneurial tradition in the family

Self-efficacy

Attitude towards entrepreneurship

Personal traits

Entrepreneurial intention

Social norms

Attitude towards new technologies

Fig. 1 Model of the planned behavior theory considering the impact of new technologies on entrepreneurial intention

New technologies are included into the model by considering the attitude of the individual to-wards those new technologies. In fact, institutional theory acknowledges that certain new technologies come to be adopted widely, while other, equally plausible, alternatives languish (Tushman and Anderson 1986; Utterback 1994). Munir and Phillips (2005) have tried to disentangle the role of entrepreneurial institutions to that choice. They developed, using the observation from discourse analysis, that technologies can become a type of institution through processes of social construction, provides a very useful foundation for the development of an institutional theory of technology that will strengthen both technology and innovation research and institutional theory (Munir and Phillips, 2005, 1684). Moreover, the accumulated tacit knowledge and culture of the entrepreneur are the resources essential to create wealth from research commercialization leading to technological innovation (Hindle and Yencken, 2004). We believe that the development of a positive attitude towards new technologies could be the starting point to initiate the entrepreneurial career as means to develop new technologies.

223


3 Methodology Our aim is to evaluate the model presented in Figure 1 in a sample of students enrolled in the last academic year in the University of Valladolid (Spain). We collected information by means of a questionnaire during the period February-March 2013. A total of 183 complete questionnaires were obtained. We focus on young people since this group contains the largest proportion of entrepreneurs in the EU (CEEDR, Middlesex University, 2000). In fact, there is a particular interest of the European Union promoting entrepreneurship and policies as the Programme for the Competitiveness of enterprises and SMEs (COSME) 2014-2020 is being discussed. Table 1 summarizes a characterization of sample in terms of gender, age and type of studies, social class, academic performance, entrepreneurial tradition in the family, job experience, and previous entrepreneurial experience. Table 1 Sample characteristics Gender (%)

Age (%)

Type of studies (%)

Female

54.1

20 to 22

31.8

Business

47.5

Male

45.9

23 to 25

59.2

Business and Law

13.1

More than 25

9.0

Industrial Engineering

10.9

Organizational Engineering

28.4

Social class (budget) (%)

Academic performance (%)

Entrepreneurial tradition in the family (%)

Low

0.5

Very low

0

No

48.1

Medium-low

14.3

Low

3.9

Yes

51.9

Medium

64.5

Medium

16.9

Medium- high

19.1

High

53.4

High

1.1

Very high

25.8

Work experience (%)

Previous entrepreneurial experience (%)

Entrepreneurship intention (%)

No

56.3

No

95.1

No

43.7

Yes

43.7

Yes

2.2

Yes

56.3

At this moment

2.7

Observation of Table 1 allows verifying the equilibrium of the sample in the majority of the variables. In fact, there are half of the students with family business relatives, with previous experience in some jobs, and half are women. Related to academic performance, half of the students have a high performance. Finally, even though almost none of the students have previous entrepreneurial experience, half of them have an intention to become entrepreneur.

224


With regards to the measurement of the variables (Table 2) we have used the Entrepreneurial Intention Questionnaire (EIQ) designed by Liñan and Chen (2009). Whenever possible, items have been built as 7-point Likert-type scales. The exceptions to this norm are the gender, the social class and the entrepreneurial traditional in the family that are dummy variables. A structural equation modeling (SEM) analysis has been used to test the research hypotheses. Between the two alternative SEM approaches, we have selected Partial Least Square (PLS) mainly because our variables are not normally distributed and because of the formative nature of some of the measures used in this research. Our model includes both latent (measured with reflective indicators) and emergent (formative) constructs. Table 2 Construct definition and measures Construct name (Alpha’s, CR, AVE) Entrepreneurial intention1

Attitude towards entrepreneurship1

Construct measurement1

Loadings

Weights

I am ready to do everything to be entrepreneur

0.916*

-

Mi personal objective is to be entrepreneur

0.931

*

-

I am decided to create a business in the next future

0.916*

-

I would want to create a business or keep working in the family business

0.742*

-

Entrepreneurs are attractive to me

0.850*

-

0.872*

-

0.875*

-

0.882*

-

0.881*

-

0.850*

-

Creating a firm and keep it will be easy to me

0.833*

-

I can control the process of business creation

0.852*

-

I know the practical details to create a business

0.798*

-

I know how to develop a business project

0.807*

-

*

-

If I had the opportunity and resources, I would be entrepreneur To be entrepreneur would give to me a lot of satisfactions

Social norms1

Entrepreneurial activity is very considered in the culture of my country The role of entrepreneur in the economy is enough considered In my culture, it is an advantage to be entrepreneur in comparison to other jobs

Selfefficacy1

If I create a firm, I will be successful

0.821

Gender (n.a)

Female /male

-

Social class (n.a.)

Very low/low/medium/high/very high

-

225

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 2 (continued) Construct definition and measures Courses of specialization in business areas (marketing, finance, etc.)

-

0.421*

Courses of developing managerial abilities

-

-0.259

Courses related to entrepreneurial activity

-

0.722*

Knowledge about foreign languages2

English knowledge

-

0.094

French knowledge

-

0.125

German knowledge

-

0.643*

Academic performance2 (n.a.)

Level of academic performance

-

Entreprenurial business tradition (n.a.)

Is there any family member who has been entrepreneur (parents/grandparents/siblings)?

-

Training2

I am an outgoing person, I love chattering, having contacts and be with other people

Personal traits1

-

0.155

I am a nice person and I try to know what the others need

-

-0.032

I am very efficient at work, I am constant and I have a previous plan

-

-0.151*

I am emotionally stable, I am usually not surpassed by problems

-

0.078

I am independent and I have my own ideas, I do not copy others ideas

-

0.172*

I think that my results depend on me and not on the external factors

-

0.001

I am not afraid to assume financial risks is the entrepreneurial activity would need

-

0.595*

I am always looking for new opportunities and new ways of doing things

-

0.270*

I regularly search for activities that make me happy

-

0.005

When I am happy, I usually give good ideas

-

0.200*

When someone does something good, I usually congratulate them

-

0.040

0.742*

-

0.850*

-

0.872*

-

0.875*

-

I love trying new communication technologies that are launched to the market Atittude towards new technologies1

I consider myself an innovator and I buy products as soon as those are launched to the market I have a great variety of new technological products

I consider myself to have a great understanding and knowledge of new technologies 1 1= strongly disagree to 7 = strongly agree. 2 1= very low to 7= very high.

226


In particular, training, knowledge about foreign languages and personal traits are formative variables, and entrepreneurial intention, attitude towards entrepreneurship, social norm, self-efficacy and attitude towards new technologies are reflective variables. Variables that are measured using a single item have not been included as this analysis has no sense. For formative constructs, in Table 2 weights instead of loadings are reported. Item weight represents its relative contribution in the formation of the corresponding construct. It is necessary to bear in mind that neither is it assumed nor required that formative indicators are correlated; therefore, traditional measures of internal consistency and validity assessment are inappropriate and illogical (Bollen, 1989; Chin, 1998; Hulland, 1999). This explains why the information about CR and AVE in Tables 3 is not shown for this type of variables. We estimated our model using SmartPLS (Ringle et al., 2005). Following the two-step approach suggested by Anderson and Gerbing (1988), before the testing and assessment of the structural model, we analyzed the reliability of individual reflective items and the corresponding constructs, as well as the convergent validity and discriminant validity of our measures. As can be observed in Table 2, all the reflective item loadings are significant and greater than 0.7, which is the generally recommended threshold. We evaluated composite reliability using the internal consistency measure (CR) developed by Fornell and Larcker (1981). A construct is considered reliable if CR is at least 0.70 (Nunnally, 1978). We also examined the average variance extracted (AVE) of each latent construct, which should be greater than 0.5. All the reflective constructs exceed these conditions (see Table 3). Discriminant validity is established by comparing the square root of AVE (i.e. the diagonals in Table 3) with the correlations among latent variables (i.e. the offdiagonal elements in Table 3). Table 3 Composite fiability (CR), average variance extracted (AVE) and correlations 1. Entrepren. intention 2. Attitude entrpren. 3. Social norms 4. Self-efficacy 5. Gender 6. Social class 7. Training 8. Foreign languages 9. Academmic performance 10. Family business tradition 11. Personal traits 12. Attit. new technologies

CR .94

AVE .85

1. .92

2.

3.

4.

5.

6.

7.

8.

9.

.93 .92

.73 .79

.79 .15

.85 .22

.89

.91 -

.68 -

.59 -.12 .02 .29 .01 .02

.59 -.11 -.02 .32 -.02 .09

-

-

.29

-

-

.91

.73

.22 .18 .11 .26 -.09 .09

.82 -.00 .13 -.03 .10 .18

.04 .05 .10 .11

.02 .35 .05

-.11 -.03

.20

-

.27

.13

.29

.06

.12

.10

.07

-.05

-

.65

.61

.13

.59

-.08

.18

.30

.12

.08

.22

-

.26

.21

.00

.30

-.23

.10

-.00

.07

.18

.11

.30

227

10.

11.

12.

.85


For each reflective construct, the square root of its AVE should be greater than its correlation with any other construct, which means that it shares more variance with its own measures than with other constructs in the model. This condition is met in all the cases. In addition, another test of discriminant validity can be obtained by calculating the cross-loadings. It was verified that each reflective item loads more on the construct it intends to measure than on any other construct, and that each latent variable relates more to its own manifest variables than to the indicators of other constructs.

4 Results Figures 2a and 2b summarize the results of the PLS analysis performed to test two structural models. In particular, Figure 2a shows the results of a model which includes the favorable attitude towards new technologies. Figure 2b, however, presents the same model, but now include the additional antecedents emphasize by the literature. Specifically, the standardized path coefficients (β) the value of the R2 of the dependent variables are shown. Since traditional parametric tests are inappropriate when no assumption is made about the distribution of the observed variables, the level of statistical significance of the coefficients of both the measurement and the structural models was determined through a bootstrap resampling procedure (500 sub-samples were randomly generated). The estimation of the first model (Figure 1) reveal that a positive attitude towards new technologies favors the feeling of self-efficacy (Β=0.36) and this last variables has an effect on the attitude towards entrepreneurship (B=0.57) and on the entrepreneurial intention (B=0.15). Attitude towards new technologies

Β=0.36 Self-efficacy R2= 0.12

Β=0.15 Β=0.57 Attitude towards entrepreneurship R2= 0.38

Β=0.72

Entrepreneurial intention R2= 0.64

Social norms R2= 0.00

Fig. 2a Model of the planned behavior theory considering the impact of new technologies on entrepreneurial intention

228


Attitude towards new technologies Β=0.14 Training Β=0.14 Knowledge languages Academic performance

Self-efficacy 2 R = 0.44

Β=0.14

Entrepreneurial family

Β=0.45

Personal traits Β=0.18 Social class (budget)

Gender

Β=0.13 Β=0.26

Β=0.44

Attitude towards entrepreneurship R2= 0.50

Entrepreneurial intention Β=0.72 R2= 0.64

Β=-0.14 Social norms R2= 0.07

Β=0.18

Fig. 2b Model of the planned behavior theory considering the impact of new technologies and other antecedents on entrepreneurial intention

The first model does not include the rest of the variables that literature considers having an effect on the entrepreneurial intention. However, when those variables are included in the model (Figure 2) the positive attitude towards new technologies remain significant and positive (B=0.14), and therefore the rest of the effects on the attitude towards entrepreneurship (B=0.23) and on the entrepreneurial intention (B=0.13). This attitude of the students is important in the entrepreneurial intention, even though some of its effect is captured by the personal traits of the students –see the correlation of both variables in Table 3- as we can observe in the reduction of the size of the coefficient (B from 0.36 to 0.14). As a consequence, we claim that the attitude toward new technologies could help to identify those students with a higher entrepreneurial intention. Our objective is therefore accomplished. Other interesting results from the analysis are related to the variables of the planned behavioral theory. In fact, attitude towards entrepreneurship is positively related to entrepreneurial intention (Β=0.72). Moreover, self-efficacy has a positive effect on entrepreneurial intention (B=0.15) that is smaller than the one of attitude. This result means that students with higher capabilities to create a firm and sustain over time have a higher entrepreneurial intention. This relationship could be independent on the attitude towards entrepreneurship. One possible explanation to those results could be the situation of some students that consider being entrepreneur as an alternative to find a job in the marketplace. Finally, social norms have not a significant effect on entrepreneurial intention. The personal traits of students contribute creating social norms (B=0.18), as risk aversion or opportunities’ searching, however, this effect is not persistent on the relation between social 229


norms and entrepreneurial intention. Therefore, the intention to be entrepreneur is not related to the way students’ environment is considering the entrepreneurial activity. This result is consistent with previous literature, that is, variables of the planned behavioral theory have an effect on entrepreneurial intention, even though our data does not show a strong effect of the social norms. The variable ‘personal traits’ has the broadest and largest effects on the planned behavior theory variables. In fact, the outgoing, risk-taking, leader, optimistic students are the ones with higher attitude towards entrepreneurship (B=0.45), leave in an entrepreneurial environment (B=0.18) and are self-confident about being entrepreneur (B=0.44). Both, the variables ‘training’ (B=0.14) and ‘family business tradition’ (B=0.14) have an impact on self-efficacy. In fact, self-efficacy is the planned behavioral theory variable with more influences coming from the individual features of students compared to the other two variables (social norms and attitude towards entrepreneurship). Gender is significant on social norms, meaning that being women is positively related to the perception that those students have about the entrepreneurial environment (B=0.18). Women feel that the environment in which they leave is more entrepreneurial oriented. Finally, the social class has a small effect on attitude towards entrepreneurship (B=0.14).

5 Conclusion Attitude and perception about new technologies have been considered in different streams of research (e.g. agricultural technology implementation, e-banking; technology adoption). The results of the empirical literature show that individuals when new using or adopting a new technology are driven by their attitudes towards this technology (Adesina and Baidu-Forson, 1995; Kai-Ming and Enderwick, 2000; Liao and Cheung, 2002). In our study, we found in students a similar pattern; their intentions to be entrepreneur are driven by their attitude towards new technologies, for instance, they are innovation-drivers or consider themselves knowledge experts in new technologies. This relationship is important for our understanding of the drivers of entrepreneurial intention, and designing the specific training programs to promote this intention is students at the university (Fayolle, Gailly and Lassas-Clerc, 2006). The model empirically tested and based on the theory of planned behavior is still valid explaining entrepreneurial intentions. Those results are robust with previous literature (Krueger and Carsrud, 1993; Azjen, 2011; Kautonena, Van Gelderenb and Tornikoskic, 2013), which means, previous teaching practices that have been applied in Universities based on this theoretical approach could be still used to promote entrepreneurial intentions. Our study could be extended by adding other factors as the social networks in which students are part and contribute to. In fact, social networks are considered a 230


powerful tool to create, disseminate, articulate and exploit knowledge. Recently, some networks are being used to promote the creation of new ventures (Field, Elbert and Moser, 2012; Martin, Platis, Malita and Ardeleanu, 2011). The inclusion of those variables could be of interest to promote entrepreneurial intentions in students at the University

6 References Adesina, A.A. and Baidu-Forson, J. (1995): “Farmers' perceptions and adoption of new agricultural technology: evidence from analysis in Burkina Faso and Guinea, West Africa”. Agricultural Economics, 13, 1-9. Anderson, J.C. and Gerbing, D.W. (1988): “Structural equation modeling in practice: a review and recommended two-step approach”. Psychological Bulletin, 103(3), 411-423. Azjen, I (1991): “Theory of planned behavior”. Organizational Behavior and Human Decision Processes, 50, 179-211. Azjen, I. (2011): “The theory of planned behaviour: Reactions and reflections”, Psychology & Health, 26(9), 1113-1127. Bollen, K.A. (1989): Structural Equations with Latent Variables, Wiley, New York. CEEDR (2000): “Young entrepreneurs, women entrepreneurs, co-entrepreneurs and ethnic minority entrepreneurs in the European Union and Central and Eastern Europe”, Final report to the European Commission, DG Enterprise, Middlesex University Business School, UK. Chin, W.W. (1998): The partial least square approach for structural equation modeling. In Marcoulides, G.A. (Ed.), Modern Methods for Business Research, Lawrence Erlbaum Associates, Hillsdale, NJ, 295-336. Choy, C.S.; Kuppusamy, J.; Jusoh, M. (2005): “Entrepreneurial careers among business graduates: match- making using theory of planned behavior”. International Journal of Entrepreneurship, 9, 67-90. Cunningham, J. B. and Lischeron, J. (1991): “Defining entrepreneurship”. Journal of Small Business Management, 29(1), 45-61. De Carolis, D.M. ; Litzky, B.E. and Eddleston, K.A. (2009): “Why networks enhance the progress of new venture creation: The influence of social capital and cognition”, Entrepreneurship Theory and Practice, March, 527-545. Engle, L.E.; Dimitriadi, N.; Gavidia, J.V.; Schlaegel, C.; Delanoe, S.; Alvarado, I.; HE, X.; Buame, S.; Wolff, B.; (2010): “Entrepreneurial intent”. International Journal of Entrepreneurial Behaviour & Research, 16(1), 35-57. Fayolle, A, Gailly, B. and Lassas-Clerc, N., (2006): “Assessing the impact of entrepreneurship education programmes: a new methodology”. Journal of European Industrial Training, 30 (9), 701-720. Field, J.A.; Elbert, D.J. and Moser, S.B. (2012): “The use of social media in building interest in wellness on a college campus”, American Journal Of Business Education, 5(5), 515-524. Fornell, C. and Larcker, D. (1981): Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (February), 39-50. Greve, A. and Salaff, J.W. (2003): “Social networks and entrepreneurship”. Entrepreneurship Theory and Practice, March, Fall, 1-22. Hindle, K. and Yencken, J. (2004): “Public research commercialisation, entrepreneurship and new technology based firms: An integrated model”. Technovation, 24, 793-2003. Hulland, J. (1999): ”Use of partial least squares (PLS) in strategic management research: A review of four recent studies”. Strategic Management Journal, 20, 195-204.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Kai-Ming Au, A. and Enderwick, P. (2000): "A cognitive model on attitude towards technology adoption". Journal of Managerial Psychology, 15(4), 266-282. Kautonena, T., Van Gelderenb, M. and Tornikoskic, E.T. (2013): “Predicting entrepreneurial behaviour: a test of the theory of planned behaviour”. Applied Economics, 45(6), 697-707. Kor, Y.Y., Mahoney, J.T. and Michael, S. C. (2007): “Resources, capabilities and entrepreneurial Perceptions”. Journal of Management Studies, 44(7), 1187-1212. Krueger, N. F., Jr. and Carsrud, A.L. (1993): “Entrepreneurial Intentions: Applying the theory of planned behaviour. Entrepreneurship theory and practice”. Entrepreneurship and Regional Development, 5(4), 315-330. Li, W. (2007): “Ethnic entrepreneurship: studying Chinese and Indian students in the United States”. Journal of Developmental Entrepreneurship, 12(4), 449-466. Liao, Z. and Cheung, M.T. (2002). “Internet-based e-banking and consumer attitudes: An empirical study”. Information and Management, 39, 283–295. Liñan, F. and Chen, Y.W. (2009): “Development and cross-functional application of a specific instrument to measure entrepreneurial intentions”. Entrepreneurship Theory and Practice, 33 (3), 593-617. Liñán, F., J.C. Rodríguez-Cohard, and J.M. Rueda (2011). "Factors affecting entrepreneurial intention levels: A role for education". International Entrepreneurship and Management Journal, 7(2), 195-218. Martin, N.; Rodríguez, A.I.; Hernangomez, J. and Saboia, F. (2009): “The effect of entrepreneurship education programmes on satisfaction with innovation behaviour and performance”. Journal of European Industrial Training, 33(3), 198-214. Martin, C.; Platis, M.; Malita, L. and Ardeleanud, M. (2011): “The role of EMENTORING and social media for developing the entrepreneurship competences”. Procedia - Social and Behavioral Sciences, 15, pp. 947–951. Mathews, C.H., and Moser, S.B. (1996): “A longitudinal investigation of the impact of family background and gender on interest in small firm ownership”. Journal of Small Business Management, 34(2), 29-43. Minniti, M., and Nardone, C. (2007): “Being in someone else’s shoes: The role of gender in nascent entrepreneurship”. Small Business Economics, 28(2-3), 223-238. Munir, K. A. and Phillips, N. (2005): “The birth of the 'Kodak moment': Institutional entrepreneurship and the adoption of new technologies”. Organization Studies, 26(11), 1665-1687. Nunnally, J. (1978): Psychometric Theory, McGraw-Hill, New York. Rauch, A. and Frese, M. (2007): “Let’s put the person back into entrepreneurship research: A meta-analysis of the relationship between business owners’ personality characteristics and business creation and success”. European Journal of Work and Organizational Psychology, 16(4), 353-385. Ringle, C.; M, Wende, S. and Will, S. (2005), SmartPLS 2.0, Hamburg http://www.smartpls.de. Sullivan, D.M. and Ford, C.M. (2013): “How Entrepreneurs Use Networks to Address Changing Resource Requirements During Early Venture Development”. Entrepreneurship Theory and Practice, forthcoming, 1-24. Tushman, M.L. and Anderson, P. (1986): "Technological discontinuties and organizational environments". Administrative Science Quarterly, 31, 439-65. Utterback, J. M. (1994): Mastering the dynamics of innovation: How companies can seize opportunities in the face of technological change. Boston: Harvard Business School Press. Veciana, J.M.; Aponte, M. y Urbano, D. (2005): “University Students’ Attitudes Towards Entrepreneurship: A Two Countries Comparison”. International Entrepreneurship and Management Journal, 1(2), 165-182.

232


EN-02 OR, Modelling and Simulation

233


Toward Various Exact Modeling the Job Shop Scheduling Problem for Minimizing Total Weighted Tardiness Namakshenas M 1 , Sahraeian R2 Abstract In this paper, two different mixed integer programming (MIP) and one constraint programming (CP) models are formulated for classical job shop problem with the aim at minimization of the total weighted tardiness as objective function. The proposed models are solved and compared with well-known benchmarks in the job shop literature, using IBM ILog Cplex software. Examination and comparison of these exact models suggest that one formulation performs much more efficiently than others, namely CP model, in triple criteria: First, number of generated variables; Second, solution time and Third, complexity scale.

Keywords: Job Shop, Total Weighted Tardiness, Mixed Integer Programming, Constraint Programming

1 Introduction The classical job shop problems are the most prevalent issues in scheduling processes in factories in which high number of products should be produced each with custom orders. The usage of job shop algorithms is not restricted to production and manufacturing environment, but they can be implemented in services and other applications, too. With the rapid development in computational technologies, mixed integer programming (MIP) and other high-tech modeling concepts for solving scheduling problems are significantly receiving attention from researchers. Although, there is no efficient solution methodology due to the NP-hard nature of

1

Mohammad Namakshenas ( e-mail: [email protected] ) Department of Industrial Engineering, College of Engineering, Shahed University, Tehran, Iran 2

Rashed Sahraeian ( e-mail: [email protected]) Department of Industrial Engineering, College of Engineering, Shahed University, Tehran, Iran

235


these problems, mathematical programming is the first step to develop an effective heuristic or algorithm. Contrary to job shops with makespan objective, literature on solution procedures to the total weighted tardiness job shop scheduling problem (TWT-JS) is very limited. Given the only branch-and-bound algorithm for this problem proposed by (Singer & Pinedo, 1997) the remaining approaches mainly based on local search (Essafi, et al., 2008; Mati, et al., 2011) and shifting bottleneck methods (Pinedo & Singer, 1999). In the widely used three-field notation of Graham, TWT-JS is written as: J m || w jT j , where Tj = max (0, cj – dj). The assumptions made for the classic job-shop problem are summarized here. The processing times are known, fixed, and independent of the sequence. All jobs are ready for processing at time zero. No preemption is allowed, i.e. once an operation has started it must be completed before another operation may be started on that machine. Also, recirculation is prohibited, i.e. all jobs should meet machines only one time and each job should meet all machines. Only one job may be processed on a machine at any instant of time. No restrictions are placed on the routings of jobs. By this supposition, the problem can be declared as: Given n jobs to be processed on m machines in a job shop with no restrictions on the routing constraints of jobs, determine the optimal job sequence on each machine in order to minimize the total weighted tardiness. The rest of paper is organized as follows: In section (0), first we introduce our notation used throughout the paper, then two integer-based formulation will be discussed. In section (3) a constraint programming model will be developed in OPL terms. Next section has to do with comparison and analysis of proposed formulations and the last section concludes this study with a summary and conclusion.

2 Mixed Integer Formulation In this paper, we use the following notations for MIP formulation procedure: Parameters & Sets: n number of jobs (N: jobs set); m number of machines (M: machines set); pjh processing time of job j on machine h; wj weight of job j; dj due date of job j;  rjlh 1 if the lth operation of job j requires machine h;  0 o.w.  236


Decision variable: cj completion time of job j; sjh starting time of job j on machine h; wj.max (0, cj – dj); Zj Ekh wk.max (0, ck – dk) on machine h;  xjkh 1 if job j scheduled in position k on machine h ;  0 o.w.  yijh

  

1 if job j follows job i on machine h (not necessarily immediately); 0 o.w.

2.1 Disjunctive Approach Disjunction based (DJ) formulation is closely intertwined with the disjunctive graph representation of the job shop. However, the relationship between disjunctions is implicit, which allows us to define the starting times sjh with combination of a key binary variable, say yijh. Also, It suffices to work with these variables on the basis of i < j. Objective:

Min

Z

j N

(1)

j

Constraints:

w

h M

j

j  N ,

rjmh (s jh  p jh ) w j d j  Z j ,

(2)

s ih  s jh  p jh  My ijh ,

i , j  N , h  M , with i  j ,

(3)

s jh  s ih  pih  M (1  y ijh ) ,

i , j  N , h  M , with i  j ,

(4)

r

h M

jlh

(s jh  p jh ) 

r

h M

j , l 1, h

j  N , l  M  {n},

s jh ,

Z j , s jh  nonnegative integers , y ijh  binary,

(5)

i , j  N , h  M .

Constraints set (2) is used for linearization of the max function in TWT-JS and based on operational variable, namely rjlh. Constraints set (3) ensures that if the starting time of job j precedes i on machine h, then there must be delay with duration of processing job j on machine h and it must relax the constraints set (4) and vice versa. Also, Constraints set (5) imposes operational precedence of a job on specified machine. To be precise, it declares that starting time of operation l+1 should occur after the completion of operation l for job j.

237


2.2 Hybrid Approach An alternative formulation can be constructed by deploying both the sequenceposition variables and the precedence variables, namely hybrid formulation (HB). In order to establish a consistent model using two sets of variables, we define a variable vkh for declaration the starting time of the scheduled job in the kth position for processing on machine h. Objective:

Min



k N



h M

(6)

E kh

Constraints:

E kh 

 x

j N t 1..k

jth

p jhw j   x jkh d jw j ,

k  N , h  M ,

(7)

j N

x

jkh

 1,

k  N , h  M ,

(8)

x

jkh

 1,

j  N , h  M ,

(9)

j N

k N

v kh v k 1 ,h 

M (2 

r

h M

x

j N

jlh

j , k 1 , h

x jth 

r

h M

k  N  {1}, h  M , (10)

p jh , j ,l 1 , h

x jkh ) 

r

h M

v kh 

j ,l 1 , h

r

h M

v 

jlh th

j , k , t  N , l  M  {m }, j , k  N , h  M .

r

h M

jlh

p jh ,

(11)

Z j ,v kh  nonnegative integers , x jkh  binary,

In hybrid formulation, the first set of constraints (7) is used to linearized the expression wj.max (0, cj – dj) and this allows to calculate the objective function based on the position of jobs. The second (8) and third (9) set of constraints impose position sequence for jobs, the fourth set (10) indicate that starting time of consecutive position of jobs must have delay with duration of processing time of the previously positioned job, and eventually last set (11) impose operational constraints of each job.

3 Constraint Programming Formulation It is axiomatic that intrinsic difficulties of exact methods or algorithmic problems in the context of combinatorial optimization often render large number of scheduling problems as NP-hard. From the complexity viewpoint, representation of the solution space in a specific algorithms plays an important role in dealing with such NP class instances. Designed solution methods, even high-tech ones, which are 238


highly dependent on number of variables and solution space, might yield the optimum in exponential function of time in practice. In order to deal with such drawbacks of conventional mathematical models, we tried and developed a constraint programming (CP) model. CP has been proven very efficient for solving scheduling problems (IBM Ilog CP, 2009). This approach is highly applicable in two cases: 1) A non-convex solution space that comprised myriad of locally optimal solutions, 2) Multiple disjunctions or globally-defined constraints, which results in poor information retrieved by a linear relaxation of the problem. A pure disjunctive programming with interval variables sij (starting time of job i on machine j in a directed graph) is represented as follows: Objective:

Min



j N

Zj

(12)

Constraints: w j (s ij  pij  d j )  Z j ,

s ik  s ij  pij ,

i  N , j  M ,

i  N , ( j , k )  M , with  i , j  i , k ,

(13) (14)

(s ih  s jh )  (s jh  s ih )  p( jh ) (ih ) ,

(i , j )  N , h  M ,

(15)

s ij , Z j  0 ,

i  N , j  M .

(16)

In this formulation, the first set of constraints (13) is considered for linearization of the objective function. The second set (14) ensure that operation (i,k) cannot start before the completion of operation (i,j). The third set of constraints (15) observe ordering among operations of different jobs that have to be assigned on the same resource. The CP model, in contrast to IP model, is highly contingent upon the CP package used for modeling the problem because of the discrepancies in functional structures of various modeling languages (Edis & Ozkarahan, 2011). In this study, ILOG’s OPL Studio 11.1 is used as the modeling language. Also, Table 1 presents the syntax definition of the constraints used in OPL model. Table 1 Syntax definition for declared OPL local or global constraints Syntax

Definition

cum

Accumulation over interval variables

precedes

Declares precedence constraint on interval variables

requires

Declares resource requirement

wait

Declares precedence constraint on the assignment of resource variables

A basic OPL modeling framework involves a set of intervals (jobs) that need to be assigned on a set of resources (e.g. machines, operators, etc.). An interval variable is a decision variable with three components, i.e. a start and end time and a 239


duration, logically linked together. For interval variables, the search methodology does not enumerate the values in the variables domain and the search space is usually independent of the problem domain size. The search space is estimated as the number of possible orderings of the n interval variables and the complexity of problem is estimated as n.log2 (n). Then, the OPL formulation can be written as follows: Objective:

Min cum i N {w [i ]. max (C [i ]  d [i ],0)}

(17)

Constraints:

i  N , OPR [i , nb _ resource ] precedes C [i ] , i  N , OPR [i , j ] precedes OPR [i , j  1] , i  N , j  M  {n}, OPR [i , j ] requires MAC [OPR [i , j ], j ] , i  N , j  M , MAC [OPR [i , j ], j ] waits MAC [OPR [i , j ], j 1 ] , i  N , j  M  {n}, C [i ]

assigns OPR [i , nb _ resource ].end ,

(18) (19) (20) (21) (22)

In this OPL formulation, we deployed two key variables, namely OPR as interval variable and MAC as resource variable or machines. The objective allows the solver to accumulate over sequences of interval variables and to select the minimum value corresponding to that combination. The first set of constraints (19) declares that jobs on their last operations cannot override C[i] interval. This auxiliary variable helps the modeler to impose a global deadline constraint for the entire planning horizon. The constraints set (20) adjusts the precedence conception, and (21) indicates all interval variables should be dedicated to unary resource variable (MAC). Note that there is no alternative resource for interval variables, therefore they must be dedicated to only one source. The last set of constraints (22) suggests that resource assignment should not be overlapped.

4 Test Problems and Experiments In order to evaluate the capabilities of proposed models, it should be tested on difficult problem instances. Also, our attempt should be focused on conditions under which the solution procedure is most severely challenged. Moreover, the ideal condition for conducting such experiment could exist in usage of data which are representative of real scheduling problems, but providing such pure data is almost impossible. We obtained our job shop problem benchmarks among well-known test problems in the literature, e.g. ABZ05, ABZ06, MT10, etc. This benchmarks initially intended for makespan case are revised by adding a due date and a weight for each 240


of jobs. The latter are constructed following scheme of Pinedo & Singer (1999): They suggested that 20% of the customers are very important, 60% of them are of average importance, and the remaining 20% are of less importance. Therefore, we assume that wj = (4,4,2,2,2,2,2,2,1,1) for a typical 1010 (jobmachine) instance. According to following equation, the due date of job j is set to be equal to the floor of the sum of the processing times of its operations multiplied by a due date tightness factor β.

 m  d i    . p ik  ,  k 1 

  1.3,1.5,1.6.

4.1 Computational Results and Analysis Table displays the size of the MIP and CP formulations for all three alternatives. As the table indicates, the CP formulation contains the smallest number of constraints and variables in comparison with the other formulations. The hybrid formulation (HB) has the highest number of variables. It can be immediately inferred that the last set of constraints possess high portion of constraints in this model, but it is obviously not a tight enough set to take advantage of this property. The disjunction formulation (DJ) has a moderate number of constraints by a wide margin, which seems to account for its efficiency to solve larger problems. In spite of the fact that the HB formulation is conceived to be very tight, the size of the formulation finally contributes to its longer computation times. Table 2 signals the fact that number of binary variables in DJ and HB formulation almost tend to grow exponentially by the rise of problem size. Moreover, solving the CP model is roughly analogous to solving a pure integer model, because solution procedures for facing with CP models only have been built and designed on the integer base. Table 2 Model comparison based on the number of generated variables and constraints Variables Binary

Integer or interval

Non-negative

Constraints

Problem size (job  machine)

DJ

HB

CP

DJ

HB

CP

DJ

HB

CP

DJ

HB

CP

44

24

64

0

0

0

20

21

40

0

64

254

16

66

90

216

0

0

0

36

43

89

0

216

1230

36

88

224

512

0

0

0

72

73

133

0

512

3832

64

1010

450

1000

0

0

0

110

11

192

0

1000

9390

100

1212

792

1728

0

0

0

156

157

291

0

1728

19572

144

1515

1575

3375

0

0

0

240

241

453

0

3375

48135

225

241


Our experiments involved solving each test problem using ILog CPLEX 11.1 on a 2.66 GHZ Intel Core 2 Quad Processor (4 MB Cache) with 6 GB of memory. We restricted the solver with a 3600-s time limit in order to terminate a specific run if the optimal solution had not been verified in that period of time. The runs information are summarized in Table 3. For each formulation, the table displays the number of problems solved within the time limit for the full set of 30 problems, the average time (in second), and the maximum time. We also kept track of the maximum and average gap for the cases in which an optimal solution was not found by the solver and for better addressing the convergence of the model. (A gap is the difference between the solution returned by truncated run and the optimum, computed as a ratio to the optimum.) The results indicate that the HB formulation is very weak, it is also inefficient compared to other formulations. The CP formulation solves most of the benchmarks. Also, we found that DJ formulation converges as fast as CP to the optimum in some cases, but it takes so much time to prone and explore the branches and prove optimality. As the table displays, tightness factor has dramatic impact on average and maximum time to solve a problem, because it restricts the search space and triggers fast convergence. There remains no skepticism about the performance of CP: it outperforms other formulations in all measures. Table 3 Summary of computational results Tightness factor (β)

Model

Problem solved

Average time (sec)

Maximum time (sec)

Average gap (%)

Maximum gap (%)

1.3

DJ

27

985.13

3600+

11.11

30.00

1.3

HB

11

2549.67

3600+

46.25

100.00

1.3

CP

30

748.02

1985.22

0.00

0.00

1.5

DJ

21

2914.65

3600+

73.12

97.01

1.5

HB

5

3600+

3600+

100.00

100.00

1.5

CP

22

2771.36

3600+

25.97

43.12

1.6

DJ

17

3600+

3600+

100.00

100.00

1.6

HB

2

3600+

3600+

100.00

100.00

1.6

CP

23

2789.27

3600+

65.74

100.00

Also, in order to intuitively validate the proposed models including MIP and CP, we used a graphical chart similar to Gant chat (Fig. 1).

242


Fig. 1 Gant chart for ABZ06 instance optimal schedule; obtained by proposed CP (First and second indexes respectively indicate the job’s number and operation’s number for processing that job.)

5 Conclusions That a scheduling problem can be formulated through mathematical programming does not insinuate that there is an available satisfactory standard solution procedure. TWT-JS is a very hard problem either based on enumeration or on heuristics. We conducted some computational experiments based on two integer model and one OPL model, namely CP, using state-of-the-art software package, CPLEX11.1. We tested the efficiency of our proposed formulations by wellknown job shop 1010 benchmarks each with different computational complexity. The CP formulation solves nearly all difficult problems in a reasonable amount of time, because search space is usually independent of the problem domain size. Also, we found that formulation based on disjunction concept (DJ) provides a highly consistent perspective. It produces least number of variables and constraints in comparison with HB formulation and yields a tight model. When it fails to prove optimality after an hour of computation time, it preserves optimality gap. For scheduling researchers, the implication is that standard optimization approaches are able to solve moderate-sized scheduling problems in a reasonable amount of time. Specialized algorithms would seem to be preferable only for larger problems in size. Furthermore, the attention paid to CP formulation may be justified if they provide insight into combinatorial perspective, but CP model are desirable when mathematical models come to fail in description of highly complex search spaces.

243


6 References Edis, E. B. & Ozkarahan, I., 2011. A combined integer/constraint programming approach to a resource-constrained parallel machine scheduling problem with machine eligibility restrictions. Engineering Optimization, 43(2), p. 135–157. Essafi, I., Mati, Y. & Dauzère-Pérès, S., 2008. A genetic local search algorithm for minimizing total weighted tardiness in the job-shop scheduling problem. Computers & Operations Research, Volume 35, p. 2599–2616. IBM Ilog CP, 2009. Detailed Scheduling in IBM ILOG CPLEX Optimization Studio with IBM ILOG CPLEX CP Optimizer. [Online] Available at: http://cpoptimizer.ilog.com Mati, Y., Dauzère-Pérès, S. & Lahlou, C., 2011. A general approach for optimizing regular criteria in the job-shop scheduling problem. European Journal of Operational Research, Volume 212, p. 33–42. Pinedo, M. & Singer, M., 1999. A Shifting Bottleneck Heuristic for Minimizing the Total Weighted Tardiness in a Job Shop. Naval Research Logistics, Volume 46, pp. 1-17. Singer, M. & Pinedo, M., 1997. A computational study of branch and bound techniques for minimizing the total weighted tardiness in job shops. IIE Transactions, 30(2), p. 109–118.

244


Two Simple Constructive Algorithms for the Distributed Assembly Permutation Flowshop Scheduling Problem Hatami S1, Ruiz R2, Andrés Romano C3 Abstract Nowadays, it is necessary to improve the management of complex supply chains which are often composed of multi-plant facilities. This paper proposes a Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP). This problem is a generalization of the Distributed Permutation Flowshop Scheduling Problem (DPFSP) presented by Naderi and Ruiz (2010). The first stage of the DAPFSP is composed of f identical production factories. Each center is a flowshop that produces jobs that have to be assembled into final products in a second assembly stage. The objective is to minimize the makespan. Two simple constructive algorithms are proposed to solve the problem. Two complete sets of instances (small-large) are considered to evaluate performance of the proposed algorithms.

Keywords: Distributed Assembly flowshop, Permutation Flowshop, Constructive Algorithms

1Sara Hatami ( e-mail: [email protected]) Departamento de Estadística e Investigación Operativa, Facultad de Ciencias Matemáticas, Universitat de València, Spain 2Rubén Ruiz ( e-mail: [email protected]) Grupo de Sistemas de Optimización Aplicada, Instituto Tecnológico de Informática, Ciudad Politécnica de la Innovación, Edifico 8G, Acc. B. Universitat Politècnica de València, Camino de Vera s/n, 46021, València, Spain. 3Carlos

Andrés Romano ( e-mail: [email protected]) Departamento de Organización de Empresas, Universitat Politècnica de València,Camino de Vera s/n, 46021, València, Spain

245


1 Introduction Assembly systems have been widely studied in the last decade given their practical interest and applications. An assembly flowshop is a hybrid production system where various production operations are independently and concurrently performed to make parts that are delivered to an assembly line (Koulamas and Kyparisis, 2001). Tozkapan et al. (2003) considered a two-stage assembly scheduling problem by minimizing the total weighted flow time as an objective function. AlAnzi and Allahverdi (2006) addressed the model presented by Tozkapan et al. (2003) and minimized the total completion time of all the jobs by using metaheuristics to solve their model. This is just a small extract of the many existing papers in this regard. From a manager's point of view, scheduling in these systems is more complicated than in single-factory settings. In single-factory problems, the only objective is to find a job schedule for a set of machines, while an important additional decision in the distributed problem is allocating jobs to suitable factories. In this paper, flowshop scheduling is used as a production system for each factory or supplier in the distributed problem. The flowshop scheduling problem (FSP) is composed of a set of M of m machines where each job of a set N of n jobs must be processed in each machine. The number of operations per job is equal to the number of machines. The ith operation of each job is processed in machine i. Therefore, one job can start in machine i only after it has been completed in machine i-1, and if machine i is free. The processing times of each job in the machines are known in advance, non-negative and deterministic. In FSPs, a number of assumptions are made (Baker, 1974). In the FSP, there are n! possible job permutations for each machine. Therefore, the total number of solutions for a flowshop problem with m machines is (n!)m. To simplify the problem, it is assumed that all machines have the same job permutation. With this simplifying assumption the FSP is referred to as Permutation Flowshop Scheduling Problem (PFSP) with n! possible solutions. This problem is one of the most researched topics in the scheduling literature (Pinedo, 2012; Pan and Ruiz, 2012, etc.). The DPFSP can be viewed as a generalized version of the PFSP. This paper studies the Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP). It is a combination of the DPFSP and the Assembly Flowshop Scheduling Problem (AFSP), and consists of two stages: production and assembly. The first stage comprises of a set F of f factories or production centers where a set N of n jobs has to be scheduled. All factories are capable of processing all jobs and each factory is a PFSP with a set M of m machines. Factories are assumed to be identical. Processing times are denoted by 𝑝𝑖𝑗 , i ∈ M, 𝑗 ∈ 𝑁. The second stage is a single assembly factory with an assembly machine, 𝑀𝐴 , which assembles jobs by using a defined assembly program to make a set T of t different final products. Each product has a defined assembly program. 𝑁ℎ and 𝐽𝑗 are used, respectively, to represent product’s h assembly program and the jobs that belong 246


to the product’s h assembly program, 𝑁ℎ : {𝐽𝑗 }, 𝑗 ∈ 𝑁ℎ . Each product h has 𝑁ℎ jobs and job j is needed for the assembly of one product. Therefore, ∑𝑡ℎ=1 |𝑁ℎ | = 𝑛. Product h assembly can start only when all jobs that belong to 𝑁ℎ have been completed in the different factories. The considered objective is to minimize the makespan at the last assembly factory. Despite the innumerable literature related to PFSP and AFSP, it seems that there are few studies about the DPFSP. Naderi and Ruiz (2010) presented the DPFSP for the first time and developed six different MILPs , proposed two simple factory assignment rules and 14 heuristics based on dispatching rules, effective constructive heuristics and VND methods. To the best of our knowledge, no further literature exists on DAPFSP, so this is the first effort that considers the assembly flowshop problem in a distributed manufacturing setting. The next section presents introduces two simple constructive algorithms, Section 3 describes a complete computational evaluation of the proposed algorithms. Finally, Section 4 offers conclusions, remarks and venues for future research.

2 Heuristic Methods As mentioned in the paper of Naderi and Ruiz (2010), the DPFSP is an NPComplete problem (if 𝑛 > 𝑓); accordingly, the DAPFSP with an additional assembly stage is certainly an NP-Complete problem (or rather, one should say that the associated decision problem is). Therefore, it is necessary to develop a heuristic approach to solve large-sized problems. For the assignment of jobs to factories, the two rules (𝑁𝑅1 , 𝑁𝑅2 ), of Naderi and Ruiz (2010) are used. Using these two factory allocation rules, two heuristics are presented to schedule jobs.

2.1 Heuristic 1 We first introduce some necessary notation. An example with n=9, m=2, f=2 and t=3, this is, 9 jobs, 2 factories with a flowshop of two machines each and three products to assemble, is employed to explain expressions and heuristics in some detail. The processing times of the 9 jobs on the first and second machines on factories are {1, 5, 7, 9, 9, 3, 8, 4, 2} and {3, 8, 5, 7, 3, 4, 1, 3, 5}, respectively. Assembly processing times of products on assembly machine are 6, 19 and 12 respectively. The products’ assembly programs are: N1 = {3, 4, 6} , N2 = {1, 2, 8, 9} and N3 = {5, 7}. π represents a product sequence, e.g., π = {1, 3, 2} is a possible product sequence for the given example. As mentioned before, each product h is made up of |Nh | jobs and πh is the partial job sequence of product h, 247


e.g., π1 : {6, 4, 3}, π2 : {1, 9, 8, 2}, π3 : {7, 5}. A complete job sequence, πT , is constructed by putting together all partial job sequences, following the product sequence π, e.g., πT : {6, 4, 3, 7, 5, 1, 9, 8, 2}. The shortest processing time (SPT) is a well-known dispatching rule for the PFSP. Hence the SPT is used to determine the product sequence in the assembly machine. Heuristic 1 begins by applying the SPT rule for the assembly operation times to obtain 𝜋, 𝜋 = {1, 3, 2}. A heuristic which is based on Framinan and Leisten (2003) heuristic (FL) is applied on the jobs that belong to a given product. The heuristic evaluates the completion times of the jobs that belong to product h, for example if, h=1. Set R h is made by sorting jobs in ascending order of completion times, 𝑅1 = {6, 3, 4}. Where completion times for set of jobs of the product 1, 𝑁1 = {3, 4, 6} are 𝐶23 = 12, 𝐶24 = 16, 𝐶26 = 7. The first two jobs of R h are selected and inserted into Sh , 𝑆1 = {6, 3}. All jobs’ pairwise exchanges in Sh are checked and it is updated with the one that results in the best makespan, 𝐶max ({6, 3}) = 15 and 𝐶max ({3, 6}) = 16, 𝑆1 : {6, 3}.. The next step is removing the third job of R h and inserting it in all possible positions of Sh , 𝐶max ({4, 6, 3}) = 25, 𝐶max ({6, 4, 3}) = 24 and 𝐶max ({6, 3, 4}) = 26. The sequence with the best makespan will be selected, 𝑆1 is updated to {6, 4, 3}. All possible sequences by carrying out pairwise exchanges between jobs are evaluated again, 𝐶max ({4,6, 3}) = 25, 𝐶max ({6, 3,4}) = 26, 𝐶max ({3, 4, 6}) = 27. If a better makespan is obtained, then 𝑆ℎ is updated. The process continues until all jobs have been considered. Sh is the partial job sequence for product h, (πh ), 𝜋1 = {6, 4, 3}. By following the same method, the partial job sequences for the other products are: 𝜋2 = {1, 9, 8, 2} and 𝜋3 = {5, 7} with partial makespans of 20 and 18, respectively. πT is constructed by putting together all πh and jobs are assigned to factories from πT by using NR1 or NR 2 , which respectively result in the H11 or H12 heuristics. Hence 𝜋 𝑇 is {6, 4, 3, 5, 7, 1, 9, 8, 2}. The final step is to assign jobs in 𝜋 𝑇 to factories by using 𝑁𝑅1 /𝑁𝑅2 to obtain the 𝐻11 / 𝐻12 . 𝐶max of 𝐻11 and 𝐻12 are 55 and 53, respectively. The Gantt chart of the considered example after applying 𝐻11 is shown in Figure 1.

2.2 Heuristic 2 The idea of the second heuristic is to give priority to products whose jobs are completed in the production stage sooner. This concept is noted as the earliest start time to assemble product h, 𝐸ℎ . The procedure that is used in 𝐻11 and 𝐻12 to find partial job sequences of products (𝜋ℎ ) also is used in heuristic 2. 𝐸ℎ , is calculated by using 𝑁𝑅1 or 𝑁𝑅2 to assign jobs in each partial job sequence to factories. For example, the earliest start times for assembling products by considering 𝑁𝑅2 are 𝐸1 = 15, 𝐸2 = 15, 𝐸3 = 12. 𝜋 is built by sorting 𝐸ℎ in ascending order. 248

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. 6

5

3 6

4

8

3

7 4

2

5

8

2

Factory 1

1 9 7

1

9 Factory 2

Pro. 1

Pro. 3

Pro. 2

Assembly factory

Fig. 1 Gantt chart of 𝐻11 for the example

3 Computational Evaluation Two complete sets of instances have been generated to test the proposed heuristics. Four instance factors (𝑛, 𝑚, 𝑓, 𝑡) are combined at the levels provided for small and large instances. In small instances, number of jobs (𝑛) is tested at 5 levels, 8, 12, 16, 20 and 24, number of machines (𝑚) has 4 levels, 2, 3, 4 and 5, both factors of number of factories (𝑓) and number of products (𝑡) have 3 levels, 2, 3 and 4. In the large instances, all factors have 3 levels and are; 𝑛= {100, 200, 500}, 𝑚= {5, 10 20}, 𝑓= {4, 6, 8} and 𝑡= {30, 40, 50}. Processing times in the production stage are fixed to ∪ [1, 99] as it is usual in the scheduling literature. The assembly processing times depend on the number of jobs assigned to each product h as U[1 × |𝑁ℎ |, 99 × |𝑁ℎ |]. The total number of combinations in the small and large instances are 5 × 4 × 32 = 180 and 34 = 81, respectively. There are five replications per combination for small instances and ten replications for every large combination. Therefore, the total number of instances is 900 and 810, respectively. All instances are available at soa.iti.es.

3.1 Heuristics Evaluation on Small Instances The four proposed methods (𝐻11 , 𝐻12 , 𝐻21 , 𝐻22 ) are tested. A MILP model is constructed for the small instances are solved with two commercial solver packages (CPLEX 12.3 and GUROBI 4.6.1). Serial (1 thread) and parallel (2 threads) and two time limits (900 and 3600 seconds) are tested with the solvers. As the proposed heuristics are not expected to find an optimal solution, the Relative Percentage Deviation (RPD), is measured for comparisons. We measure RPD as follows: using the optimal solution or the best known solution, (𝑂𝑃𝑇𝑏𝑒𝑠𝑡 ) 249


and 𝐴𝐿𝐺𝑆𝑂𝐿 , which reports the makespan obtained by a given algorithm for a given instance: 𝐴𝐿𝐺𝑆𝑂𝐿 − 𝑂𝑃𝑇𝑏𝑒𝑠𝑡 𝑅𝑃𝐷 = × 100 𝑂𝑃𝑇𝑏𝑒𝑠𝑡 Table 1 provides the summarized results of the MILP and the average algorithm deviations from the best known solution for the small instances. They are grouped by n and f. Table 1 Relative Percentage Deviation (RPD) of MILP and proposed algorithms over the best known solution for the small instances. 𝑓×𝑛 2×8 2 × 12 2 × 16 2 × 20 2 × 24 3×8 3 × 12 3 × 16 3 × 20 3 × 24 4×8 4 × 12 4 × 16 4 × 20 4 × 24 Average

MILP 0.00 0.01 0.42 1.26 2.70 0.00 0.00 0.06 0.35 1.18 0.00 0.00 0.04 0.23 0.44 0.45

𝐻11 14.62 13.70 12.52 9.92 7.75 11.35 9.96 10.10 9.86 7.65 9.03 5.63 7.21 6.80 5.13 9.41

𝐻12 13.61 12.78 11.40 9.28 7.38 9.96 9.13 9.16 8.93 6.37 8.01 4.53 6.34 6.00 4.42 8.49

Algorithms 𝐻21 6.91 5.74 5.77 4.25 4.07 4.57 3.03 3.77 2.72 3.00 2.16 1.82 2.86 2.96 2.00 3.71

𝐻22 5.99 5.17 5.10 3.48 3.81 3.15 2.55 3.14 2.19 2.40 1.25 1.38 2.27 2.61 1.59 3.07

MILP reports better results when compared to the proposed heuristics. CPU times to solve small instances with the proposed algorithms are negligible while most of the instances that are solved with the MILP. Therefore, the 3% average deviation of 𝐻22 needs to be contextualized. In order to identify the best algorithm, a means plot and Tukey's Honest Significant Difference (HSD) intervals (99% confidence) for the four simple constructive heuristics is shown in Figure 2. The second heuristic performs better in comparison with the other simple constructive heuristic and there is no significant difference between the rules used to assign jobs to factories.

3.2 Heuristics Evaluation on Large Instances In this case, for calculating the RPD, only the best known solution is used as the MILP cannot be employed. A summarized result of the average RPD, considering number of factories, number of products and number of jobs, is shown in Table 2. 250


Figure 2 shows a means plot (99% confidence level Tukey's HSD intervals) of the proposed algorithms for large instances. Table 2 Relative Percentage Deviation (RPD) for the proposed algorithms over the best known solution for the large instances.

Algorithms 𝐻11 𝐻12 𝐻21 𝐻22

Number of factories (f) 4 6 8 5.39 3.72 3.07 4.91 3.24 2.65 0.14 0.06 0.02 0.01 0.00 0.00

Number of products (t) 30 40 50 3.66 4.20 4.31 3.23 3.76 3.80 0.10 0.06 0.07 0.00 0.01 0.00

Number of jobs (n) 100 6.21 5.53 0.09 0.00

200 3.69 3.21 0.09 0.00

500 2.27 2.06 0.04 0.00

Average 4.06 3.60 0.07 0.00

The second proposed algorithm performs better than the first one also for the large instances. 𝑁𝑅2 as a job assignment rule, reports better results on the first algorithm while job assignment rule on second algorithms does not have any significant effect. It is clear on Table 2, generally when the number of factories and jobs increases, finding a better solution becomes easier, while this trend has a reverse effect when the number of products increases. Proposed simple constructive algorithms use a very short time in order to solve problems (less than 0.01 seconds on average), therefore the details are not reported. 4.8

10.5

3.8 RPD

RPD

8.5

2.8

6.5

1.8

4.5

0.8 -0.2

2.5 11

12

21

11

22

12

21

22

Fig. 2 Means plot and 99% confidence level Tukey's HSD intervals of the relative percentage deviation for simple constructive heuristic methods for small instances on the left and for large instances on the right.

4 Conclusion and Future Research To the best of our knowledge, this paper is the first attempt to generalize the Distributed Permutation Flowshop Scheduling Problem to the Distributed Assembly 251


Permutation Flowshop Scheduling Problem, where there is more than one production center to process jobs and a single assembly center to make final products from produced jobs. Two constructive algorithms are proposed. Computational evaluations were performed with two groups of small and large instances. Results show that in small instances MILP reported results perform better than the proposed algorithms. On the other side, the proposed methods consume very little CPU time in comparison with the MILP while they still produce reasonable solutions. For future works, the setup time and distinct production factories can be considered in the presented model to make it more realistic. Applying metaheuristics like a Genetic Algorithm, Tabu Search, etc., may report better solutions if compared to our proposed simple heuristics.

5 References Al-Anzi F, Allahverdi A (2006) A hybrid tabu search heuristic for the two-stage assembly scheduling problem. The International Journal of Operational Research, 3 (2), 109-119. Baker K R(1974) Introduction to sequencing and scheduling. Wiley, New York. Framinan J, Leisten R (2003) An efficient constructive heuristic for flowtime minimisation in permutation flow shops. Omega, The International Journal of Management Science 31 (4), 311-317. Koulamas C, Kyparisis G J (2001) The three stage assembly flowshop scheduling problem. Computers & Operations Research 28 (7), 689-704. Naderi B, Ruiz R (2010) The distributed permutation flowshop scheduling problem. Computers & Operations Research 37 (4), 754-768. Pan Q K, Ruiz R (2012) Local search methods for the flowshop scheduling problem with flowtime minimization. European Journal of Operational Research 222 (1), 31-43. Pinedo M (2012) Scheduling: Theory, Algorithms and Systems (fourth ed.). Springer, New York. Tozkapan A, Kirca O, Chung C S (2003) A branch and bound algorithm to minimize the total weighted flowtime for the two-stage assembly scheduling problem. Computers & Operations Research 30 (2), 309-320.

252


Set-up Continuity in Tactical Planning of Semicontinuous Industrial Processes Pérez D1, Alemany M.M.E2, Lario F.C3 , Fuertes V.S4 Abstract In most of production planning models developed in a hierarchical context at the tactical level setup changes are not explicitly considered. Its consideration includes decisions about the allocation and lot sizing of production, known as CLSLP problem. However the CLSLP problem does not account for set-up continuity, specially relevant in contexts with lengthy set-ups and where product families minimum run length are almost are similar to planning periods. In this work, a MILP model which accounts for this set-up continuity inclusion is modelled, solved and validated over a simplified real-case example.

Keywords: Set-up Continuity, Semicontinuous Processes, Tactical Planning

1

David Pérez Perales ( e-mail: [email protected]) Centro de Investigación en Gestión e Ingeniería de Producción. Universitat Politècnica de València. Camino de Vera s/n, 46022 Valencia. 2

Maria del Mar Alemany Diaz ( e-mail: [email protected]) Centro de Investigación en Gestión e Ingeniería de Producción. Universitat Politècnica de València. Camino de Vera s/n, 46022 Valencia. 3 Francisco-Cruz Lario Esteban ( e-mail: [email protected]) Centro de Investigación en Gestión e Ingeniería de Producción. Universitat Politècnica de València. Camino de Vera s/n, 46022 Valencia. 4 Vicente Samuel Fuertes-Miquel ( e-mail: [email protected]) Dpto. de Ingeniería Hidráulica y Medio Ambiente. Universitat Politècnica de València. Camino de Vera s/n, 46022 Valencia

* This research has been carried out in the framework of the project funded by the Spanish Ministry of Economy and Competitiveness (Ref. DPI2011-23597) and the Polytechnic University of Valencia (Ref. PAID-06-11/1840) entitled “Methods and models for operations planning and order management in supply chains characterized by uncertainty in production due to the lack of product uniformity” (PLANGES-FHP)

253


1 Introduction In the majority of the production planning models developed in a hierarchical context at the tactical level, the capacities at each stage are aggregated and setup changes are not explicitly considered. However, if at this level the setup times involve an important consumption capacity and have been completely ignored, this may lead to an overestimation of the real capacity availability which, in turn, may lead to unfeasible events during the subsequent disaggregation of tactical plans. Considerable savings may be also be achieved through optimum lot-sizing decisions. However, accounting for setup times at the tactical level would mean simultaneously including decisions about the allocation and lot sizing of production. This problem is known as the capacitated lot-sizing and loading problem (CLSLP) (Özdamar and Birbil 1998). Nevertheless, CLSPP does not consider the set-up continuity over discrete periods of time, that is, it assumes that if a product family is manufactured in two periods of time a double set-up should be considered, leading to an understimation of the real capacity availability. It becomes necessary to model the set-up continuity in these cases so that only one set-up is considered, and therefore saving one. This is particularly important in industrial sectors such as ceramic (Alemany et al. 2011), food (Romsdal et al. 2011), textile, etc., since they cope with very lengthy setup times in their manufacturing semicontinuous processes and at the same time their product families minimum run length are almost or equal to the planning period. In this article, a manner to model the former set-up continuity is proposed. It is applied and validated in a one-stage production process of the ceramic sector, so it may be adapted to a larger model for a specific situation. The rest of the paper is arranged as follows. Section 2 describes the problem being studied. In Section 3, a deterministic MILP model to solve the problem is presented. Section 4 reports a numerical example to validate the model. Section 5 offers some conclusions.

2 Problem Description Production in ceramic SCs usually includes several stages such as presses-glazing lines, kilns and sorting-packing. In this work, only the first one is characterised, although it may also be extrapolated to the second one, with similar characteristics. This presses-glazing stage is made up of one or several production lines in parallel with a limited capacity. Different product families can be processed by each production line. Changeovers from one product family to the next incur setup time and costs. Given the important setup times, when a certain product family is manufactured on a specific line, it should be produced in an equal or greater amount than the minimum lot size. At the tactical level, an Aggregate Plan (AP) is defined for product families, while at the operational level, the Master Plan (MP) 254


is defined for finished goods. Tactical planning must account for two aspects, setup times and its continuity over consecutive planning periods, because the set-up are lengthy and the product families run length (3 weeks) are similar to the planning periods (1 month). These aspects are crucial to get an accurate capacity availability estimation, which will constraint the MP.

3 Problem Modeling A deterministic MILP model has been developed to solve the ceramic tactical planning problem. This model has been simplified since the main objective is formulate and validate the set-up continuity constraints. A supply chain-based extended version of this model may be found in Alemany at al. (2009), but without accounting for the set-up continuity. The objective is to minimize the total cost (set-up and inventory) over the time periods of the planning horizon. Decisions will have to simultaneously deal with not only the allocation of product families to production lines with a limited capacity, but also with the determination of lot sizing. Another decisions regard to set-up continuity modelling. For example those which allow to know the first and the last product family processed on a production line in a planning period, so that one changeover can be saved if the last one processed in t and the first one in t+1 are the same. Or those which allow to process the minimum lot size between two consecutive periods with no change over. All of them are later explained. The indices, parameters, and decision variables are described in Tables 1-3, respectively. Table 1 Indices f

Product families (F) (f = 1…F)

l

Production lines (L) (l = 1…L)

t

Periods of time (PT) (t = 1…T)

Table 2 Parameters dmdft

Demand of F f in PT t.

costinvf

Inventory cost of a F in a PT.

costsetuplfl

Setup cost of F f on L l.

tfablfl

Time to process a F f on L l.

tsetuplfl

Setup time for F f on L l.

lminffl

Minimum lot size of F f on L l.

capfabllt

Production capacity available (time) of L l during PT t.

inv0f

Inventory of F f at the start of the first PT.

M1, M2

Very large integres.

255

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 2 (continued) Parameters nfamilias betal0fl

Number of F. The L l is prepared to manufacture the F f at the start of the first PT.

Table 3 Decision Variables Decisión Variables INVft PFLflt YLflt

Inventory of F f in PT t. Amount of F f manufactured on L l in PT t. Binary variable with a value of 1 if F f is manufactured on L l in PT t, and with a value of 0 otherwise. Binary variable with a value of 1 if L l is ready to manufacture the F f in PT t, and with a value of 0 otherwise. Binary variable with a value of 1 if L l if a setup takes place of F f on L l in PT t, and with a value of 0 otherwise. Binary variable with a value of 1 if more than one F f is manufactured on L l in PT t, and with a value of 0 otherwise. Binary variable with a value of 1 if L l is prepared to manufacture the F f at the start of PT t, and with a value of 0 otherwise. Binary variable with a value of 1 if L l is prepared to manufacture the F f at the end of PT t, and with a value of 0 otherwise.

XLflt ZLflt WLlt ALFALflt BETALflt

Min  cos tsetupl fl * ZL flt   cos tinv f * INV ft t

l

f

t

(1)

f

subject to: INV ft  inv 0 f   PFL flt  dmd ft , l

INV ft  INV ft 1   PFL flt  dmd ft ,



f, t = 1



f, t > 1

l

 tfabl

fl

* PFL flt   tsetupl fl * ZL flt  capfabl lt ,

f

(2) (3)



l, t 1

f

 f, l, t ,  f, l, t

(4)

PFL flt  M 1 * XL flt ,

(5)

PFL flt  M 2 * YL flt

(6)

l min f fl * ( ZL flt  ZL flt 1  YL flt 1 )  PFL flt ,  l, f, t l min f fl * ( ZL flt  ZL flt 1  YL flt  YL flt 1  2)  PFL flt  PFL flt 1

,  l, f, t YL flt  PFL flt ,



f, l, t

(7) (8) (9)

256


YL flt  XL flt , ZL flt  YL flt

,

 f, l, t  f, l, t

(10)

ALFAL flt  betal 0 fl   ZL flt ,



(11) f, l, t = 1

(12)

f

ALFAL flt  BETAL flt 1   ZL flt ,



f, l, t >1

(13)

f

BETAL flt  ALFAL flt  ( XL flt )  1 ,



f, l, t

(14)

f

 ALFAL

flt

1 ,



l, t

flt

1 ,



l, t

(15)

f

 BETAL

(16)

f

ALFAL flt  XL flt , BETAL flt  XL flt ,

 

f, l, t

(17)

f, l, t

(18)

3 * XL flt  XL flt  ALFAL flt  BETAL flt ,



f, l, t

f

2 * XL flt  ALFAL flt  betal 0 fl  2 * ZL flt ,



f, l, t

2 * XL flt  ALFAL flt  BETAL flt 1  2 * ZL flt ,  f, l, t

 ZLflt  nfamilias * (3  ALFAL flt  BETAL flt  betal 0 fl ) f

,  f, l, t = 1  ZL flt  nfamilias * (3  ALFAL flt  BETAL flt  BETAL flt 1 ) f

,  f, l, t > 1

(20) (21) (22)

(23)



l, t

( YL flt )  1  nfamilias *WLlt ,



2   YL flt  2 * (1  WLlt ) ,

(19)

(24)

f

l, t

(25)

f

ALFAL flt  BETAL flt  (2  WLlt ) ,



f, l, t

(26)

The objective function (1) expresses the minimization of the setup costs of the FPs on the Ls and the inventory costs of the Fs at the end of the manufacturing process. Constraints (2) and (3) are the inventory balance equations of in-process and finished Fs, respectively. Constraint (4) ensures that the capacity required for the setup of Fs and the manufacturing of the lots assigned to each L do not exceed the capacity available on each L in each PT. Constraint (5) indicates that a F can only 257


be manufactured on a L in a PT if the L has previously be prepared to manufacture the F in such a PT. Constraint (6) indicates that a F can only be manufactured on a L in a PT if it has previously been decided to manufacture the F on the L in such a PT. Constraint (7) guarantees that should a certain amount of a F be manufactured on a L, it is equal to or above the minimum lot size established for the F on that line. Constraint (8) allows not to manufacture the minimum lot size established for a F on a L in a PT, if either the F was the last one manufactured in the previous PT and the first one manufactured in the next PT, or the F is the only one manufactured during two consecutive PTs. However, it guarantees in both cases that the total amount of F manufactured will be superior to its minimum lot size. Constraint (9) establishes that if there is no amount of FP manufactured on a L in a PT then it is not allowed to manufacture the F on the L in such a PT. Constraint (10) establishes that if a F is manufactured on a L in a PT, then the L has been previously prepared to manufacture the L in such a PT. Constraint (11) establishes that if a F is not manufactured on a L in a PT, then there is no setup on the L in such a PT. Constraints (12) and (13) ensure that if a L “status” at the start of a PT is different from the “status” of the L at the end of the previous PT, then at least one setup has to be made on the L in such a PT. Constraint (14) indicates that if a L does not change its “status” during a PT, then the L is already prepared (either at the start or the end of such a PT) to manufacture the same F. Constraints (15) and (16) guarantee that a L can be only prepared to manufacture just one F, in the start and in the end of a PT, respectively. Constraints (17) and (18) ensures that if a L is not prepared to manufacture a F in a PT, then that F can not be either the first or the last, respectively, for which the L was prepared in such a PT. Constraint (19) indicates that if a L is only prepared to manufacture just one F in a PT, then the L should be prepared either at the start or the end of such a PT to manufacture the FP. Constraints (20) and (21) indicate that it is only possible to save a single changeover on a L in a PT if the L is prepared at the start of the current PT to manufacture the same F for which it was prepared at the end of the previous PT. Constraints (22) and (23) indicate that if the “status” of a L at the start and the end of a current PT is equal to the “status” at the end of the previous PT, then just one or no F is manufactured. Constraint (24) assures that if one or no F is manufactured on a L in a PT, then WL=0, although the contrary case does not imply WL=1. For this it is implemented constraint (25). Constraint (26) guarantees that if more than one F is manufactured on a L in a PT, no one of them can be the first and the last at the same time in such a PT. Therefore, only in the case in which one or no F is manufactured on a L in a PT is possible that ALFAL=1 and BETAL=1 for that F.

258


4 Validation An example to validate the model is described. Data of product families demand and production lines capacity in each TP and specific data of product families on production lines (inventory cost, minimum lot size, etc) are respectively shown in Figures 1-2. F

t1

t2

dmdft t3

t4

t5

t6

L

t1

t2

capfabllt t3 t4

t5

t6

F1 F2 F3 F4 F5 F6

100

125

135

140

150

130

50

70

70

50

70

70

125

110

135

150

125

115

70

50

70

50

50

70

140

125

110

130

115

125

L1 L2 L3

50

50

50

70

70

50

100

125

135

140

150

130

125 140

110 125

135 110

150 130

125 115

115 125

Fig. 1 Data of product families (F) demand and production lines (L) capacity in each TP (t) F

L

costinvf

inv0f

tsetuplf

costsetuplf

tfablf

lminff

beta0lf

F1 F2 F3 F4 F5 F6

L1

0,1 0,15 0,2 0,15 0,25 0,1

50 50 50 50 50 50

2 2,5 3 3.5 2,5 3

35 30 40 45 30 45

0,1 0,25 0,2 0,2 0,1 0,15

160 180 175 160 180 170

0 1 0 0 0 0

F1 F2 F3 F4 F5 F6

L2

0,1 0,15 0,2 0,15 0,25 0,1

50 50 50 50 50 50

2 2,5 3 3.5 2,5 3

35 30 40 45 30 45

0,1 0,25 0,2 0,2 0,1 0,15

160 180 175 160 180 170

0 0 1 0 0 0

F1 F2 F3 F4 F5 F6

L3

0,1 0,15 0,2 0,15 0,25 0,1

50 50 50 50 50 50

2 2,5 3 3.5 2,5 3

35 30 40 45 30 45

0,1 0,25 0,2 0,2 0,1 0,15

160 180 175 160 180 170

1 0 0 0 0 0

Fig. 2 Data of product families (F) on production lines (L)

Just a few representative values of the decision variables that lead to the optimum solution and help to validate the set-up continuity are shown in Table 4.

259

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 4 Amount (m2) of product families (F) manufactured on production line L1 in PT t t1 L1

PFL

XL=YL

Betal0=F2 ZL

F1 F2 F3 F4 F5 F6 F1 F2 F3 F4 F5 F6 ALFAL BETAL F1 F2 F3 F4 F5 F6 WL

t2

t3

t4

70

165

110

130

240 1

1

1

1

1

1 F3 F1 1

F1 F3

1 F3 F6

t5

t6

75 125 75

140

145 115

125

1 1 1

1

F2 F5

F5 F3

1

1 F6 F6

1

1 1

1

1 1

1

1 1

These results confirm that the described constraints are valid to model the setup continuity and that the minimum lot size can be splitted between two consecutive periods of time in case a F is the last to be manufactured on a L in a PT t and the first to be manufactured on the same L in PT t+1. A representative example may be seen in Table 4, for example for F5, which is manufactured on L1 in PTs t=1 and t=2.

5 Conclusions This work presents a deterministic MILP model to solve the tactical planning problem for the production in the ceramic sector, although in may be extrapolated to another semicontinuos production sectors. Its main contributions are on one hand that the accounting for setup times at the tactical level which implies including decisions about the allocation and lot sizing of production (CLSLP problem). Not many works accounts for it in tactical planning. On the other hand the consideration of set-up continuity constraints, specially important in contexts with lengthy set-ups and where product families minimum run length are almost or equal to the planning period.

260


Both contributions help to achieve a more accurate capacity availability estimation in the tactical level so it may lead to feasible and more efficient events during the subsequent disaggregation into operational plans. Since the main objective of this work is this set-up continuity validation, the model has just been applied in a simplified real one-stage ceramic production process and only some of the results are shown. These results show how this model may be adapted to a larger model for a specific situation.

6 References Alemany MM, Alarcón F, Lario FC, Boj JJ (2009). Planificación agregada en cadenas de suministro del sector cerámico. III internacional conference on industrial engineering and industrial management. Alemany MM, Boj JJ, Mula J, Lario FC (2011). Mathematical programming model for centralised master planning in ceramic tile supply chains. International Journal of Production Research 48: 5053-5074. Özdamar L, Birbil SI (1998). Hybrid Heuristics for the capacitated lot sizing and loading problem with setup times and overtime decisions. European Journal of Operational Research 110: 525-547. Romsdal A, Thomassen MK, Dreyer HC, Strandhagen JO (2011) Fresh food supply chains; characteristics and supply chain requirements. 18th international annual EurOMA conference. Cambridge, UK, Cambridge University.

261


Literature Review of Master Planning Models with Lack of Homogeneity in the Product Characteristics under Uncertainty Context Mundi I, Alemany M.M.E1, Poler R, Fuertes V.S Abstract Supply Chains (SCs) with lack of homogeneity in the products (LHP) present particular inherent sources of uncertainty. The intent of this paper is to review how LHP uncertainty is handled in master planning mathematical programming models for different sectors SCs. The result will allow identifying addressed issues and gaps as the base for defining a common body of LHP research.

Keywords: Master Planning, Uncertainty, Lack of Homogeneity in Products, Mathematical Programming Models.

1 Introduction Uncertainty refers to the unpredictability of environmental or organisational variables that have impact on corporate performance. A variety of uncertainty factors affect different organisations in different ways. In fact, supply chains (SCs) with lack of homogeneity in the product (LHP) have unique characteristics. LHP appears in some production processes that incorporate raw materials (RM) directly from nature and /or production processes that cause heterogeneity in the characteristics of the products obtained, even when the materials used are homogeneous (Alemany et al. 2013). LHP is a problem when the customer requires

1 Maria del Mar Alemany Diaz ( e-mail: [email protected]) Centro de Investigación en Gestión e Ingeniería de Producción. Universitat Politècnica de València. Camino de Vera s/n, 46022 Valencia


262


homogeneity between required units of the finished goods in regards to certain attributes because they have to be used, shown, placed or consumed jointly. LHP SCs are forced to classify items in different homogeneous subsets (subtypes) based on certain criteria with the aim of accomplishing with the customer homogeneity requirement. However, the homogeneous quantities (subtypes) really available to customers will not be known until manufactured and classified. LHP introduces specific aspects related to materials, transformation activities and customer order characteristics, which make SCs present unique characteristics with sources of uncertainty that are different from others SCs. Thus, the main purpose of this paper is to review and discuss how and what LHP characteristics have been handled in master planning mathematical programming models under uncertainty context with the aim of dealing with LHP in a unified way. The paper is structured as follows. Section 2 describes the taxonomy to review the literature. Section 3 presents the literature review according to this taxonomy. Finally, section 4 reports the conclusions and the future research directions.

2 Taxonomy The taxonomy of this paper adopts that proposed by Mula et al. (2010) and Peidró et al (2009) as a base. As Mula et al. (2010), we identify in the analyzed papers the environment block for which they are developed for. However, different dimensions for the environment have been defined in our case: sector and LHP characteristics. Then, we propose a new block named uncertainty within those environmental characteristics that have been modeled in an uncertainty way. For the purpose of this research we distinguish between no LHP inherent uncertainty and LHP inherent uncertainty dimensions. As regards the model itself, we identify, as Peidró et al. (2009), the modeling approach and the uncertainty approach. In the following, each dimension of the taxonomy is more detailed. ENVIRONMENT

UNCERTAINTY

MODEL

SECTOR

NO LHP INHERENT UNCERTAINT Y

MODELING APPROACH

LHP CHARACTERISTICS

LHP INHERENT UNCERTAINTY

UNCERTAINTY APPROACH

Fig. 1 Taxonomy dimensions for LHP SC Master Planning under Uncertainty

263


Environment The way in which the LHP occurs primarily depends on the sector and SC studied. There are different sectors with LHP: horticulture, ceramic, marble, tanned hides, meat, etc. But the aim of this review is to know in which sectors some LHP characteristics have been modelled and what is more important, it have been modelled under an uncertainty point of view.We refer to LHP characteristics as those aspects relevant to characterize LHP for planning purposes. LHP can be originated by the lack of homogeneity in raw materials (LHRM) and/or transformation activities (LHP-activities) which confer heterogeneity to the characteristics of the outputs obtained, even when the inputs used are homogeneous due to some environmental factors (LHP-factors). All these industries are obliged to include one or several classification (sorting) stages whose localization along the process and classification criteria depend on the specific industry. For each sorted item, the classification attributes and the values they can take should be identified. This sorted items causes the appearance of subtypes defined as a set of units of the same LHP-item with the same value of attributes. These subtypes can have the same or different economic value. Usually, different economic values imply the existence of several qualities. Furthermore, it is possible that the value of the classification criteria (subtype state) remains unaltered over time (static) or can vary over time (dynamic). For example, in the food sector, the freshness of food decreases over time (decay).Because LHP managerial problem arises due to the homogeneity requirement of customers, it is necessary to know the homogeneity characteristics of customer demand in the forecasts. For instance, the forecast demand can be expressed by subtype (e.g. varieties in fruits) or defined by customer classes (e.g., based on customer size). Uncertainty LHP originates inherent sources of SC uncertainty. Van der Vost (2000) defines the inherent sources of uncertainty as those originated by the SC natural physical characteristics and identifies three possible causes: Intrinsic product characteristics that are caused by the lack of homogeneity in raw materials (LHRM) and the dynamic state of some LHP items (subtypes), for instance the perishabilitity aspect. Technological characteristics of the processes that are caused by the existence of LHP activities and LHP factors (like humidity, temperature, etc.) Logistic actors characteristics: for instance due to eating habits of consumers (preferences of customers in required subtypes) The LHP inherent sources of uncertainty affects four main aspects of relevance for planning purposes: the number of subtypes, the quantities of each subtype, the subtype value and the subtype state. Furthermore, three main uncertainty types are usually identified (Peidro et al 2009): a) Supply uncertainty, b) Process uncertain264


ty and c) Demand uncertainty. The result of combing the LHP uncertainty aspects with the three main uncertainty types provides us with the twelve LHP inherent uncertainty types (Figure 2). We named No LHP inherent uncertainty to other uncertainty types different from these twelve LHP types. Uncertainty Types/ LHP Uncertainty Suppy (Sp) Aspects Uncertainty number of subtypes in supplied raw materials or Subtypes (ST) components (LHRM) in a specific lot or among lots Quantities per subtype of LHRM Subtype quantity (in the same lot or among lots) is (SQ) variable and not known with certainty Subtype value (SV)

Subtype state (SS)

Process (Pr)

Demand (Dm)

Uncertainty number of subtypes in intermediate (LHIP) or finished goods (LHFG)

Uncertainty in the subtypes (LHFG) required per customers/markets in their orders

Quantity required for each subtype Quantities per subtype of LHIP or LHFG(in (LHFG) and customer/market the same lot or among lots) is variable and variable and not known with not known with certainty certainty. The value (cost) of produced LHIP subtypes The value (cost) of supplied can be equal or different but it is not known The value (price) of produced subtypes can be equal or different subtypes (LHFG) in the market can with certainty (cost depends on the LHFG but it is not known with certainty subtypes demand, process (storage be equal or different but it is not (cost depends on the availability known with certainty. conditions) or the final availability of and demand of LHRM subtypes) subtypes) The state of the subtype (LHRM) The state of the subtype (LHFG) is The state of the subtype (LHIP or LHFG) is is dynamic and its evolution is not dynamic and its evolution is not dynamic and its evolution is not known with known with certainty known with certainty (perishability, certainty (perishability, obsolescence) (perishability, obsolescence) obsolescence)

Fig. 2 LHP inherent uncertainty types

Model As regards the model block, we distinguish the same modeling approaches as Mula et al. (2010): Linear Programming (LP), Non Linear Programming (NLP), Multi-objective Programming (MOP), Fuzzy Programming (FP) and Stochastic Programming (SP). However, we have excluded heuristics algorithms, metaheuristics and hybrid models because the focus of our analysis is on mathematical programming models. Finally, the uncertainty approach dimension distinguishes the following cases (Lalmazloumian et al. 2012): distribution-based approach (DBA), fuzzy-based approach (FBA), and scenario-based approach (SBA).

3 Literature Review The search process was carried out through six scientific-technical bibliographic databases based on different search terms. Focusing the analysis on mathematical programming models and considering the limited extension of this paper, a total of 21 references were selected as more representative of different sectors (Table 1).

265

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 Classification of reviewed papers according to the proposed taxonomy. Environment Authors

Sector

Model

Uncertainty

LHP Character- Modeling UncertaintyNo-LHP uncer- LHP unistic approach modeling tainty certainty

Ahumada et Agricultural (fresh quality products SP al (2012) products) perishable product

SBA

crops’ prices and crops’ yields

None

Alem et al Wood (Furniture) trim-loss (2012)

SP

SBA

production costs and/or product demands

None

AlPetroleum Shammari et al (2011)

LP

SBA

demands, sup- None plies, prices, and operations costs

Amaro et al Remanufacturing quality of re(2009) (Pharmaceutical) turns

LP

SBA

products’ de- None mand and prices

Begen et al Food (Fish) (2003)

LP

SBA

Types, grades, None quantity

SP

SBA

labor availabil- Pr-SS/SV ity

Carneiro et Petroleum al (2010)

composition SP crude oil supply

SBA

crude oil sup- Sp-SQ ply, demand, product and oil prices

ChakrabortyCoal et al (2005)

quality: raw coal grades

FP

FBA

Composition Sp-SQ RM (%Ash), yield process, cost RM

SP

SBA

outcome of the Sp-SQ grading process

Dong et al Remanufacturing quality of re- LP (2011) turns customer classes

SBA

quality , arriv- None ing time, and process time of returns

Ghasemy et Fashion goods al (2012)

perishable product

FP

FBA

unit costs and None capacity levels. profit of manufacturer and profit of retailer

Guan et al Food (Dairy) (2011)

perishable product

SP

SBA

milk supply

quality

perishability

Bohle et al Agricultural (wine quality loss (2010) grape) function

Denizel et Remanufacturing quality of real (2010) turns

266

None

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) Classification of reviewed papers according to the proposed taxonomy. Environment Authors

Sector

Model

Uncertainty

LHP Charac- Modeling teristic approach

Uncertainty No-LHP un- LHP uncermodeling certainty tainty

Leung et al Toys (2007)

perishable product

SP

SBA

Demand

Mundi et al Ceramic (2013)

homogeneous LP subsets customer classes

SBA

homogeneous Pr-SQ subsets

Peidro et al Ceramic (2012)

first quality FG

FP

FBA

gross margin, None idle time, backorder quantities

Rong et al Steel (2008)

raw materials FP composition

FBA

raw materials Sp-SQ composition and final product composition

Schutz et al Food (Meat) (2011)

splitting pro- SP cess

SBA

Demand

None

None

Shi et al (2011)

Remanufactur- quality of re- NLP ing turns

DBA

Demand and Sp-SQ quality of returns

Wu et al (2010)

film transistor- quality grades SP liquid crystal in assemblies display and FG

SBA

price and de- None mand FG

raw materials SP characteristics

SBA

Yield of pro- Pr-SQ cess

Zeballos et Remanufactur- quantity and SP al (2012) ing (glass) quality of returns with different economic value

SBA

quantity and Sp-SQ quality of returns

Zanjani et alWood (2011) (Sawmill)

4 Conclusions and Future research From the literature review it can be concluded, that LHP has been majority modeled for the remanufacturing sector. Other sectors are food, agricultural, wood, petroleum, ceramic, steel, fashion products and coal. The LHP characteristics most modeled have been: quality of FGs (subtypes) and perishability. Only two papers consider customer classes (Dong et al, 2011 and Mundi et al, 2013). Zeballos et al (2012) takes into account the different economic value of subtypes. It is 267


remarkable the work of Schutz et al (2011) that address the subtype quantities by means the so called reverse bill of materials, and Mundi et al (2013) that split the produced lots into homogeneous sublots. Though the three main types of uncertainty (supply, process and demand) are addressed, less than half of the analyzed papers consider it from the point of view of the LHP Inherent Uncertainty. From this point of view, three of them consider LHP Inherent Uncertainty in the process: Bohle et al (2010) consider uncertainty in SS and SV; Zanjani et al (2011) consider the process yield uncertain (SQ); Mundi et al (2013) split each lot into homogeneous sub-lots of the same product to reflect the LHP characteristics (SQ). The remaining six deal with the LHP Inherent Uncertainty from the perspective of supply uncertainty: Carneiro et al (2010) consider that uncertainty properties of final product must be within a range established by environmental regulations (SQ) and this uncertainty in modeled through predefined scenarios; Chakraborty et al (2005) investigate the amount of raw material from different coal seams (SQ) through the fuzzy programming; Rong et al (2008) also use fuzzy programming to examine the necessary amount of RM to achieve suitable composition of FG (SQ); Denizel et al (2010) and Shi et al (2011) assume the total amount of returns in a remanufacturing environment is known in advance, however, their quality levels are uncertain (SQ). Finally, Zeballos et al (2012) propose also in remanufacturing a stochastic programming model where not only quality is assumed to be uncertain (SQ) but also quantity (ST) is assumed to follow a pre-defined probability distribution using scenario-based approach. It can be stated that the most LHP features addressed in an uncertainty context are the quantities per subtype of LHRM (Sp-SQ) meanwhile the remaining LHP inherent uncertainty subtype have been either very scarcely or not addressed. Therefore, it can be concluded that current planning models do not provide adequate decision support for the uncertainty modeling of LHP characteristics. This gap provide us with the opportunity of developing new research as regards reference models, modeling and solution techniques to properly handling LHP uncertainty. This new research field will allow the development of more realistic models that significantly improve the practice of master planning.

5 References Ahumada, O., Rene Villalobos, J., & Nicholas Mason, A. (2012). Tactical planning of the production and distribution of fresh agricultural products under uncertainty. Agricultural Systems, 112(0), 17-26. Alem, D. J., & Morabito, R. (2012). Production planning in furniture settings via robust optimization. Computers & Operations Research, 39(2), 139-150. Alemany M.M.E., Lario Francisco-Cruz, Ortiz A., Gómez F. (2013) Available-To-Promise modeling for multi-plant manufacturing characterized by lack of homogeneity in the product: An illustration of a ceramic case. Applied Mathematical Modelling 37:3380–3398

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Al-Shammari, A., & Ba-Shammakh, M. S. (2011). Uncertainty analysis for refinery production planning. Industrial & Engineering Chemistry Research, 50(11), 7065-7072. Amaro, A. C. S., & Barbosa-Povoa, A. P. F. D. (2009). The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure. Computers & Chemical Engineering, 33(12), 2144-2158. Begen, M. A., & Puterman, M. L. (2003). Development of a catch allocation tool design for production planning at JS McMillan fisheries. Infor, 41(3), 235-244. Bohle, C., Maturana, S., & Vera, J. (2010). A robust optimization approach to wine grape harvesting scheduling. European Journal of Operational Research, 200(1), 245-252. Carneiro, M. C., Ribas, G. P., & Hamacher, S. (2010). Risk management in the oil supply chain: A CVaR approach. Industrial & Engineering Chemistry Research, 49(7), 3286-3294. Chakraborty, M., & Chandra, M. K. (2005). Multicriteria decision making for optimal blending for beneficiation of coal: A fuzzy programming approach. Omega-International Journal of Management Science, 33(5), 413-418. Denizel, M., Ferguson, M., & Souza, G. ". C. (2010). Multiperiod remanufacturing planning with uncertain quality of inputs. IEEE Transactions on Engineering Management, 57(3), 394-404. Dong, M., Lu, S., & Han, S. (2011). Production planning for hybrid remanufacturing and manufacturing system with component recovery. Lecture Notes in Electrical Engineering. Ghasemy Yaghin, R., Torabi, S. A., & Fatemi Ghomi, S. M. T. (2012). Integrated markdown pricing and aggregate production planning in a two echelon supply chain: A hybrid fuzzy multiple objective approach. Applied Mathematical Modelling, 36(12), 6011-6030. Guan, Z., & Philpott, A. B. (2011). A multistage stochastic programming model for the new zealand dairy industry. International Journal of Production Economics, 134(2), 289-299. Lalmazloumian, M., & Kuan Yew Wong. (2012). A review of modelling approaches for supply chain planning under uncertainty. Service Systems and Service Management (ICSSSM), 2012 9th International Conference on, pp. 197-203. Leung, S. C. H., & Ng, W. (2007). A stochastic programming model for production planning of perishable products with postponement. Production Planning & Control, 18(3), 190-202. Mula, J., Peidro, D., Díaz-Madroñero, M., & Vicens, E. (2010). Mathematical programming models for supply chain production and transport planning. European Journal of Operational Research, 204(3), 377-390. Mundi, I., Alemany, M.M.E., Boza, A., & Poler, R. (in press). A Model-Driven Decision Support System for the Master Planning of Ceramic Supply Chains with non Uniformity of Finished Goods. Studies in Informatics and Control Journal. Peidro, D., Mula, J., Poler, R., & Lario, F. C. (2009). Quantitative models for supply chain planning under uncertainty: A review. The International Journal of Advanced Manufacturing Technology, 43(3), 400-420. Peidro, D., Mula, J., Alemany, M. M. E., & Lario, F. (2012). Fuzzy multi-objective optimisation for master planning in a ceramic supply chain. International Journal of Production Research, 50(11), 3011-3020. Rong, A., & Lahdelma, R. (2008). Fuzzy chance constrained linear programming model for optimizing the scrap charge in steel production. European Journal of Operational Research, 186(3), 953-964. Schutz, P., & Tomasgard, A. (2011). The impact of flexibility on operational supply chain planning. International Journal of Production Economics, 134(2), 300-311. Shi, J., Liu, Z., Zhu, C., & Zhang, Y. (2011). Optimal prodcution planning for a closed loop system with quality uncertainty of used product. Proceedings - 2011 4th International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2011, , 2. pp. 394-397. Van der Vorst, JGAJ, (2000). Effective food supply chains: generating, modeling and evaluating supply chain scenarios, doctoral thesis, Wageningen University.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Wu, C., Lin, J. T., & Wu, H. (2010). Robust production and transportation planning in thin film transistor-liquid crystal display (TFT-LCD) industry under demand and price uncertainties. International Journal of Production Research, 48(20), 6037-6060. Zanjani, M. K., Nourelfath, M., & Ait-Kadi, D. (2011). Production planning with uncertainty in the quality of raw materials: A case in sawmills. Journal of the Operational Research Society, 62(7), 1334-1343. Zeballos, L. J., Gomes, M. I., Barbosa-Povoa, A. P., & Novais, A. Q. (2012). Addressing the uncertain quality and quantity of returns in closed-loop supply chains. Computers and Chemical Engineering, 47, 237-247.

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A MILP Model for the Scheduling of Noncontinuous Serial Multi-product Multi-stage Batch Processes with Non-identical Machines. Latorre F1, García-Sánchez A2, Méndez C3, Aguirre A4, Ortega-Mier M5 Abstract In this paper a mixed integer lineal programming (MILP) approach is proposed for the scheduling of multiple dissimilar orders in a non-continuous serial production environment. In this context, different products must be produced in several stages, in which a single machine is chosen per stage to accomplish the production of each order. This work has been carried out in a manufacturing company of garden decoration's products. The major complexity of this problem relies on the possibility of considering a wide range of colors, shapes and sizes of products to be manufactured, commonly named as modes. The main aim of this mathematical model is to correctly schedule and synchronize different types of modes, minimizing the total tardiness and the completion time of all production orders in the system.

Keywords: MILP Scheduling, Serial Production, Multi-stage, Multi-product.

1 Francisco Latorre Dueñas ( e-mail: [email protected]) Depto. de Ingeniería de Organización, Administración de Empresas y Estadística. ETSI Industriales, (UPM), C/José Gutierrez Abascal 2, 28006 Madrid, España. 2 Álvaro García-Sánchez ( e-mail: [email protected]) Depto. de Ingeniería de Organización, Administración de Empresas y Estadística. ETSI Industriales, (UPM), C/José Gutierrez Abascal 2, 28006 Madrid, España. 3

Carlos A. Méndez (e-mail: [email protected]) Centro Avanzado de Ingeniería de Procesos y Sistemas (CAPSE). INTEC (UNL-CONICET), Güemes 3450, 3000 Santa Fe, Argentina.

4

Adrián M. Aguirre (e-mail: [email protected]) Centro Avanzado de Ingeniería de Procesos y Sistemas (CAPSE). INTEC (UNL-CONICET), Güemes 3450, 3000 Santa Fe, Argentina. 5

Miguel Ortega-Mier (e-mail: [email protected]) Depto. de Ingeniería de Organización, Administración de Empresas y Estadística. ETSI Industriales, (UPM), C/José Gutierrez Abascal 2, 28006 Madrid, España.

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1 Introduction Production scheduling has become in a critical issue for decision makers in recent years. Nowadays companies tend to increase their product’s portfolio in order to satisfy a wide range of customer’s demands. This context pushes newest companies to improve their daily production schedule in order to gain flexibility without losing production performance. In other hand, batch scheduling problems have drawn growing attention from research community over last decades. Several contributions have been proposed to solve different issues in chemical process industry and then have been extended to other research areas and application problems. As an example, Mendez et al. (2006) presents a suitable survey of principal MILP formulations developed for batch scheduling systems based on both discrete and continuous time representations. A general mathematical model for a serial multi product multi-stage batch production process is introduced. In this model, several orders (batches) must be scheduled and delivered fulfilling specific due date times (see Méndez et al., 2000). All the information about items and order features are known. In addition, sequence-dependent set-up times and parallel non-identical machines are also considered in this problem (see Hui et al., 2000). This work is based in the complex process appeared in the manufacturing of fences used as a garden’s decoration products. Fences are commonly made of plastic and also have different shapes, colours and sizes. All possible combination of these labels generates a wide range of fencing products which are usually known as modes. The correct synchronization in the manufacturing of different modes during the scheduling horizon represents a very complex issue for actual manufactures. Only few works are reported in this area. As an example, Halsall and Price (1999) develop a DSS (“Decision Support System”) for the production planning and control in small companies, such as fence manufacturing plants. In this work, a real manufacturing facility of fencing products is presented to be study. The main contribution is to provide a well description of fence manufacturing process and then a full-space solution approach that allow scheduling certain mixes of fencing modes minimizing the total tardiness and the completion time of all orders in the system.

2 Fences Manufacturing Facility Fences manufacturing facility is illustrated in order to explain the flow of task processes. There are two types of fence family products: wind-breaks and trellis panel. Each of those families has several kinds of shapes, colour measures which 272


makes hard to schedule several task. Each task is made up by only one product and its quantity. The production process is formed for both families by four main processes and one relevant process which will be tackled in future researches. The relevant process is the first stage which relies on make the raw material. An unlimited supply is supposed for that first process or stage. The first relevant stage is extrusion, which transform raw material in sticks for both wind-breaks and trellis panel products. In that point there is a splitting up for each family. Next stage for windbreaks is sewed process which assembly sticks in order to make a wind-break roll. Before that stage wind-break rolls are packed in packing process. Next stage for trellis panel before extrusion process is trellis machine which assembly sticks in order to make trellis panels. Packing trellis panels are made in that process. Figure 1 shows a schematic process flow.

Fig. 1 Flowchart of facility

There are a predetermined number of orders 𝑖 ∈ 𝐼, where each order belongs to a unique product and a given quantity. Each product is defined by its family, shape, colour and measures. Each order must be processed in their corresponding stages 𝑠 ∈ 𝑆 𝑖 , furthermore each order must be processed in an allowed machine for the corresponding order 𝑘 ∈ 𝐾 𝑖,𝑠 . Notice that machines depends not only on the stages, but also the order, because some orders cannot be processed in any machine in a given stage. Since each order belongs to a unique product, that approach is a way to restrict products and machines. That is, wind-break orders cannot be processed in trellis process and vice versa. Furthermore some machines cannot make some type of color or shape. Processing time does depend on the speed production of the machine and the amount of units given in the order. Quantity could be specifying as a customer order or a kanban order. Rely on that parameters, processing time for each machine is known. 273


It is important to take into account set-up time between products, that is, between orders. Changes between shapes, colors and measures can add a relevance time to the lead time’s product that could make a delayed order. Set-up time not only depends on products features but also depend on the machine. A due date must be accomplished for each order and it is not easy to schedule several order considering processing time and set-up time without optimization tools.

2.1 Schedule Optimization Optimal schedule for the whole plant use to permit weekly targets because WIP (“Work In Process”) inventory levels remains low over the entire scheduling horizon and there is a sizable reduction in labor and changeover costs (Méndez and Cerdá, 2002). Adopting those measures in a fencing-product manufacturing both due date accomplishment and make-span minimization are compared.

2.2 Hypothesis and Assumptions Several statements and assumptions must be considered in the model explained below:  Customer orders or kanban order must be manufactured in its stages and its available machines.  Processing time in each machine is known  Due date are known for each order.  Set-up time between each orders in a given machine is known  There is unlimited raw material. In that kind of manufacturing, raw material are used at the first stage. Otherwise the order that have not required raw material is not planned.  Unlimited inventory capacity between stages is allowed. The main goal is to compare due date accomplishment and make-span minimization. In the case of due date accomplishment, every order must accomplish a due date penalizing tardiness.

274


3 MILP-based Formulation In this section a continuous time MILP-based model is presented. One of the main features of the proposed mathematical model is to allocate the decision variable 𝛽𝑖,𝑘,𝑠 . Thus, if this variables is equal one, the order (𝑖) must be made in machine 𝑘 ∈ 𝐾 𝑖,𝑠 at the stage 𝑠 ∈ 𝑆 𝑖 . On the other hand, the decision variable 𝛼𝑖,𝑖 ′ ,𝑘,𝑠 establishes the sequence between two dissimilar orders. Thus, if 𝛼𝑖,𝑖 ′ ,𝑘,𝑠 = 1, order (𝑖) precedes order (𝑖′) in a given machine and stage, otherwise, order (𝑖′) precedes order (𝑖). According to this, only a single variable has been necessary to determine all sequencing decision in the system.

3.1 Nomenclature List Sets are described as follows. 𝐼, Set of order. Indices 𝑖, 𝑖′. 𝑆, set of stages. Indices s, s′. 𝐾, set of machines. Index 𝑘. 𝑆 𝑖 , subset of stage 𝑠 s of each production order 𝑖. 𝐾 𝑖,𝑠 , subset of available machines 𝑘 in stage s for production order 𝑖.

3.1.1 Parameters 𝑇𝑃𝑖,𝑘,𝑠 𝑆𝑈𝑖,𝑖 ′ ,𝑘,𝑠 𝐷𝐷𝑖 𝑃𝐸𝑖

Processing time of order 𝑖 in machine 𝑘 on the production stage 𝑠. Set-up time between orders i’ and i in machine k on production stage s. Due date of order 𝑖. Penalty tardiness of order 𝑖.

3.1.2 Continuous Variables 𝑐 𝑡𝑖,𝑠 𝑓 𝑡𝑖,𝑠 𝑒𝑖 𝑚

Start time of order 𝑖 in machine 𝑘 on production stage 𝑠 Finish time of order 𝑖 in machine 𝑘 on production stage 𝑠 Delay time of order 𝑖 Makespan

275


3.1.3 Binary Variables 𝛽𝑖,𝑘,𝑠

1 if order i is processed in machine k on production stage s. Otherwise is zero. 1 if order i’ is processed after order i in the production sequence of machine k on production stage s. Otherwise is zero.

𝛼𝑖,𝑖 ′ ,𝑘,𝑠

3.2 Model Constraints Constraints and objective function are formulated and explained below. ∑|𝐾| 𝛽 =1 𝑘∈𝐾 𝑖,𝑠 𝑖,𝑘,𝑠

∀𝑖 ∈ 𝐼, 𝑠 ∈ 𝑆 𝑖

|𝐾|

𝑓

𝑐 𝑡𝑖,𝑠 = 𝑡𝑖,𝑠 + ∑𝑘∈𝐾𝑖,𝑠(𝑇𝑃𝑖,𝑘,𝑠 · 𝛽𝑖,𝑘,𝑠 )

∀𝑖 ∈ 𝐼, 𝑠 ∈ 𝑆 𝑖

(1) (2)

𝑓

𝑡𝑖,𝑠 + 𝑆𝑈𝑖,𝑖 ′ ,𝑘,𝑠 ≤ 𝑡𝑖𝑐′ ,𝑠 + 𝑀(1 − 𝛼𝑖,𝑖 ′ ,𝑘,𝑠 ) + 𝑀(2 − 𝛽𝑖,𝑘,𝑠 − 𝛽𝑖 ′ ,𝑘,𝑠 ) ′

′

∀𝑖, 𝑖 ′ ∈ 𝐼, 𝑘 ∈ (𝐾 𝑖,𝑠 ∩ 𝐾 𝑖 ,𝑠 ), 𝑠 ∈ (𝑆 𝑖 ∩ 𝑆 𝑖 ), 𝑖 > 𝑖 ′

(3)

𝑓

𝑐 𝑡𝑖 ′ ,𝑠 + 𝑆𝑈𝑖 ′ ,𝑖,𝑘,𝑠 ≤ 𝑡𝑖,𝑠 + 𝑀(𝛼𝑖,𝑖 ′ ,𝑘,𝑠 ) + 𝑀(2 − 𝛽𝑖,𝑘,𝑠 − 𝛽𝑖 ′ ,𝑘,𝑠 ) ′

′

∀𝑖, 𝑖 ′ ∈ 𝐼, 𝑘 ∈ (𝐾 𝑖,𝑠 ∩ 𝐾 𝑖 ,𝑠 ), 𝑠 ∈ (𝑆 𝑖 ∩ 𝑆 𝑖 ), 𝑖 > 𝑖′ 𝑓

𝑐 𝑡𝑖,𝑠 ≤ 𝑡𝑖,𝑠 ′ 𝑓

𝑡𝑖,𝑠 ≤ 𝐷𝐷𝑖 + 𝑒𝑖

∀𝑖 ∈ 𝐼, 𝑠 ∈ 𝑆 𝑖 , 𝑠 ′ > 𝑠 ∀𝑖 ∈ 𝐼, 𝑠 ∈ 𝑆 𝑖 : 𝑠 = |𝑆| |𝐼|

𝑚𝑖𝑛 𝑍 = ∑𝑖∈𝐼 𝑒𝑖 · 𝑃𝐸𝑖

(4) (5) (6) (7)

Each order must be produced in each production stage by a single machine, as is exposed in (1). The finish time of a particular order is calculated in (2) by using the information of processing time and the start time of each order. The start time of an order depends on the finish time of the previous order in the sequence and also by the set-up between orders. The sequencing constraints of different orders in the same production unit are presented in (3) and (4). Equation (5) determines that the processing time of an order in a particular stage begins when the activity in the previous stage is finished. The delay time is derived from the information of due date time and the finish time of each order in the final production stage, as is explained in (6). 276


Finally, the objective function of the problem is presented in (7), in order to minimize the total delay time of all orders in the system. For this, a penalty cost is proposed according to the relevancy of each order in the delivery schedule. Alternative objective functions can be easily considered into the model for this particular problem. According to this, equations (8) and (9) are proposed to compute the minimum completion time of all production orders in the system, as the Makespan criterion. 𝑚 ≥ 𝑡 𝑓 𝑖,𝑠

∀𝑖 ∈ 𝐼, 𝑠 ∈ 𝑆 𝑖 : 𝑠 = |𝑆|

(8)

min 𝑧 = 𝑚

(9)

Other strategies could be taken into account. For instance, the minimum manufacturing cost. May be every order can be accomplished without start every machines, so a fixed start cost could be added if at least one order is made in a machine. In addition a variable cost depending of the total processing time in a machine could be added. Index domain for variables have been defined so that decision variables only refer to all possible combinations of orders, stages and machines.

4 Case Study: Problem Description The model developed above was implemented and tested using data based on an actual system, where a wide range of garden decoration products for concealment. There are two product families, wind-break and trellis panel. Wind-breaks orders have to be manufactured in their corresponding stages (extrusion, sewing and packaging). In addition, trellis panels orders have to be manufactured in their corresponding stages (extrusion and trellis). Notice that either Wind-breaks orders or Trellis panel orders share a common stage (extrusion). Features of an order depends on it features and amount of product. Product range has five main colours, three main shapes of cane, three heights and two main widths. All of these features require a good scheduler. Notice that every product cannot be produced in every machine, so the model must choose the right machine in order to make every order using the less global time. Furthermore, every set-up must be considered between orders. Set-ups depend on the change of any feature of product (order), that is, a change in colour, or type of cane depending of the machine it makes the set-up time goes through zero to a great time which makes non optimal a possible solution. Main ranges of features of product are the following  Colours: green, white, cane colour (yellow), brown and silver.  Shapes: double sided, simple sided and rectangular 277


 Sizes: it depends of the product – Wind-break has two kinds of sizes, width and length – Length: 1 metro, 1’5 metro and 2 metros – Width: 3 metros and 5 metros – Trellis panel has a size of 1 metro length and 2 metros width. But canes have all of them the same measure. Set-up depends on the numbers of changes in the features of the product we want to take into account. Table 1 shows guidance times between changes. If more than one feature changes between two orders, the corresponding set-up is the addition of the set-up times corresponding to all of these feature changes, for instance, if we have to change color, shape and length in extrusion, set-up is going to be the addition of all of them, that is, 71 minutes. Furthermore set-up time depends of each machine of the stage. Processing time depends on the speed of the machine and the amount of items in the order. Table 1 Set-up time (min.) for each feature of the product

Extrusion

Colour

Shape

Length

Width

10

60

1

-

Sewing

2–20

5

10

1

Trellis

5

-

-

-

packaging

-

-

-

5

4.1 Computational Analysis Several instances are modeled. A maximum of ten orders were scheduled through the proposed MILP-based approach. Stage extrusion is integrated by four extruders, stage sewing is integrated by four sewers, stage trellis is integrated by two trellis machine and stage packaging is integrated by one packaging machine. Orders 1,2,5,6, 7 and 9 have to be processed in the stages extrusion, sewing and packaging. Orders 3, 4, 8 and 10 have to be processed in the stages extrusion and trellis. Every order has similar processing time, but every order cannot be processed in each machine. Set-up time depends on two orders in each machine. In that case there is a wide range of set-up time due to the fact there are eleven machines and ten orders. Every processing time and set-up time for each order, machine and stage can be found in the next URL (http://goo.gl/Gi9wO). Is important to take into account the solving time since a scheduler would not be useful if it is very time consuming. Cases exposed has been implemented on 278


the modeler AIMMS 3.13 and solved with CPLEX v12.4. Computer used is a PC Intel Core I3, OS Windows 7 and NVIDIA graphic card of 4 GB.

4.1.1 Results Two alternatives are implemented in the model, minimizing make-span and accomplishing due date. Minimizing make-span, four instances have been considered with 8 to 10 orders and changing the quantity of machines (Table 2). Accomplishing due date, two instances have been considered (instance 5 and 6). In instance 5, model is scheduled with the same due date for every order, then 3 due date orders are advanced, so that, before a rescheduling, model must accomplish news due dates. In instance 6, every order has the same due date but it is enforcing to a delay, so that, one order is delayed. Then a great penalty for delayed order (because order is considered as a relevant order) is added and rescheduled, so that, there exists other delayed order less relevant. Table 2 Instance characteristics and computational data Instance

Orders

Machines

Instance 1

10

4 Extruders, 4 sewers, 2 trellis, 1 packaging

65

1497.5

Instance 2

10

3 Extruders, 4 sewers, 2 trellis, 1 packaging

5490

1698.14

first 8 orders 4 Extruders, 4 sewers, 2 trellis, 1 packaging

1.68

1496.5

Instance 3 Instance 4

Solving time in Optimal soluseconds tion in minutes, makespan

first 8 orders 4 Extruders, 4 sewers, 355 2 trellis, 1 packaging Every empiric instance can be found in the next URL (http://goo.gl/Gi9wO).

1518.18

4.1.2 Computational Experience Make-span instances were solved in 3.199 to 38.130.055 iterations, spending a solving time of up to 5.490 seconds. Due-date instances were solved in 125 to 4.609 iterations, spending a solving time of up to 0’94 seconds. Instances model use 310 to 485 constraints, 221 to 316 variables (which 117 to 262 are integers). For more details about this problem see also URL (http://goo.gl/Gi9wO). As a summary, due date instances solve faster than make-span instances, also due date is a good manufacturing politic, therefore, due date constraints is a good implementation for the model.

279


5 Conclusions A MILP-based model for the scheduling of different production orders in a noncontinuous serial manufacturing process of fencing products has been presented in this work. This model considers, different processing times, sequence-dependent set-up times, non-identical machines and delivery due dates. Several objective functions have been implemented, such as minimum makespan and tardiness. The model obtains optimal results for all problem instances analyzed in very short computational time which demonstrate the effectiveness of the solution method. Extensions of this model will consider the consumption of raw materials at the beginning production stage. Moreover further researches will look at the possibility to consider the scheduling and rescheduling of incoming orders when nonfinished orders have been in the system at the beginning of the scheduling horizon.

6 References Halsall, D. N., Price, D. H. R. (1999). A DSS approach to developing systems to support production planning and control in smaller companies.International journal of production research, 37(7), 1645-1660. Hui, C., Gupta, A., Van der Meulen, H. (2000). A novel MILP formulation for short-term scheduling of multi-stage multi-product batch plants with sequence-dependent constraints. Computers and Chemical Engineering 24 (12), pp. 2705-2717. Méndez, C. A., Cerdá, J. (2002). An MILP-based approach to the short-term scheduling of makeand-pack continuous production plants. Or Spectrum,24(4), 403-429. Méndez, C. A., Cerdá, J., Grossmann, I. E., Harjunkoski, I.,Fahl, M. (2006). State-of-the-art review of optimization methods for short-term scheduling of batch processes. Computers and Chemical Engineering 30 (6-7), pp. 913-946. Méndez, C. A., Henning, G. P., Cerdá, J. (2000). Optimal scheduling of batch plants satisfying multiple product orders with different due-dates. Computers and Chemical Engineering 24 (9-10), pp. 2223-2245

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NTIGen: a Software for Generating Nissan Based Instances for Time and Space Assembly Line Balancing Chica M1, Cordón O2, Damas S3, Bautista J 4 Abstract The time and space assembly line balancing problem (TSALBP) is a realistic multiobjective version of assembly line balancing industrial problems involving the joint optimization of conflicting criteria such as the cycle time, the number of stations, and the area of these stations. For this family of problems there is not any repository where researchers and practitioners can obtain realistic problem instances also containing information on mixed products plans. In this contribution we introduce a new TSALBP instance software generator that can produce problem instances having industrial real-like features. This generator is called NTIGen (Nissan TSALBP Instance GENerator) since it is developed from the information and real data of the assembly line and production planning of the Nissan plant of Barcelona. The NTIGen software as well as some benchmark instances are publicly available on Internet and could be used by researchers to carry out general TSALBP experiments and to also discriminate between different assembly line configurations when future demand conditions vary.

Keywords: Time and Space Assembly Line Balancing, Problem Instance Generator, Mixed Products, Nissan, Optimization 1Manuel

Chica Serrano ( e-mail: [email protected]) European Centre for Soft Computing, Gonzalo Gutiérrez Quirós s/n 33600 Mieres (Asturias).

2

Óscar Cordón García ( e-mail: [email protected]) DECSAI and CITIC-UGR, Universidad de Granada, 18071 Granada European Centre for Soft Computing, Gonzalo Gutiérrez Quirós s/n 33600 Mieres (Asturias). 3 Sergio Damas Arroyo ( e-mail: [email protected]) European Centre for Soft Computing, Gonzalo Gutiérrez Quirós s/n 33600 Mieres (Asturias). 4

Joaquín Bautista Valhondo ( e-mail: [email protected]) Dpto. Organización de Empresas, ETSEIB, UPC Catalunya, 08028 Barcelona. * This work has been supported by Ministerio de Economía y Competitividad under project SOCOVIFI2 (TIN2012-38525-C02-01 and TIN2012-38525-C02-02), and under PROTHIUS-III: DPI2010-16759, both including EDRF funding.

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1 Introduction An assembly line is made up of a number of workstations, arranged either in series or in parallel. Since the manufacturing of a production item is divided into a set of tasks which require an operation time for their execution, a usual and difficult problem, called assembly line balancing (ALB), is to determine how these tasks can be assigned to the stations fulfilling certain restrictions such as precedence relations. The final aim of ALB is to get an optimal assignment of subsets of tasks to the stations of the plant (Boysen et al. 2007). A well-known family of ALB problems is the simple assembly line balancing problem (SALBP) (Baybars 1986, Scholl and Becker 2006). The SALBP only considers the assignment of each task to a single station in such a way that all the precedence constraints are satisfied and no station workload time is greater than the line cycle time. As a result of the observation of the ALB operation in an automotive Nissan plant from Barcelona (Spain), Bautista and Pereira (2007) recently proposed a SALBP extension aiming to design a more realistic ALB model. They considered an additional space constraint to get a simplified but closer version to real-world situations, defining the time and space assembly line balancing problem (TSALBP). The TSALBP presents eight variants depending on three optimization criteria: m (the number of stations), c (the cycle time), and A (the area of the stations). The multicriteria nature of the TSALBP favoured the application of multiobjective meta-heuristics such as multiobjective ant colony optimization (Chica et al. 2010), evolutionary multiobjective optimization (Chica et al. 2011), and memetic algorithms (Chica et al. 2012). However, we noticed the absence of an available dataset with real-like instances for the TSALBP. And what is more, there is not any instance containing mixed product plans when the demand is uncertain. Therefore, we have implemented real-like Nissan TSALBP instance generator software (NTIGen) in order to let researchers to validate their models and methods in a diverse set of TSALBP instances and production plans. The design and implementation of NTIGen is done with the use of real data and industrial features of the Nissan industry plant of Barcelona. The software is freely available on-line to be used for future research works. Using this tool, a set of eight instances has been generated as a benchmark to show the different features of the instances. The rest of the paper is structured as follows. In Section 2 the TSALBP formulation is explained. The description of the NTIGen software is shown in Sections 3 and 4. A comparison of the eight instances generated by NTIGen is shown in Section 5. Some concluding remarks are given in Section 6.

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2 Time and Space Assembly Line Balancing Problem The manufacturing of a production item is divided into a set J of n tasks. Each task j requires an operation time for its execution tj > 0 that is determined as a function of the manufacturing technologies and the employed resources. Each station k (k = 1, 2,..., m) is assigned to a subset of tasks Sk (Sk ⊆ J ), called workload. Each task j can only be assigned to a single station k. Each task j has a set of direct “preceding tasks” Pj which must be accomplished before starting it. These constraints are normally represented by means of an acyclic precedence graph, whose vertices stand for the tasks and where a directed arc (i, j) indicates that task i must be finished before starting task j on the production line. Thus, task j cannot be assigned to a station that is ordered before the one where task i was assigned. Each station k also presents a station workload time t(Sk) that is equal to the sum of the tasks’ processing time assigned to the station k. SALBP focuses on grouping tasks in workstations by an efficient and coherent way. In this simplistic model there is a need of introducing space constraints in assembly lines’ design based on two main reasons: (a) the length of the workstation is limited in the majority of the situations, and (b) the required tools and components to be assembled should be distributed along the sides of the line. Hence, an area constraint may be considered by associating a required area aj to each task j and an available area Ak to each station k that, for the sake of simplicity, we shall assume it to be identical for every station and equal to A = maxk=1,2,...,mAk . Thus, each station k requires a station area a(Sk) that is equal to the sum of areas required by the tasks assigned to station k. This leads us to a new family of problems called TSALBP (Bautista and Pereira 2007). It may be stated as: given a set of n tasks with their temporal tj and spatial aj attributes (1 ≤ j ≤ n) and a precedence graph, each task must be assigned to a single station such that: (i) every precedence constraint is satisfied, (ii) no station workload time (t(Sk )) is greater than the cycle time (c), and (iii) no area required by any station (a(Sk)) is greater than the available area per station (A). TSALBP presents eight variants depending on three optimization criteria: m (the number of stations), c (the cycle time) and A (the area of the stations). Within these variants there are four multiobjective problems depending on the set of criteria to be minimized (m, c and/or A). For more information about the problem we refer the interested reader to Chica et al. (2010; 2012).

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3 Basics of the Nissan TSALBP Instance Generator Software (NTI-Gen) The main goal of the NTIGen software is to create real-like TSALBP instances with different features to serve as a benchmark for any future research work. Although there are ALB instances available online and even a SALBP instance generator (Otto et al. 2011), there is not any existing source where TSALBP instances can be generated and referred. Also, as pointed out in the Introduction section, there is no instance containing production plans information. Assembly lines in the automotive industry present a set of industrial features which condition the task and graph distribution of the problem instance. The user must be allowed to incorporate these industrial real-like features to the generated instances and these instances should be similar to the original Nissan instance context (Chica et al. 2012). Concretely, the developed NTIGen software includes the following features, which are illustrated in Figure 1:  Checkpoints: They are assembly line points in which workers test the quality and completeness of a set of operations previously finished. If we consider these checkpoints as new tasks, the representation of a checkpoint in an assembly line graph is given by a task having a high number of preceding tasks (for instance, task 11 in Figure 1).  Tasks without precedence: In real industrial scenarios, such tasks are justified if there are operations unconditioned by other operations. They are commonly found in the engine and trim lines of the car manufacturing. In Figure 1, tasks 1, 3, 8, 7, and 10 have no precedence.  Final tasks: Tasks in an assembly line which are associated to the most external and final operations of the product. They are represented as tasks with no successors in the precedence graph (tasks 12, 13 and 14 in Fig 1).  Isolated tasks: They can be performed at any part of the assembly of an item. An example of these kinds of tasks is this related with additional parts of a product which can be incorporated to the global product at any station. Task 4 in Figure 1 is an isolated task as it has no precedence.

Fig. 1 A precedence graph with 13 tasks showing examples of different kinds of tasks in an industrial context: chains of tasks, initial and final tasks, isolated tasks, and checkpoints.

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 Operations aggregation: This process comes up when some operations need the same tools or are done by the same worker. In this case, several tasks of the same stage are put together in just one task.  Operations breaking up: If possible, it is used in the industrial context to detail the implementation of an operation in different operating tasks. It is useful for balancing an assembly line when the cycle time is reduced.  Chains of tasks: They appear when there are strongly linked operations, normally in the same station or stage. A chain of tasks represents natural sequences of operations within the assembly process (see tasks 1, 2, 5, and 6 in Figure 1).

4 Tuneable Parameters of NTIGen The features introduced in the previous sub-section can be parameterized by the NTIGen user to generate a customizable instance. NTIGen is also fed by a set of stages with some initial tasks. By default, these stages and tasks correspond to the original Nissan instance with 140 tasks and 21 workstations (Chica et al. 2012) although they can be modified by the user before launching the application. The user can set all the desired features by changing the parameters of an XML file. The most important input parameters are the following:  Number of tasks (n). This is an important parameter of the instance that enormously conditions its complexity. From the initial set of tasks, new operating tasks are generated by breaking up them until reaching the user needs. If we need fewer tasks than the original ones, they are merged at random. The new generated tasks are required to belong to the same or close stages than their original ones.  Processing times (tj). The processing time of each task tj is randomly disrupted by a normal distribution within a user-defined interval. When creating or merging tasks, the processing times for the resulting tasks are reduced or duplicated, respectively. This is done to maintain the original situation of the Nissan instance.  Production plans. The production plans are always set to the NSIO original plans. The processing times of the tasks for the different engine products are created by randomly modifying the original processing time tj within the range [0.9tj, 1.1tj].  Cycle time (c). It is also disrupted independently from the processing times of the tasks. As done with tj, the disruption is created within a user-defined interval. In our case, the new cycle time is set to a value within [0.75c, 1.25c].  Required operation area (aj). Task areas are specified by two-dimensional units, i.e. length (aj) and width (bj). The first dimension, aj, is the truly useful variable for the TSALBP optimization. In the original instance, bj is always set 285


to one distance unit. To generate a new instance, the squared area of each task is always maintained by the generator but bj is randomly changed to a set value. In our case, the set is given by {0.5, 0.75, ..., 2.25}. This set of possible bj values can be modified by the user of the NTIGen software. Therefore, the length of each task aj, used for the optimization, is different for each generated TSALBP instance. As done with the processing times, aj is reduced or duplicated when increasing or decreasing the number of tasks to try to maintain the original Nissan situation. Apart from the operating tasks and their corresponding processing times and areas, NTIGen generates the precedence graph of the instance. These precedence relations are created between tasks of the same stage (generating chains) or different stages within a maximum window, set by the user, in order to link tasks which are industrially close. The minimum and maximum number of preceding tasks for a checkpoint in a problem instance can be set prior the instance generation. The same definition can be done for the number of initial, final, and isolated tasks. NTIGen creates precedence relations until it reaches the required complexity of the graph which is another important feature of an ALB instance (Bhattacharjee and Sahu 1990). This complexity of the precedence graph is also a user parameter and it is measured by the order strength (OS) of the graph (Dar-El 1975). The OS is calculated from the graph in transitive closure. The transitive closure of a set of direct precedences E is given by ET = {(i, j)|i ∈ V, j ∈ FiT }, with V being the set of nodes and FiT the set of indirect successors of the task i. The OS represents the number of ordering relations of the graph in a transitive closure with respect to all possible ordering relations: OS =

|ET |

n(n−1) 2

.

The OS varies between [0, 1]. If OS is equal to 0 the instance has no precedence relations but if OS takes value 1, there is just one feasible sequence of tasks. The result after running the NTIGen software is a structured text file describing the generated instance with the list of tasks, their operating times and area, and their precedence relations. The precedence relations form the transitive reduction of the graph in order to minimize computational resources. In addition, by changing the number of tasks, their processing time and area we can generate instances having different time variability (TV) and area variability (AV). Descriptors about the generated instance are listed after its creation to show the complexity of the graph, TV, AV, and the number of checkpoints, isolated, initial, and final tasks.

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5 Examples of some Generated TSALBP Instances By using the NTIGen software, a set of eight new TSALBP real-like instances have been created (Table 1). The NTIGen software and this set of TSALBP instances are publicly available at http://www.prothius.com/TSALBP. Table 1 Main characteristics of the generated TSALBP instances Features

P1

Random seed No. of tasks Cycle time

P2*

P3

P4

P5

P6

P7

P8

24151 N/A

117017

21277

113683

56399

5869

73553

100

190

220

280

320

376

420

199.97 180

207.07

222.42

221.62

169.552

186.65

137.751

OS

0.5

0.9

0.7

0.5

0.3

0.6

0.25

0.95

Precedences

156

140

293

314

304

407

435

548

608

Precs. window 5

N/A

5

1

2

1

3

2

TV

35.95

24

41.75

151.45

224.29

2742.28

901.34

1003.77

AV

500

513.86 266.67

300

400

200

300

133.33

Initial tasks

14

1

6

33

59

32

87

6

Final tasks

8

5

7

20

42

31

49

8

Isolated tasks 2

0

5

3

0

5

0

3

Checkpoints

N/A

0

6

7

1

12

0

3

6 Concluding Remarks The existing TSALBP formulation and previous ALB works do not cover an important real scenario where the same assembly line is devoted to produce mixed products and their demand is not fixed. Furthermore, the TSALBP instances of the literature were created by modifying ALB instances. The NTIGen software presented in this work allows researchers to create realistic TSALBP instances and production plans for future research. The generated TSALBP instances contain many real-like industrial features, e.g. checkpoints, isolated tasks, initial and final tasks, chains of tasks, or stages, which make the NTIGen software a practical tool for simulating the industrial conditions of an assembly line. Also, the NTIGen user can generate instances with production plans, having different operation time for each task of the assembly line.

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7 References Bautista, J., Pereira, J., 2007. Ant algorithms for a time and space constrained assembly line balancing problem. European Journal of Operational Research 177, 2016–2032. Baybars, I., 1986. A survey of exact algorithms for the simple assembly line balancing problem. Management Science 32, 909–932. Bhattacharjee, T.K., Sahu, S., 1990. Complexity of single model assembly line balancing problems. Engineering Costs and Production Economics 18, 203– 214. Boysen, N., Fliedner, M., Scholl, A., 2007. A classification of assembly line balancing problems. European Journal of Operational Research 183, 674–693. Chica, M., Cordón, O., Damas, S., 2011. An advanced multi-objective genetic algorithm design for the time and space assembly line balancing problem. Computers and Industrial Engineering 61, 103–117. Chica, M., Cordón, O., Damas, S., Bautista, J., 2010. Multiobjective, constructive heuristics for the 1/3 variant of the time and space assembly line balancing problem: ACO and random greedy search. Information Sciences 180, 3465– 3487. Chica, M., Cordón, O., Damas, S., Bautista, J., 2012. Multiobjective memetic algorithms for time and space assembly line balancing. Engineering Applications of Artificial Intelligence 25, 254–273. Dar-El, E.M., 1975. Solving large single-model assembly line balancing problems - A comparative study. IIE Transactions 7, 302–310. Otto, A., Otto, C., Scholl, A., 2011. SALBPgen - a systematic data generator for (simple) assembly line balancing. Jena Research Papers in Business and Economics 5. Scholl, A., Becker, C., 2006. State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research 168, 666–693.

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Agent-based Modelling and Archaeological Complexity Poza D1, del Olmo R2 Abstract This paper presents a brief overview of social simulation in the field of Archaeology. It has been conducted from an agent-based modelling focus, a very interesting and valid methodology for modelling prehistoric societies. The second part of this work presents an application of this methodology in a specific model that analyzes the emergence of ethnicity in a prehistoric society.

Keywords: Archaeology, Agent-based Modelling, Social Simulation, Ethnicity

1 Introduction Social simulation is a methodology where the modelled system is a social process. Its aim is to generate models of present or past realities that allow creating or validating theories about their regularities and, of course, their exceptions. Amongst all the modelling paradigms of Artificial Intelligence that allow social simulation, we have opted for Agent-based Modelling (hereafter ABM), which is defined by Gilbert (2007) as: “a computational method that enables a researcher to create, analyse and experiment with models composed of agents that interact within an environment”. The idea is to represent a human society by means of software-objects (the so-called agents) that interact between one another in a virtual environment. There exists a correspondence between the individuals in the real society and the agents in the virtual environment in such a way that observing 1David

J. Poza ( e-mail: [email protected]) INSISOC. E.I. Industriales. Universidad de Valladolid. Pso del Cauce s/n, 47011 Valladolid. 2Ricardo del Olmo ( e-mail: [email protected]) INSISOC. E.P.S. Universidad de Burgos. Avda. Cantabria s/n, 09006 Burgos.

* The authors acknowledge support from the Spanish Ministry of Science and Innovation Project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010) and by the Regional Government of Castile and Leon (Spain) Project VA056A12-2.

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the evolution of the simulation in our model allows us to draw conclusions on the individuals in the modelled society. ABM has some advantages that make it suitable for social research (Epstein 1999, Axtell 2000, Bonabeau 2002, Bousquet and Le Page 2004). We can summarize them as follows: it permits a more natural and transparent description of the modelled systems; it allows a realistic incorporation of explicit relationships from a geographic environment; it permits modelling local interactions, which implies considering the relationship between the micro-definition of the individuals and the macroscopic behaviour of the system; it captures the emerging behaviour, i.e. the appearance of new patters as a consequence of interactions at an elemental level (Holland 1998); and the possibility of including other dimensions (e.g. economical, social, geographical, technological, etc.) in a single model. Social simulation is accepted in many scientific environments, including Archaeology, due to its versatility to simulate individuals’ birth and death, their activities and their ways of interaction. As Barceló (2010a) puts it: “This methodology is considered fundamental in Prehistoric Archaeology, whose aim, human action in a remote past is by definition non-observable. Artificial societies allow us to represent hypothetical models of what could have happened, which facilitates the analysis and the comparison of those models”. This article is organized in two parts: First, we will analyze the relevance of social simulation in Archaeology, which will enable us to justify the importance of ABM when modelling and simulating prehistoric societies. Secondly, we will describe an application of ABM in the study of Ethnicity in a prehistoric society.

2 Archaeology and Agent-based Social Simulation Through the application of social simulation in Archaeology we can simulate the behaviour of individuals in past societies. “Archaeologists and historians have started to transform social theories into computer programs by simulating social beings – obviously not humans – that ‘live’ in virtual environments that result from the generalization of social theory or historic data. By means of the implementation of social events as computational agents and their mutual influences as interactions we want to discover that collective action can be described and explained as something non-accidental and non-chaotic” (Barceló 2010a). In the following paragraphs we will cite some examples and applications of ABM in this scientific domain that can be found in literature specialized in social and historic simulation. In their project EOS, Doran and Palmer (1995a, 1995b) studied the emergence of social order in the Palaeolithic Age. Doran (1999) continued this work to explain some features associated with the increase of social complexity. Other works related to hunter-gathering societies were conducted by Barceló (2010b, 2010c) to 290


study how local interactions facilitate cultural diffusion and ethnic differentiation, and Del Castillo and Barceló (2012). De La Cruz et al (2010) developed a general model of social behaviour of a fishing-hunting-gathering society with strict social norms and no political institutions. Dean et al (2000) use the model Sugarscape by Epstein y Axtell (1996) as the basis for establishing the population dynamics in the Anasazi society (Arizona) between centuries IX and XIV. Lake (2000) and Kohler et al (2000) studied spatial processes and resource management in ancient societies. Other similar works are: Gumerman et al (2003), Kohler et al (2007) and Johnson et al (2005). To complete this brief review, we will cite the works by Christiansen and Altaweel (2006) and Wilkinson et al (2007), related to the evolution and decadence of the settlements in Mesopotamia during the Bronze Age. The case of study by Barceló et al (2010c) that we describe in the following section evidences ABM’s capabilities to shed light on Archaeology research. Traditionally, ancient societies have been tackled through universal theoretical models. However, the use of Agent-based Modelling in the study of ancient societies has recently increased. This tool allows researchers to create artificial societies based on archaeological, ethnological and historical data and observe how they interact in a virtual environment. By means of computer simulations, one can analyse the parameters that affect the outcome of the simulations, which may lead to identify yet unknown social relationships.

3 A Case of Study: the Emergence of Ethnicity and Cultural Differentiation in Patagonian Hunter-gatherer Societies Ethnicity is the historical emergence of groups of people who share cultural characteristics in such a way that members within a group regard themselves and are regarded by others as truly distinctive (Cohen 2000). Ethnic differentiation is a consequence of how social agents have interacted over a period of time. Particularly, in the case of Patagonia’s hunter-gatherer societies - target of this study geographic separation among groups is believed to be crucial in the emergence of cultural groups: the further the groups, the less interactivity between groups and therefore, the more cultural differences between groups.

3.1 Description of the Model The model consists of a population of a fixed number (N) of agents that move randomly in a virtual space searching for economic resources and interacting with

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other agents. Each agent represents a household in the Patagonian hunter-gatherer society under study. All the agents are identical, except for two properties:  Capacity (cj∈N ): This parameter represents each agent’s ability to exploit natural resources: cj∈N ∈ [0,1].  Cultural identity (Axelrod 1997): an integer vector of k features (i.e. cultural dimensions) that can take any value {1, 2, …, r} within a set of r cultural traits. In other words, each agent has k features each of which represent a cultural dimension (e.g. language, religious beliefs, etc.) and, each cultural dimension can take r different values (cultural traits). The virtual space where the agents interact is a finite toroidal grid made up of regular patches. The agents interact with other agents from their neighbourhood as long as they belong to the same cultural group. The size of the neighbourhood is given by the parameter η. In order to determine what agents belong to the same cultural group, the model computes the cultural proximity within the agents. Cultural proximity is measured by the relative number of shared cultural dimensions. That is to say, two households consider they belong to the same ethnical group if the number of cultural dimensions they share is above a certain threshold δ, which is another parameter of the model (cultural proximity). Therefore, an agent’s local group (i.e. the set of agents with whom she will interact during the current simulation period) consists of other culturally-close agents within her neighbourhood (see Figure 1). The model considers increasing returns-to-cooperation (given by a parameter θ) which means that families get more resources when they cooperate than when they act individually (i.e. the fact that θ > 1 represents the fact that the amount of resources collected by two agents that cooperate is more than twice the amount of resources they would collect if they acted individually). Therefore, the output (i.e. the amount of resources) that an agent j gets depends of her own capacity c j, the sum of the capacities of the agents within her local group Gj(t) and the value of the parameter return-to-cooperation θ according to equation 1: Oj (t) = cj (∑k∈Gj (t) ck )

θ−1

with θ ≥ 1

(1)

Each agent j has a surplus Sj (t+1) that depends on three factors (equation 2):  The output obtained at the current period Oj(t) given by equation (1).  The remaining surplus from previous periods Sj (t) multiplied by a depreciation factor (1 – ρ)  The amount of resources each agent consumes every period S0: 𝑆𝑗 (𝑡 + 1) = 𝑂𝑗 + 𝑆𝑗 (𝑡)(1 − 𝜌) − 𝑆𝑜

292

(2)


Fig. 1 An example of a local group from household1’s viewpoint for a given neighbourhood radius η. We have considered k=5 cultural dimensions (which means that cultural identity vectors have length 5) and r=5 cultural traits (i.e. each cultural dimension can take a value between 1 and 5). The parameter cultural proximity δ takes the value 0.4 which means that the agents within agent 1’s neighbourhood need to share, at least, 2 (out of 5) cultural traits to be considered a member of her local group. This condition holds for agents 2, 3 and 4, but not for agent 5. Therefore, agents 2, 3 and 4 will cooperate with agent 1 in the current simulation period. Agent 6 belongs to the same ethnic group as agent 1 (as they share, at least, a proportion of δ cultural traits), but she is outside her local group and thus she will not cooperate in the current simulation period.

Culture diffusion and ethnical differentiation occurs through local interactions within the population. On the one hand, culture diffuses within agents that interact in the same local group by copying – with certain probability pdiff – the most frequent trait in her cultural group. This process favours the emergence of culturallyclose groups. On the other hand, culture may evolve by means of a local mutation process, in which an agent can mutate one of her cultural traits with certain probability pmut. When this occurs, the new cultural traits are copied by all the agents in her local group. Agents may die at some point during the simulation due to two reasons:  Dead by old age: agents have certain life expectancy: her maximum age follows a Poisson distribution with mean a particular life expectancy (another parameter of the model). The agents’ age increases at every simulation step. Agents die when they reach their maximum age.  Death of starvation: At every simulation step, agents consume an amount of surplus equal to S0. Agents die when they run out of surplus (Sj = 0). Independently from the reason why an agent dies, she is replaced by another agent in such a way the number of agents remains constant (and equal to N). The 293


new agent will inherit the cultural dimensions of an agent in the population chosen through a roulette wheel (i.e. the probability that an agent is replicated is proportional to her surplus). The simulation takes place as follows: at a time period t the agents move randomly to one of their neighbour patches. Then, they determine what their local is (agents within a distance η that are culturally-close – that is to say - agents that share at least a proportion of δ cultural traits). The cooperation of the agents that belong to the same local group may result in an increasing return-to-cooperation, according to equation 1. Then, the agent’s surplus at the current simulation period is computed through equation 2. Afterwards, with probability pdiff, she copies a trait (the mode of the traits of her local group); and, with probability p mut, she mutates one of her traits and spreads it to her local group. Agents are replaced either if they do not have enough surplus or if they reach their maximum age. Finally, the number and the size of the ethnic groups (i.e. all the agents in the population that share at least a proportion of δ cultural traits) at this period of the simulation are computed.

3.2 Results This relatively simple model is the first approach to a more complex model that will permit Archaeology researchers to test different social theories by means of computational simulation. The simulations performed revealed the influence of the increasing returns-to-cooperation parameter (θ) and the cultural proximity parameter (δ) on the emergence of ethnic groups3. In fact, it was found that both parameters have a crucial effect on the outcome of the simulations (i.e. the number and the size of the ethnic groups). For low values of δ, the agents only need to share a few cultural traits to be considered members of the same ethnical group. This gives rise to one simple ethnic group in which cultural mutation and local diffusion processes are not enough to break the group’s ethnic identity. However, when the value of δ is increased, cultural mutation and local diffusion split the population into several ethnic groups. On the other hand, when the value of the parameter θ is low, the size of the emergent ethnical groups is small. Low values of θ mean low returns-tocooperation. In fact, for θ1, cooperating with the local group does not provide more surplus than acting individually. Consequently, the replication process facilitates the reproduction of any emerged cultural differentiation and therefore we observe a higher number of ethnic groups. For larger values of θ, cooperating within 3

All the experiments were conducted with the following parameters: N=50; η = 2; k=8; r=8; pdiff=0.8, pmut=0.05; S0=0.4 and ρ=0.5.

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a local group yields more surplus and therefore agents who cooperate get more replications in the future generations, which splits the population into a smaller number of ethnic groups. One of the conclusions we can draw from this brief study is that ABM is a really relevant burgeoning methodology in social simulation in general and in Archaeology in particular. A proof of that is the model by Barceló et al (2010c) that we have described in this paper. It is an outstanding example of how ABM and Archaeology can be jointly used in the study of the emergence of ethnicity and cultural differentiation in ancient societies. This model is currently being extended in order to simulate a more realistic behaviour. In fact, in the current version of the model, the agents always cooperate with other agents (as long as they are culturally similar). However, being culturally similar might not be a sufficient condition to cooperate. In order to make the agents decide whether to cooperate or not, the patches will be endowed with random amounts of resource and different levels of accessibility to those resources. This has an important implication: the agents will act by themselves unless they cannot get enough resources to survive (because there are too little resources, they are hard to collect, or the agents’ capacities are low). If this is the case, they will ask other culturally-close agents for help. However, this demand for help might be rejected by other agents if their capacity does not even let them collect the resources they need to survive.

4 References Axelrod, R. (1997) The dissemination of culture. J of Conflict Resolution, 41(2), pp.203–226. Axtell RL (2000) Why agents? On the varied motivations for agent computing in the social sciences. In CM Macal and D Sallach (eds.), Proceedings of the Workshop on Agent Simulation: Applications, Models, and Tools, pp. 3-24. Argonne National Laboratory, Argonne. Barceló JA (2010a) Sociedades artificiales para el análisis de procesos sociales en la prehistoria. CPAG 20:123-148. Barceló JA, Cuesta F, Del Castillo F et al (2010b) Simulating social, economic and political decisions in a hunter-gatherer group. The case of prehistoric Patagonia. Computer Applications in Archaeology Conference. http://www.leidenuniv.nl/caa/caa_proceedings.htm, Leiden. Barceló JA, Cuesta F, Del Castillo F et al (2010c) Simulating prehistoric ethnicity. The case of patagonian hunter-gatherers. In Contreras F and Melero M (eds.), Fussion of Cultures. Computer Applications and Quantitative Methods in Archaeology, (in press). Bonabeau E (2002) Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Science of the USA 99(2):7280-7287. Bousquet F, Le Page C (2004) Multi-agent simulations and ecosystem management: A review. Ecological Modelling 176(3-4):313-332. Christiansen J, Altaweel M (2006) Simulation of natural and social process interactions: an example from Bronze Age Mesopotamia. Social Science Computer Review, 24(2):209-226. Cohen, A.P. (2000). Signifying Identities: Anthropological Perspectives on Boundaries and Contested Values, London: Routledge.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Dean JS, Gumerman GS, Epstein JE et al (2000) Understanding Anasazi culture change through agent-based modelling. In Kohler TA and Gumerman G (eds.), Dynamics in Human and Primate Societies, pp. 179-205. Oxford Univer. Pres, New York. De La Cruz D, Estévez J, Noriega P et al (2010) Normas en sociedades cazadoras-pesacadorasrecolectoras. Argumentos para el uso de la simulación social basada en agentes. CPAG 20:149-161. Del Castillo F, Barceló JA (2012) Why hunter and gatherers did not die more often? Simulating prehistoric decision making. Proceedings of the Computer Applications and Quantitative Methods in Archaeology Congress. Amsterdam University Press (in press). Doran JE, Palmer M (1995a) The EOS project: integrating two models of palaeolithic social change. In Gilbert N and Conte R (eds.), Artificial Societies: The Computer Simulation of Social Life, pp. 103-125. UCL Press, London. Doran JE, Palmer M (1995b) The EOS project: modelling prehistoric sociocultural trajectories. Proceedings of First International Symposium on Computing and Archaeology, pp. 183-198. Doran JE (1999) Prospects for agent-based modelling in archaeology. Archeologia e Calcolatori 10:33-44. Epstein JM (1999) Agent-based computational models and generative social science. Complexity 4(5):41-60. Epstein JM, Axtell R (1996) Growing artificial societies: social sciences from the ground up. Brooking Institution Press. Washington. Gilbert N (2007) Agent based model. Sage, London. Gumerman G, Swedlund AC, Dean JS, Epstein JS (2003) The evolution of social behaviour in the prehistoric American Southwest. Artificial Life 9(4):435-444. Holland JH (1998) Emergence. From chaos to order. Addison-Wesley, Reading. Johnson CD, Kohler TA, Cowan JA (2005) Modeling historical ecology, thinking about contemporaly systems. American Anthropologist 107:96-108. Kohler TA, Kresl J, Van West CR, Carr E, Wilshusen R (2000) Be there then: A modelling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Mesa Verde region, U.S. southwest. In Kohler TA and Gumerman GJ (eds.), Dynamics in Human and Primate Societies, pp. 145-178. Oxford U. Press, New York. Kohler TA, Gumerman G, Reynolds RG (2005) Simulating ancient societies. Scientific American 293:77-84. Lake MW (2000) MAGICAL computer simulation of mesolithic foraging. In Kohler TA and Gumerman GJ (eds.), Dynamics in Human and Primate Societies pp. 107-143. Oxford U Press, New York. Wilkinson TJ, Christiansen J, Ur J et al (2007) Urbanization within a dynamic environment: modelling bronze age communities in upper Mesopotamia. A.Anthropologist 109(1):52-68 .

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Optimizing Stochastic Supply Chains via Simulation: What is an Appropriate Simulation Run Length? Arreola-Risa A1, Fortuny-Santos J2, Vintró-Sánchez C3 Abstract The most common solution strategy for stochastic supply-chain management problems that are analytically intractable is simulation. But, how can we be sure that the optimal solution obtained by simulation is in fact the true optimal solution? In this paper we try to shed light on this question. We report the results of an extensive simulation study of a base-stock controlled production-inventory system. We tried different values of base-stock levels (R) to determine, via simulation, which was the value that minimized the total inventory holding and backordering costs per period. For 25 different cases (and 100 replications each), we compared the optimal solution obtained from simulation (Rs*) with the true optimal base-stock level (Ra*) obtained from an analytical result, with the goal of obtaining a lower bound of 95% matches. Results show that when the traffic intensity increases, the run length necessary to achieve a minimum of 95% matches increases too, and when the backorder cost increases, the number of matches decreases for each specific run length. In most of the cases simulated, 100,000 demands were enough to achieve reasonably reliable results.

Keywords: Stochastic Supply Chains, Optimization, Simulation

1

Antonio Arreola-Risa Mays Business School. Texas A&M University, College Station (TX), USA. 2

Jordi Fortuny-Santos (e-mail: [email protected]) Business Organization Department, Technical University of Catalonia, Manresa, Spain. 3

Carla Vintró-Sánchez Business Organization Department, Technical University of Catalonia, Manresa, Spain.

297


1 Introduction There is a vast literature on inventory control in production-inventory systems. Many models have been created in order to address issues such as lead time demand, advanced information, or optimal policies. Nowadays, these issues have gained relevance, because we now consider not an isolated company but a chain of companies commonly called a supply chain. Difficulties arise when one tries to solve the above-mentioned models for supply chains. Equations including convolutions and mixtures of random variables soon become intractable and out of the reach of analytic tools. Consequently, these intractable models are usually tested by means of simulation. Researchers develop their own computerized simulators or use commercial applications such as ARENA or PROMODEL. But, how can we be sure that the results yielded by the simulator correspond to the true optimal solution? This question has been studied by researchers in other settings for a long time, especially from the point of view of Statistics, and different tools have been developed; however, those statistical tools are not applicable to our problem setting because the decision variables of interest are discrete. This question is also of interest for practitioners because simulation is widely used by companies in the real world. In fact, this research arises from the needs of a global energy company that required frequent use of simulation for decision making on a supply chain project. Optimization results had to be reliable and accurate but the simulation run length had to be reasonably short. In this paper, we try to shed light on the problem of finding a relationship between simulation run length and the reliability of a simulation optimization results. We have selected a stylized model of a supply chain studied by Arreola-Risa (1996), where demand is a Poisson process, unit manufacturing times are exponentially distributed, inventory is controlled by a base-stock level, and we are interested in the steady-state behaviour of the supply chain. There are two reasons for our selection of such model. First, the studied model is ergodic and hence a steady-state is guaranteed to exist, and to the best of our knowledge, it is one of a few instances where the optimal value of the base-stock level has been determined analytically. Hence we can compare the optimal base-stock level obtained via simulation to the truly optimal base-stock level. Second, given that Poisson demand and exponential unit manufacturing times represent extreme cases of variability in realworld situation (Knott and Sury 1987, and Buzacott and Shanthikumar 1993), our results represent upper bounds for practical settings that researchers may study and practitioners may find in practice.

298


2 Literature Review The relation between simulation run length and accuracy of the results is qualitatively well known. Broadly speaking, the longer the simulation, the better results we get. It is based on the fact that, in general, as sample size increases, estimates improve in statistical accuracy and, when it comes to queuing problems, they have a transient period and then a steady state which is necessary to reach to collect meaningful statistics from the simulation. The longer the simulation run, the higher the probability that the steady state has been reached. The problem of convergence for an M/M/1 system is analyzed by Fishman (1978). Fishman (1971) had already set forth an autoregressive approach for estimating the sample size of a process with a specified level of precision in simulation experiments. That procedure was intended to determine when enough data had been collected in ongoing experiments. Whitt (1989) finds heuristics to be used to estimate run lengths before the simulation starts. For the particular case of an M/M/1 model, results show that, with a 5% error and a 95% confidence, a length of 27,500 periods is enough for a traffic intensity () of 0.8 while 592,000 periods are necessary for a level of  equal to 0.95. As stated above, in our research, we simulate a base-stock controlled production-inventory system. Under this approach, we have a warehouse (or an inventory supermarket in lean manufacturing) that has an amount, called base-stock level, of inventory (Rs) of a certain item. Demand for that item, stochastic in nature, is immediately served -if enough units are in stock, and a replenishment order is immediately placed to the production system (i.e. by means of kanban cards, or the equivalent, in lean companies where production is adjusted to demand). The behavior of a base-stock policy has been studied by Clark and Scarf (1960), Zipkin (1991) and Veatch and Wein (1994) amongst others. And besides the analytical approach, base-stock level has also been used in simulation. Liberopoulos and Koukoumialos (2005) determine the optimal base-stock level using simulation. In each experiment the authors used a simulation run length of 60 million time units. That yielded 95% confidence intervals on the estimated values of cost and base-stock level with half width values of less than 0.5% or 4% of their respective estimated values. Snyder and Schen (2006) test the supply and demand uncertainty using base-stock level. They made 10 independent replications with 10,000 periods each and 100 warm-up periods.

299


3 Research Approach: a Simulation Experiment In order to determine the necessary simulation run, we have carried out a simulation experiment. We have designed our own computer simulator in C++ language. Parameter input and data output are captured in EXCEL spreadsheets. We have simulated a base-stock controlled production-inventory system where a warehouse has an initial amount of inventory (R). Demand is stochastic and each arriving demand is for one item. When a demand arrives, it is immediately served -if possible- following the first-come first-served (FCFS) rule, and an order is placed to the production system. After production is completed, the item is instantaneously delivered to the warehouse. Demands that cannot be fulfilled because the warehouse is temporarily out of stock are backordered. In this model, we change the value of R in order to find which one minimizes the sum of inventory holding and demand backordering costs. That value is the optimal base-stock level (Rs*). We have assumed that demand is a Poisson process and unit manufacturing time is exponentially distributed. There are two main reasons for these assumptions. The first one is that this problem has been solved analytically and therefore we know which is the optimal solution that should be obtained via simulation. The second one is that the Poisson and exponential distributions represent extreme practical cases of randomness and therefore if a simulation run length is valid for such disperse results, it will be an upper bound for other models with less variability. We have considered different levels of backorder cost per unit at the warehouse (p): 2, 4, 8, 16 and 32 times the holding cost per unit per unit time (h). The relationship between supply and demand is modeled in terms of the traffic intensity () defined as the average arrival rate () divided by the average service rate ( ). Five traffic intensity values were used: 0.1, 0.3, 0.5, 0.7 and 0.9. The combination of cost ratios (p/h) and traffic intensities () gives 25 different cases to be simulated (Table 1). For example, case 13 represents a product being manufactured in a facility that operates at capacity utilization of 50% and with a backorder cost rate that is 8 times the holding cost rate. Table 1 Simulation cases Traffic intensity () Cost ratio (p/h)

0.1

0.3

0.5

0.7

0.9

2

1

6

11

16

21

4

2

7

12

17

22

8

3

8

13

18

23

16

4

9

14

19

24

32

5

10

15

20

25

300


The simulation experiment for each of the 25 cases included 100 independent replications. The warm up period was set equal to 1,000 demand arrivals. Then, cost data was collected for the following n demand arrivals, where n is the proxy for simulation length and hence the control variable in our simulation experiment. In order to gather information on the relationship between n and the accuracy of the simulation results, for each of the 25 cases and each of the 100 runs per case, the authors exhaustively tried different values of R in order to determine the optimal base-stock level (Rs*) and compared it with the true optimal base-stock level (Ra*) obtained from the analytical result, to know how many times (out of 100) Rs* is exactly equal to Ra* for each value of n. Values of n in the range 100 to 10,000,000 were tested with the aim of reaching Ra* in, at least, 95 replications. Equation 1.1 is the analytical formula for the optimal base-stock level (Ra*), where x  denotes the greatest integer less than or equal to x.    h   ln h  1   p    *  Ra    ln     

(1.1)

Table 2 summarizes the following two analytical results for the 25 simulated cases: The optimal base-stock level (Ra*) and its associated expected total cost E(TC)[h, p, Ra*], where E(·) is the expected value operator. The system decision variable in the simulation experiment is the base-stock level R. Let E(OH) and E(BO) respectively be the expected on-hand inventory and the expected number of backorders per unit time (both functions of R). Equation 1.2 describes the system’s objective function as the sum of the expected inventory holding cost and demand backordering costs. E(TC)[h, p, R] = hE(OH) + pE(BO)

(1.2)

Table 2 Analytical values of optimal base-stock level (Ra*) and the expected total cost (E(TC)[h, p, Ra*)]) for each simulation case. The expected total cost is in parenthesis Traffic intensity () Cost ratio (p/h)

0.1

0.3

0.5

0.7

0.9

2

1 (1.100)

1 (1.300)

1 (1.500)

1 (1.700)

1 (1.900)

4

1 (1.300)

1 (1.900)

2 (2.250)

2 (2.770)

3 (3.477)

8

1 (1.700)

2 (2.330)

3 (3.125)

4 (4.148)

6 (6.035)

16

2 (2.050)

3 (3.015)

4 (4.063)

5 (5.748)

9 (9.686)

32

2 (2.210)

3 (3.447)

5 (5.031)

7 (7.494)

14 (14.380)

301


Next, by means of case 13 ( = 0.5; p/h = 8), we describe the procedure to determine the rung length. The same procedure was applied to each one of the 25 cases. Table 2 shows that when  = 0.5 and p/h = 8, Ra* is 3 units of the item, with an expected total cost of 3.125 monetary units. We set the simulation parameters, including the simulation length (n = 100) and run the simulation (created the queue). We computed the costs for different values of R (i.e. between 0 and 10). For each run (one hundred independent runs were made), Rs* was selected as the value of R that minimized the expected total inventory costs (results were between 2 and 5 units). Rs* matched Ra* in 63% of the runs. That result did not reach the minimum bound of 95% hits. The experiment was repeated one hundred more times for n = 1,000 periods .The number of hits improved to 93% but it was still unsatisfactory. Finally, after one hundred more replications with n = 10,000 periods, Rs* matched Ra* in 100% of the runs. Figure 1 shows that the number of hits (Rs* = Ra*) increases with the length of the simulation n.

100%

100

Percentage of hits (R s* = R a*)

93%

Results (in percentage)

90 80 70

63%

60

n=100

50

n=1,000

40

n=10,000

32%

30 20 10

7%

4%

1%

0 2

3

4

5

Base stock level (Rs *)

Fig 1 Summary of the simulation experiment results for case where  = 0.5 and p/h = 8

4 Results The simulation experiment required more than 7,500 runs. The percentages of runs in which Rs* = Ra* are presented in Table 3. 302


Note that we increased exponentially the number of periods to be simulated (n) in order to reach at least 95% hits (Rs* = Ra*) in the simulation experiment. We first defined the experiment with n = 100; 1,000 and 10,000 periods. Since the predefined values of n were not enough for higher values of traffic intensity ( ), we considered values of n up to 100,000 periods. In most of the cases simulated, we reached a 100% of hits. We do not include the values of Rs* nor the values of E(TC)[h, p, R] obtained in the simulation since the aim of the experiment was to determine the minimum number of runs needed to ensure that the simulation of the supply chain has achieved steady state and consequently, that the optimal base-stock level obtained in the simulation (Rs*) is in fact the optimal solution of the inventory system under study (Ra*). Table 3 Summary of the simulation experiment results (number of hits: Rs*= Ra*) for the 25 cases considered Case



p/h

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

0.1 0.1 0.1 0.1 0.1 0.3 0.3 0.3 0.3 0.3 0.5 0.5 0.5 0.5 0.5 0.7 0.7 0.7 0.7 0.7 0.9 0.9 0.9 0.9 0.9

2 4 8 16 32 2 4 8 16 32 2 4 8 16 32 2 4 8 16 32 2 4 8 16 32

102

103

Periods (n) 104 105

100 100 99 100 100 100 76 99 54 82 99 99 63 41 35

100 100 100 100 100 100 100 100 66 99 100 100 93 75 64 100 92 70 66 51

100 100 100 100 100 100 100 100 81 100 100 100 100 94 69 100 100 99 94 93

303

106

107

100 100

100 96 100 100 100 100 100 100 100 60 95 85

100 100

100 100 90 99 100

100 100 100 99 100


5 Findings, Relevance and Concluding Remarks This paper fills a void in the literature by providing supply-chain management researchers and practitioners with a practical understanding of the necessary length of a simulation run to achieve reasonably reliable results. We know of cases where researchers had no choice but to perform simulations with more than one billion demands in order to be sure that they had reached the steady state and hence reliable results. Our simulation experiment suggests that in most practical situations, simulating 100,000 demands should be enough, given that Poisson demands and exponential unit manufacturing times represent upper bounds for most supply chains that would be found in the real world. An analysis of the results in Table 4 reveals the behavior of the system:  For each of the 25 cases, as expected, the number of hits (Rs*= Ra*) increases with the length of the simulation n.  For each cost ratio p/h, when the traffic intensity ( ) increases, the run length necessary to achieve a 100% of correct results increases too. For example, for a cost of p/h = 32, when  = 0.1, a simulation of 100 demands is enough, and when  = 0.9, a simulation of 1,000,000 is required. This is because the system requires more time to achieve the steady state due to a higher congestion level. In consequence, the results from a small n, do not correspond to the steady state of the system and in consequence they do not correspond to the expected value of Ra*, which is derived for the steady state.  For each level of traffic intensity ( ), when the backorder cost (p/h) increases, the number of hits (the reliability in predicting the optimal value of the basestock level) decreases for each specific run length. For example, if we take cases 16 to 20 in Table 4 (= 0.7) and look at the number of hits for one thousand order arrivals (n = 1,000), they fall from 100 times (if p/h = 2) to 51 times (if p/h = 32). Therefore, the number of demands in the simulation must go up to increase reliability. The main limitation of our research is that it considers only one productioninventory system configuration. It can be extended to other configurations, as long as we have optimal analytical results to use.

6 References Arreola-Risa A (1996) Integrated multi-item production-inventory systems. European Journal of Operational Research 89(2):326-340 Buzacott JA, Shantikumar JG (1993) Stochastic Models of Manufacturing Systems. PrenticeHall, Englewood Cliffs, New Jersey. Clark AJ, Scarf H (1960) Optimal policies for multi-echelon inventory problem. Management Science 6(4):475-490

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Fishman GS (1971) Estimating sample size in computing simulation experiments. Management Science 18(1):21-38 Fishman GS (1978) Principles of Discrete Event Simulation. John Wiley & Sons, New York: 219-237 Knott K, Sury RJ (1987) A study of work-time distributions of unpaced tasks. IIE Transactions 19:50-55 Liberopoulos G, Koukoumialos S (2005) Trade-offs between base stock levels, numbers of kanbans and planned supply lead times in production/inventory systems with advance demand information. International Journal of Production Economics 96(2):213–232 Snyder LV, Shen ZJM (2006) Supply and Demand Uncertainty in Multi-Echelon Supply Chains. Working Paper. Online. http://www.ieor.berkeley.edu/~shen/papers/paper38.pdf. Cited 12 February 2013 Veatch MH, Wein LM (1994) Optimal control of a two-station tandem production/inventory. Operations Research 42:337-350 Whitt W (1989) Planning Queuing Simulations. Management Science 35(11):1341-1366 Zipkin P (1991) Evaluation of base-stock policies in multiechelon inventory systems with compound-Poisson demands. Naval Research Logistics 38(3):397-412

305


Localization Based on Business Interactions through a Simulated Annealing Algorithm Sánchez R.M1, Galán J.M2, Santos J.I3 Abstract This work is aimed at presenting a simulated annealing algorithm as a decision support tool for the localization problem of stores in metropolitan areas. The approach is based on the empirical estimation of attraction and repulsive forces that emerge as a consequence of the spatial interaction among businesses. Quantification of these externalities is carried out by means of networks modelling techniques. The methodology is illustrated with a case study in the city of Turin (Italy).

Keywords: Simulated Annealing, Localization Problem, Complex Networks, Externalities, Decision Support Tools

1 Introduction Economic and industrial organization literature has analysed and postulated theories about the relationships that exist among the different types of business and how they affect each other in their location decisions. Many of these models lack of a formal formulation to quantify these interactions. Recently, some authors have proposed methodologies to begin to understand quantitatively the nature of

1

Rosa Mª Sánchez Saiz ( e-mail: [email protected]) Área de Organización de Empresas. Departamento de Ingeniería Civil.EPS. UBU. C. Villadiego S/N, 09001 Burgos. 2 José Manuel Galán Ordax ( e-mail: [email protected]) Área de Organización de Empresas. Departamento de Ingeniería Civil.EPS. UBU. C. Villadiego S/N, 09001 Burgos. 3

José Ignacio Santos Martín ( e-mail: [email protected]) Área de Organización de Empresas. Departamento de Ingeniería Civil.EPS. UBU. C. Villadiego S/N, 09001 Burgos.

306


these phenomena (Duranton and Overman, 2005;Gómez et al., 2009;Jensen, 2006;Jensen, 2009). Location patterns of firms do not seem the result of individual independent decisions or purely random events, but they are, at least partly, consequence of repulsive, attractive or mutual indifference forces among them (Hoover and Giarratani, 1984). Repulsive forces are usually found in business focused on input or customer markets, and on those that do not work for profit, such as foundations, associations, schools, universities and health centres. In these cases, firms make production and pricing decisions in response to how customers are spatially located, which conditions spatial patterns. Some of the classical models of spatial competition, as Hotelling (1929), show that geographic concurrence can emerge as consequence of competing stores trying to capture sales in central areas. However, there are other activities characterized by agglomerative patterns, for example: Companies that produce differentiated products that may vary in several aspects, requiring that buyers inspect them in person. This applies to car dealers, nightlife districts, advertising, clothing stores, etc. In these cases competitors often locate close together creating clusters. Companies in dynamic environments, in terms of products or production cycles, which require the use of expensive specialized machinery. In these cases concentration may make possible reducing production costs by means of sharing input factors or the appearance of suppliers specialized in particular operations that improve the efficiency of the whole cluster. In the most general cases there is a combination of repulsion and attraction forces among competitors. In this paper we briefly analyse the foundations of some methodologies that capture empirically aggregation and dispersion phenomena, and the forces of attraction and repulsion. Those methodologies go beyond the relations between activities of the same type and generalize the idea to interactions among different types of businesses, e.g. searching for possible complementarities. We illustrate in a particular case study the use of this formalization together with a fitness function and a simulated annealing algorithm as a decision making tool to find candidate locations that explicitly takes into account interaction externalities.

307


2 Method

2.1 Network-based Model of Attraction and Repulsion Forces A recent attempt to study quantitatively the relationships of interaction between businesses corresponds to Duranton and Overman (2005). Although they focus on the spatial distribution of industries, and not on the distribution of commercial stores in urban areas like our case, their approach is interesting because it makes use of the statistical properties of the empirical data to infer agglomeration measures. Inspired by Duranton and Overman work, Jensen et al (Gómez et al., 2009;Jensen, 2006;Jensen, 2009) proposed an original network-based approach to quantify empirically the intensity of the attraction and repulsion forces between commercial stores. Suppose an urban area with 𝑁𝑇 stores corresponding to a set of sites 𝑇 = {𝑇𝑖 ; 𝑖 = 1, … , 𝑁𝑇 } where they are placed. The subset 𝐴 = {𝐴𝑖 ; 𝑖 = 1, … , 𝑁𝐴 } is formed by the 𝑁𝐴 sites occupied by stores of type A. For each site 𝑆 ∈ 𝐴, we define the variables 𝑁𝑇 (𝑆, 𝑟) and 𝑁𝐴 (𝑆, 𝑟) as the number of respectively total and Astores, including S, whose distance from the site S is less than or equal to a radius r. The spatial interaction between A-stores is quantified by an intra-attraction coefficient 𝑀𝐴𝐴 (𝑟) as follows: 𝑀𝐴𝐴 (𝑟) =

𝑁𝑇 −1 𝑁𝐴 (𝑁𝐴 −1)

𝐴 ∑𝑁 𝑖=1

𝑁𝐴 (𝐴𝑖 ,𝑟) 𝑁𝑇 (𝐴𝑖, ,𝑟)

(1.1)

The coefficient 𝑀𝐴𝐴 (𝑟) is an average over the 𝑁𝐴 A-stores of the result of di𝑁 (𝐴 ,𝑟) 𝑁 −1 viding the local aggregation ratio 𝐴 𝑖 and the total aggregation ratio 𝑇 . 𝑁𝑇 (𝐴𝑖, ,𝑟)

𝑁𝐴 −1

When 𝑀𝐴𝐴 (𝑟) > 1 we say that the type of stores A shows spatial aggregation, i.e. the local aggregation average of A-stores is greater than the expected value if they were randomly distributed in the set of sites T. On the other hand, when 𝑀𝐴𝐴 (𝑟) < 1 we say that the type of stores A shows spatial dispersion. We can easily generalize the last measure to all sites 𝑆 ∈ 𝑇 and any pair of types of stores A and B. Now, the spatial interaction between A-stores and Bstores is quantified by an inter-attraction coefficient 𝑀𝐴𝐵 (𝑟) as follows: 𝑀𝐴𝐵 (𝑟) =

𝑁𝑇 −𝑁𝐴 𝑁𝐴 𝑁𝐵

𝐴 ∑𝑁 𝑖=1

𝑁𝐵 (𝐴𝑖, ,𝑟) 𝑁𝑇 (𝐴𝑖 ,𝑟)−𝑁𝐴 (𝐴𝑖 ,𝑟)

(1.2)

Where 𝑁𝑇 (𝐴𝑖 , 𝑟), 𝑁𝐴 (𝐴𝑖 , 𝑟) and 𝑁𝐵 (𝐴𝑖 , 𝑟) are the number of respectively total, A-stores and B-stores whose distance from the site 𝐴𝑖 is less than or equal to the radius r. In this case, when 𝑀𝐴𝐵 (𝑟) > 1 we say that the type of stores A attracts B-stores, i.e. the local aggregation average of B-stores around A-stores is greater 308


than the expected value assuming that B-stores were randomly distributed; and consequently we say that the type of stores A repulses B-stores when 𝑀𝐴𝐵 (𝑟) < 1. The intra and inter attraction coefficients can be used to model the spatial interaction between commercial stores as a network (Gómez et al., 2009;Jensen, 2009). It is not difficult to see the matrix of the attraction coefficients as an adjacency matrix of a weighted directed network (Newman, 2003). The nodes of this interaction network are the set of types of stores, and the weights of the links between any pair of nodes A and B is defined as: ∝𝐴𝐵 = log(𝑀𝐴𝐵 )

(1.3)

The logarithmic transformation of the attraction coefficients makes easy the interpretation of the link weights: a positive value means a relationship of attraction and negative one a relationship of repulsion.

3 Localization Decision Making Using a Simulated Annealing Algorithm

3.1 Case Study To illustrate our approach we have considered interactions among 21 types of business (see Fig. 1) located in the area of Turin, an Italian city in the north of the country. Our database contains 3866 georeferenced stores ranging from 541 in the case of the most numerous type, to 23 in the case of the less.

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Fig. 1 Different types of business considered in our analysis and their spatial location

We have computed the attraction matrix among the different types of stores following the explained methodology. The results of the main types of interactions are summarized in Fig. 2 as a graph, where each element ∝AB of the matrix is represented as a link showing the interaction between A and B type of business.

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Fig. 2 Interactions among the different types of business considered. Colour of nodes represents different classes found after applying a community detection algorithm. Node sizes show the number of stores of each type included in the analysis, green links represent positive associations while pink links represent negative associations. The figure only contains the main significant interactions, those in the range [-0.2, 0.2] are not included.

3.2 Search of Candidate Locations Using a Simulated Annealing Algorithm Once business interaction has been quantified by means of the attraction matrix, Jensen (2006) proposes a mathematical index to measure the fitness of a candidate place for a new store of a given type of business. This index is based on the assumption that current store localizations correctly capture positive and negative interaction externalities through the empirically estimated matrix. Jensen defines the index as follows: Let be x, y the coordinates of a geographic point candidate to hold a type of activity A, then the quality of this point is given by: Q 𝐴 (x, y) = ∑𝐵 ∝AB (𝑛𝑒𝐴𝐴𝐵 (𝑥, 𝑦) − ̅̅̅̅̅̅̅̅ 𝑛𝑒𝐴𝐴𝐵 )

(1.4)

Where 𝑛𝑒𝐴𝐴𝐵 (𝑥, 𝑦) represents the number of stores in the neighbourhood of ̅̅̅̅̅̅̅̅ (x,y), and 𝑛𝑒𝐴 𝐴𝐵 represents the average number of B stores around an A store (again given a neighbourhood defined by a radius). 311


We modify this Q index proposing a fitness function to locate an A store F𝐴 (x, y). This function is minimum in those locations in which the new place interacts with a neighbourhood in the same empirical average relation found in the city, and it increases if the relation is different. While Q index optimizes considering that if an interaction between two businesses is positive, the more in the neighbourhood the better, F implicitly assumes that average empirical relation is an optimum, so it penalizes any type of deviations. Jensen reports correlation between Q and the success of retail stores in the case study of Lyon (Jensen, 2006), but as far as we know there is not any study that compares correlation indexes of Q versus F. F𝐴 (x, y) = ∑𝐵 (𝑛𝑒𝐴𝐴𝐵 (𝑥, 𝑦) − ̅̅̅̅̅̅̅̅ 𝑛𝑒𝐴𝐴𝐵 )2

(1.5)

In order to find good candidates according to F index we use a simulated annealing algorithm (Cerný, 1985;Kirkpatrick et al., 1983), a probabilistic metaheuristic for global optimization, considering F as fitness function. The method is based on searching in the neighbourhood of a previous solution considering an adaptive criterion to accept a new solution. Acceptance mechanism is controlled by the temperature variable which determines the probability of acceptance of a solution that is worse than the previous one. Temperature is initialized in high value, T0, and is being decreased according to an specified cooling schedule α(.) until a final temperature Tf is reached. The algorithm always accepts as new solution a better solution, but it is also possible to accept a worse solution depending on the following equation: 𝛿

𝑃acceptance = 𝑒 (−𝑇)

(1.6)

Where δ is the difference between the F index of the new and old solutions, and T is the current value of the temperature. This strategy initially allows escaping from local optima when temperature is high, and converging through an optimum in the final iterations. A neighbour solution is generated selecting randomly a new point (x’,y’) inside the radius r of the current solution (x,y) (see Fig 3).

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Fig. 3 Panel a) sketches the mechanism to create a neighbour solution. Panel b) represents solutions visited searching for a new bank location and considering F fitness function. Parameters used are T0=200, Tf=0.2 following a Cauchy cooling schedule (Dave and Dave, 2008) and 10 solutions for each temperature. Panel c) shows the best solutions found

4 References Cerný V (1985). Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. Journal of Optimization Theory and Applications, 45: 41-51, doi: 10.1007/BF00940812. Dave PH, Dave HB (2008) Design and analysis of algorithms. Delhi, India, Pearson Education/Dorling Kindersley (India). Duranton G, Overman HG (2005). Testing for localization using micro-geographic data. Review of Economic Studies, 72(4): 1077-1106, doi: 10.1111/0034-6527.00362. Gómez S, Jensen P, Arenas A (2009). Analysis of community structure in networks of correlated data. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 80(1), doi: 10.1103/PhysRevE.80.016114. Hoover EM, Giarratani F (1984) An Introduction to regional economics. McGraw-Hill. Hotelling H (1929). Stability in competition. Economic Journal, 39(153): 41-57

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Jensen P (2006). Network-based predictions of retail store commercial categories and optimal locations. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 74(3), doi: 10.1103/PhysRevE.74.035101. Jensen P (2009). Analyzing the Localization of Retail Stores with Complex Systems Tools. Lecture Notes in Computer Science, 5772: 10-20, doi: 10.1007/978-3-642-03915-7_2. Kirkpatrick S, Gelatt CD, Vecchi MP (1983). Optimization by Simulated Annealing. Science, 220(4598): 671-680, doi: 10.1126/science.220.4598.671. Newman MEJ (2003). The structure and function of complex networks. SIAM Review, 45(2): 167-256, doi: 10.1234/12345678.

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Applications of the Lagrangian Relaxation Method to Operations Scheduling Laviós-Villahoz J.J 1,Arauzo J.A2, del-Olmo-Mártinez R3, Manzanedo-delCampo M.A4, Abstract Lagrangian Relaxation is a combinatorial optimization method, which is mainly used as decomposition method, so a complex problem is divided into smaller and easier problems. Lagrangian Relaxation method has been applied to solve scheduling problem in diverse manufacturing environments like single machine, parallel machine, flow shop, job shop or even in complex real-world environments. We highlight two key issues on the application of the method: the first one is about the method to solve the dual problem and second one is the choice of the constraints to relax. We present the main characteristics of these approaches and survey the existing works in this area.

Keywords: Lagrangian Relaxation, Scheduling, Combinatorial Optimization, Integer Programming

1Juan José Lavios Villahoz ( e-mail: [email protected]) Grupo INSISOC. EPS. Universidad de Burgos. Av. Cantabria s/n, 09006, Burgos 2José

Alberto Arauzo Arauzo ( e-mail: [email protected]) Grupo INSISOC. EII. Universidad de Valladolid. Pso del Cauce 59, 47011 Valladolid. 3Ricardo del Olmo Martínez ( e-mail: [email protected]) Grupo INSISOC. EPS. Universidad de Burgos. C/ Villadiego s/n, 09001, Burgos. 4Miguel

Ángel Manzanedo del Campo ( e-mail: [email protected]) EPS. Universidad de Burgos. C/ Villadiego s/n, 09001, Burgos.

* The authors acknowledge support from the Spanish Ministry of Science and Innovation Project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010) and by the Regional Government of Castile and Leon (Spain) Project VA056A12-2.

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1 Introduction The Lagrangian Relaxation method seeks the solutions of a complex optimization problem from the solutions of an easier problem, which is obtained by relaxing the complex constraints of the original problem. It is mainly used as a decomposition method, where complex problems are divided into smaller and easier problems. It has been applied to solve scheduling problems in diverse manufacturing environments like single machine, parallel machine, flow shop, job shop or even in complex real-world environments. The two key points in Lagrangian Relaxation are to decide which constraints are relaxed and to choose which method should be used to solve the dual problem. These decisions determine the performance of the method. The rest of the paper is organized as follows: in section 2 we introduce the basic idea of Lagrangian Relaxation and discuss two of the main choices in the design of the method, which constraints to relax and which method apply to solve the dual problem; in section 3, we review the main works that apply the Lagrangian Relaxation to the scheduling problem in a manufacturing environment; in section 4, the conclusions are presented.

2 Implementation of the Lagrangian Relaxation in a Manufacturing Scheduling Problem The basic idea of Lagrangian Relaxation is to remove some of the constraints and add them to the objective function. Each of the relaxed constraints is added to the objective function multiplied by a variable (Lagrange multiplier) that penalize the violation of the constraints. The key is to relax the constraints such that the relaxed problem is easier than the original problem. The Lagrangian Relaxation method has been applied to different scheduling environments like single machine, parallel machine, flow shop, job shop, realworld environments, projects and supply chain. Integer formulation can be used to formulate these problems. Total weighted tardiness or total weighted earliness and tardiness is used as objective function. As additive functions, they can be easily decomposed into job dependent subfunctions. In a manufacturing environment machine capacity constraints and task precedence constraints are the main candidates to be relaxed. The relaxed constraints will determinate the orientation of the problem decomposition. If capacity constraints are relaxed, the problem can be decomposed into job related subproblems, but if precedence constraints are relaxed, the problem can be decomposed into machine related subproblems. Wang et al (1997) and Chen et al (1998) indicates that the relaxation of precedence constraints causes important oscillations in the solution from iteration to iteration and prevent convergence of the algorithm. 316


When the number of machines is large enough the relaxation of the capacity constraints leads to better lower bounds (Baptiste et al 2008). The Lagrangian Relaxation method transforms the solutions of the relaxed problem into feasible solutions of the original problem, trying to obtain nearoptimal solutions. The optimal value of the relaxed problem is a lower bound of the optimal objective of the original problem. The subgradient method iteratively adjusts the Lagrangian multipliers to find the best lower bound of the optimal objective value of the original problem (Fisher 2004). However, the subgradient method requires the optimization of all the subproblems. It has two main drawbacks: first, in some environments it may be difficult to obtain the optimum of the relaxed problem; and second, the optimization of large size problems can be very time consuming. To overcome these difficulties the surrogate subgradient method have been proposed. The main advantage is that the minimization of all the subproblems is not required. In this method only a near optimization is sufficient to converge, so less computational effort is needed (Zhao et al 1997). The main drawback of this method is that the updating direction is worse than in the subgradient method. As is shown in Table 1 most researches relax capacity constraints rather than precedence constraints and the surrogate subgradient method is preferred for complex environments or in large problems. Table 1 Problem environment, dual problem method and type of constraints relaxed subgradient method

surrogate gradient method

Relaxed constraints

Capacity constraints

Precedence constraints

General scheduling problem

Luh and Hoitomt (1993)

Single machine

Sun et al (1999); Jeong and Leon (2005); Tang et al (2007);

Parallel machine

Luh et al (1990); Edis et al (2008); Tang and Zhang (2009)

Flow shop

Nishi et al 2007)

Tang et al (2006)

Job shop

Chen et al (1995, 1998); Wang et al (1997); Dewan and Joshi (2002); Luh and Feng (2003); Liu et al (2004, 2007); Baptiste et al (2008); Jeong and Yim (2009)

Hoitomt et al (1993)


Precedence constraints

Wang et al (1997); Kaskavelis and Caramanis (1998); Zhao et al (1999);

Chen and Luh (2003)

Jiang and Tang (2008)

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) Problem environment, dual problem method and type of constraints relaxed subgradient method Relaxed constraints

Capacity

Complex environment

Masin et al (2007); Arauzo (2007) Arauzo et al (2009)

constraints

surrogate gradient method Precedence constraints


Precedence constraints Zhang et al (2001); Chen et al (2003); Luh et al (2003), Sun et al (2006)

3 Applications of the Lagrangian Relaxation Method to Different Manufacturing Environments. In this section, we review the main works that apply the Lagrangian Relaxation to the scheduling manufacturing problems, they are classified by the type of environment. General scheduling problem Luh and Hoitomt (1993) propose a generic methodology that uses Lagrangian Relaxation to solve a scheduling problem. It is applied to three different scheduling environments: individual operations to be scheduled in identical parallel machines; job orders consisting of multiple operations to be scheduled in identical parallel machines; and tasks related with general precedence constraints which have to be scheduled in different machines. Single machine scheduling problem Sun et al (1999) use Lagrangian Relaxation algorithm to solve the problem of scheduling a single machine with sequence dependent setup time. Sequence dependent setup times are modeled as capacity constraints. Dewan and Joshi (2000) decomposes the problem into a local job problems and the machine problem. The machine fixes the prices of time slots and jobs chose the time slots that optimize their costs. This arises in a dynamic environment where new job orders may enter at any time. Every time a job is entered into the system the prices are recalculated, taking the last prices before the arrival of the new order as initial prices. Jeong and Leon (2005) apply a variation of the dual problem resolution to solve the problem of scheduling a shared resource of three production subsystems without using a central planning system. They search a fully distributed problem. 318


Tang et al (2007) deal with multiple immediate predecessors and successors. A forward and backwards dynamic programming algorithm is developed to solve the relaxed problem. Parallel machines Luh et al (1990) first apply the Lagrangian Relaxation method to schedule jobs on several identical machines. They define an iterative algorithm. The feasible program is obtained from the task sequence extracted from the relaxed problem. Edis et al (2008) add machine eligibility restrictions. In these problems different machines can do the same job with a different performance. They develop a heuristic to build feasible programs from the relaxed problem. Tang and Zhang (2009) apply Lagrangian Relaxation method to rescheduling tasks on a parallel machine in a dynamic environment. Breakdown of machines is considered. The goal is to reschedule tasks with minimal modifications to the original problem, but taking into account the efficiency the obtained schedule. Flow Shop problem Lagrangian Relaxation is applied in Tang et al (2006) to the problem of scheduling a hybrid flow shop system. This system comprises various stages of production, and in each of these stages there are a number of machines working in parallel. In Nishi et al (2007) the Lagrangian Relaxation algorithm is iteratively applied while new restrictions are progressively added. They make new proposals for improving the dynamic programming step. Job shop problem Hoitomt et al (1993) relax the precedence and the capacity constraints. A listscheduling algorithm is developed to generate a feasible schedule. The main contribution of Chen et al (1995) is the use of dynamic programming techniques to solve the relaxed job shop problem at the job order level. This avoids additional relaxation of the precedence constraints. Wang et al (1997) minimize earliness and tardiness of job orders. They compare several methods for solving the dual problem. Chen et al (1998) propose to relax only the capacity constraints to decompose the problem into several subproblems associated to job orders. These problems are solved using dynamic programming technique. They apply it to real factory data. Kaskavelis and Caramanis (1998) and Zhao et al (1999) apply the surrogate dual method to a separable problem (interleaved subgradient method). The main contribution of Dewan and Joshi (2002) is the study of the relationship between the theory of auctions and Lagrangian Relaxation. The concept of 319


multi-agent systems is used as a basis for the implementation of distributed systems in planning and production control. They define the problem as combinatorial auctions where the items sold are the time slot in which the planning horizon is divided. Liu et al (2004, 2007) also define a reactive scheduling system where auctions are held in a machine whenever a time slot is free. Chen and Luh (2003) solve the job shop problem using the Lagrangian Relaxation method and relaxing the precedence constraints, rather than capacity constraints. The resulting subproblems are equivalent to solving a problem of scheduling a single machine or parallel machines. Kutanoglu and Wu (2004) combine the stochastic analysis with the dynamic adaptation of the system to improve the robustness of Lagrangian Relaxation method. Baptiste et al.(2008) compare precedence constraints and capacity constraints. They improve the solutions by local search. Jeong and Yim (2009) apply Lagrangian Relaxation to solve the job shop problem extended to the case of virtual enterprise with agents controlling one or more job orders and machines. Each subsystem calculates its own schedule. They use the protocol CICA, developed in Jeong and Leon (2002), as a framework to solve the scheduling problem in a distributed manner using an agent-based environment Scheduling in complex environments Gou et al (1998) implement the problem of production scheduling in a real production plant using a multi-agent system. They organize the system as a hierarchy following a quasi-distributed holonic structure based on relaxation of the capacity constraints and precedence of the job shop problem. Zhang et al (2001) develop a macro-level scheduling method based on Lagrangian Relaxation method. Large problems are studied and assemblies and disassemblies are allowed. This makes the structure of the resolution process and the subproblems complex. Surrogate subgradient method is proposed to reduce the computation requirements. Chen et al (2003) study a complex environment with multiple resources, setup times and transfer lots. They use a dynamic programming method for solving the subproblems related to transfer lots easier than in the previous work. Luh et al (2003) apply Lagrangian Relaxation to a problem of supply chain as an extension of a job shop problem. It uses a variation of the Contract Net protocol for communication among agents and the surrogate gradient method to solve the dual problem. Sun et al (2006) study complex process structures with coupling assemblies and disassemblies. They propose to relax only one of the precedence constraints to avoid oscillation problems. They add an auxiliary function penalty to improve its convergence.

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Arauzo (2007) implements an auction mechanism for controlling flexible manufacturing systems. The analogy between auction and Lagrangian Relaxation process is applied in the definition of the auction. This provides a robust mathematical method in the updating prices step. Arauzo et al (2009) propose a multi-agent system for project portfolio management. Projects negotiate the allocation of shared resources by an auction. The analogy between the Lagrangian Relaxation method and auctions is used as a modeling tool. This approach allows managing the company's current projects and provides decision criteria for the acceptance or rejection of new projects.

4 Conclusions We reviewed the studies that have applied the Lagrangian Relaxation method to the resolution of scheduling operations in recent years. The scope has been diverse and covers most types of problems. The application of the method has been performed with two types of relaxation of constraints: capacity or precedence constraints. The choice of one or another implies respectively an approach towards a job decomposition or a machine decomposition of the problem. The dual problem has also been solved with two different methods: the subgradient method, the surrogate gradient method. The objectives of these studies aim to improve the speed of resolution, the stability of the method, and the ease of solving problems.

5 References Arauzo JA (2007) Control distribuido de sistemas de fabricación flexibles: un enfoque basado en agentes. Thesis. University of Valladolid. Araúzo JA, Pajares J, Lopez-Paredes A, Pavón J (2009) Agent-based modeling and simulation of multi-project scheduling. Multi-Agent Logics, Languages, and Organizations Federated Workshops. Baptiste P, Flamini M, Sourd F (2008) Lagrangian bounds for just-in-time job-shop scheduling. Computers and Operations Research 35(3):906-915. Chen H, Chu C, Proth J-M (1998) An improvement of the Lagrangean relaxation approach for job shop scheduling: a dynamic programming method. IEEE Transactions on Robotics and Automation 14(5):786-795. Chen H, Chu C, Proth J-M (1995) More efficient Lagrangian relaxation approach to job-shop scheduling problems. In Proceedings of the IEEE International Conference on Robotics and Automation 496-501. Chen H, Luh PB (2003) An alternative framework to Lagrangian relaxation approach for job shop scheduling. European Journal of Operational Research 149(3):499-512. Chen D, Lut PB, Thakur LS, Moreno Jr, J (2003) Optimization-based manufacturing scheduling with multiple resources, setup requirements, and transfer lots. IIE Transactions 35(10):973985.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Dewan P, Joshi S (2002) Auction-based distributed scheduling in a dynamic job shop environment. International Journal of Production Research 40(5):1173-1191. Dewan P, Joshi S (2000) Dynamic single-machine scheduling under distributed decision-making. International Journal of Production Research 38(16):3759-3777. Edis EB, Araz C, Ozkarahan I (2008) Lagrangian-based solution approaches for a resourceconstrained parallel machine scheduling problem with machine eligibility restrictions. In Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence. 337346. Springer, Wrocław. Fisher ML (2004) The Lagrangian relaxation method for solving integer programming problems. Management Science 50(12_supplement):1861-1871. Gou L, Luh PB, Kyoya Y (1998) Holonic manufacturing scheduling: architecture, cooperation mechanism, and implementation. Computers in Industry 37:213-231. Hoitomt DJ, Luh PB, Pattipati KR (1993) A practical approach to job-shop scheduling problems. IEEE Transactions on Robotics and Automation 9(1):1-13. Jeong I-J, Leon VJ (2005) A single-machine distributed scheduling methodology using cooperative interaction via coupling agents. IIE Transactions 37(2):137-152. Jeong I-J, Leon VJ (2002) Decision-making and cooperative interaction via coupling agents in organizationally distributed systems. IIE Transactions 34(9):789-802. Jeong I-J, Yim S-B (2009) A job shop distributed scheduling based on Lagrangian relaxation to minimise total completion time. International Journal of Production Research 47(24):6783. Jiang S, Tang L (2008) Lagrangian relaxation algorithm for a single machine scheduling with release dates. In Second International Symposium on Intelligent Information Technology Application 811-815. Kaskavelis CA, Caramanis MC (1998) Efficient Lagrangian relaxation algorithms for industry size job-shop scheduling problems. IIE Transactions 30(11):1085-1097. Kutanoglu E, Wu SD (2004) Improving scheduling robustness via preprocessing and dynamic adaptation. IIE Transactions 36(11):1107. Liu N, Abdelrahman MA, Ramaswamy S (2007) A complete multiagent framework for robust and adaptable dynamic job shop scheduling. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 37(5):904-916. Liu N, Abdelrahman MA, Ramaswamy S (2004) A multi-agent model for reactive job shop scheduling. In Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory 241-245. Luh PB, Feng W (2003) From manufacturing scheduling to supply chain coordination: The control of complexity and uncertainty. Journal of Systems Science and Systems Engineering 12(3):279-297. Luh PB, Hoitomt DJ (1993) Scheduling of manufacturing systems using the Lagrangian relaxation technique. IEEE Transactions on Automatic Control 38(7):1066-1079. Luh PB, Ni M, Chen, H, Thakur LS (2003) Price-based approach for activity coordination in a supply network. IEEE Transactions on Robotics and Automation 19(2):335-346. Luh PB, Omt D, Max E, Pattipati KR (1990) Schedule generation and reconfiguration for parallel machines. IEEE Transactions on Robotics and Automation 6(6):687-696. Masi M, Pasaogullari MO, Joshi S (2007) Dynamic scheduling of production-assembly networks in a distributed environment. IIE Transactions 39(4):395-409. Nishi T, Hiranaka Y, Inuiguchi M (2007) A successive Lagrangian relaxation method for solving flow shop scheduling problems with total weighted tardiness. In IEEE International Conference on Automation Science and Engineering 875-880. Sun T, Luh PB, Min L (2006) Lagrangian relaxation for complex job shop scheduling. In Proceedings of the IEEE International Conference on Robotics and Automation 1432-1437. Sun X, Noble JS, Klein CM (1999) Single-machine scheduling with sequence dependent setup to minimize total weighted squared tardiness. IIE Transactions 31(2):113-124.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tang L, Zhang Y (2009) Parallel machine scheduling under the disruption of machine breakdown. Industrial and Engineering Chemistry Research 48(14):6660-6667. Tang L, Xuan H, Liu J (2007) Hybrid backward and forward dynamic programming based Lagrangian relaxation for single machine scheduling. Computers and Operations Research 34(9):2625-2636. Tang L, Xuan H, Liu J (2006) A new Lagrangian relaxation algorithm for hybrid flowshop scheduling to minimize total weighted completion time. Computers and Operations Research 33(11):3344-3359. Wang J, Luh PB, Zhao X, Wang J (1997) An optimization-based algorithm for job shop scheduling. Sädhana 22(part 2):241-256. Zhang Y, Lut PB, Narimatsu K et al (2001) A macro-level scheduling method using Lagrangian relaxation. IEEE Transactions on Robotics and Automation 17(1):70-79. Zhao X. Luh PB, Wang J (1999) Surrogate gradient algorithm for Lagrangian relaxation. Journal of Optimization Theory and Applications 100(3):699-712. Zhao X, Luh P, Wang J (1997) The surrogate gradient algorithm for Lagrangian relaxation method. Proceedings of the 36th IEEE Conference on Decision and Control 1:310, 305.

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Methodology for the Strategic Capacity Planning in Universities de la Torre R1, Lusa A2, Mateo M3 Abstract This paper introduces the Strategic Capacity Planning problem in universities and proposes a methodology for solving the problem. The methodology includes the characterization of the problem, the design of a mathematical model, the data collection and pre-analysis, the model solving and the introduction of uncertainties. Besides the use for staff capacity planning, the methodology can be used to assess the impact that different strategies may have on the personnel costs and structure.

Keywords: Strategic Capacity Planning, Quantitative Methods, Staff Planning, KIO/KIF, KIBS.

1 Introduction The number of Spanish universities has increased considerably in the last decades (Corominas and Sacristán, 2010; Llinàs-Audet et al., 2010). This growth has been accompanied by changes in the European higher education (European Credit Transfer and Accumulation System - ECTS), an increasing concern about the quality of university tasks (teaching, research, technology knowledge transfer, etc.), and financial problems in public universities. Moreover, the latter has been 1

Rocío de la Torre (e-mail: [email protected]) Department of Management / ETSEIB. Universitat Politècnica de Catalunya. Universitat Politècnica de Catalunya. Av. Diagonal 647, planta 7, 08028 Barcelona, Spain 2

Amaia Lusa (e-mail: [email protected]) Department of Management / IOC / ETSEIB. Universitat Politècnica de Catalunya. 3 Manel Mateo (e-mail: [email protected]) Department of Management / ETSEIB. Universitat Politècnica de Catalunya. Universitat Politècnica de Catalunya. Av. Diagonal 647, planta 7, 08028 Barcelona, Spain

* Supported by the Spanish Ministry of Economy and Competitivity (project DPI2010-15614).

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accentuated by the global economic crisis, and particularly, by the Spanish economic crisis. Apart from the external changes, there have been several substantial changes in the structure of the university during the last years. Also, the academic staff has been notably modified (Corominas and Sacristán, 2010). One of the most relevant changes has been the importance given to the research and the knowledge and technology transfer (KTT) tasks, apart from the teaching tasks. This, obviously, has a great influence on the definition of the ideal structure of the university (composition of the workforce and, in particular, of the academic staff). The strategic management was first developed in universities as a result from the experience gained in companies. According to Llinàs-Audet et al. (2010), while the strategic management was adopted by some European universities during the eighties of the last century, it was not introduced in Spanish universities until the nineties. Several studies show that the number of strategic practices in universities is increasing (Clark, 1998, 2003, Lounsbury, 2001; Jarzabkowski, 2003; Shattock, 2003; Agasisti et al., 2008); these, of course, are highly influenced and constrained by the legal and academic regulations of each university. Llinàs-Audet et al. (2010) present an analysis about the current state of strategic planning in the Spanish universities. Moreover, the authors discuss on the effectiveness of the management tools implemented to date. They state that “there are not definitive standard formalized procedures to guide higher education institutions in this process”. In line, Corominas and Sacristán (2010) note that “in the literature predominates outline and repeated proposals that frequently are not a result of a rigorous analysis of reality or are unreasoned”. Rowley et al. (1997) affirm that often strategic planning in universities is rather short term, or alternatively, a schedule for the resolution of specific problems. Thus, strategic capacity planning in Spanish universities is a hot topic and very timely, as it will require changes in current funding policies, human resources policies (Santiago et al., 2009) and academic policies. Some authors, such as Hunt et al. (1997), argue that the use of strategic planning allows universities a better use of their resources, and therefore they achieve greater institutional success (most internationally, creating a better and innovative academic environment, etc.). Surprisingly, to the best of our knowledge, a formalized procedure for the strategic capacity planning in universities has not been previously proposed. This paper presents a procedure for solving the strategic capacity planning problem in universities, and a mathematical model (which is part of the procedure) for one of the variants of the problem. The organization of the rest of the paper is as follows: Section 2 contains a brief description of a variant of the problem. Section 3 presents a methodology for strategic capacity planning in universities. Section 4 includes a mathematical program for the problem described in Section 2. Finally, conclusions and references are detailed in Sections 5 and 6 respectively. 325


2 Strategic Capacity Planning in a University The problem consists in determining the capacity (i.e., staff, both in quantity and type) for a long time horizon. The required capacity (or a probabilistic distribution of it) is assumed to be known and it refers only to the teaching capacity. Of course, the cheapest way to cover the required capacity would be with part time staff (they work in another company or organization and do some lectures at the university, at a quite low cost). However, even if this was legal, it would be detrimental to the quality (teaching is not their main job) and to the overall activity of the university (including, of course, research and KTT tasks). To avoid this, an ideal academic staff structure should be defined. The specific characteristics of the problem are detailed below:  The system should have a certain excess of capacity.  The problem is considered to be dynamic, i.e. the capacity can vary along the horizon.  The resources in strategic capacity planning are human resources and, in this case, only academic staff (and not administration staff) is considered.  Each worker belongs to a unit (e.g., department) and to a category. The capacity and the types of task that he/she is able to do may depend on the category.  There are two types of categories: temporary and permanent categories.  Regarding temporary categories, it is mandatory for a member of the staff to progress to a top category once a certain period of time is completed.  Regarding permanent categories, it is considered that a member of the staff is able to progress to another category once the merits required in the top category are reached. A person can access to a category from a lower one or from outside the organization.  The considered decisions that influence the variation of the capacity include the creation of posts (in certain categories and units) and the non-renewal of contracts.  There is a maximum budget for personnel costs.  The evaluation criteria of the solution include the personnel cost and the composition of the academic staff (according to a preferable structure).  Some data can be uncertain.

3 Methodology of Strategic Capacity Planning in Universities The proposed methodology is developed to help the organization to:  Define the long-term workforce planning, considering uncertainties.

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 Evaluate the impact of strategic decisions taken prior to the capacity planning decisions, as for example the implementation of specific personnel policies (e.g., stabilization or promotion plans, collective dismissal, etc.), the creation or elimination of degrees, changes in the units (e.g., departments) configuration, among others. The phases that make up the methodology are represented in Figure 1 and briefly described after the figure.

Fig. 1 A methodology scheme for the strategic capacity planning problem in universities. Source: authors.

Phase I: Problem’s characterization A scheme of the most relevant characteristics of the strategic capacity planning in Knowledge Intensive Organizations (KIOs) was presented in Martinez et al. (2012). According to the different characteristics (organizational structure, workforce, capacity decisions, demand, service level, costs associated to the capacity decisions, financing, uncertainty, planning horizon, and evaluation criteria), the problem gives rise to different variants. The first step is to identify the variant, describing the specific characteristics of the problem. Phase II: Model’s formulation Once the problem has been characterized, next phase consists in designing a mathematical optimization model. Each characteristic of the problem carries an associated set of variables and constraints. To illustrate this phase, Section 4 provides the model formulation for the particular case of the university described in Section 2. 327


Phase III: Data collection and pre-analysis The objective of this phase is to define the sources of information for each type of data, and process the information as required by the model. Phase IV: Model solving In this phase the aim is to solve the mathematical model. The implementation and test of the model are included in the phase. Phase V: Add uncertainty and refine results. This phase is applied if uncertainty is considered to be relevant (for example, in the required capacity, which may have different scenarios; in the probability that a member of the academic staff is able to progress to another category; or in the available budget). Stochastic models and simulation may be used (or combined) depending on the case.

4 Model’s formulation The mathematical model for the problem described in Section 2 is presented. Table 1 Data base description Parameter

Description

𝐾

Set of categories.

𝐾′

Subset of temporary categories (∀kϵK|k ⊆ ([1, 𝑘1 ]⋃[𝑘1 + 1, 𝑘2 ])).

𝐾′′

Subset of permanent categories (∀kϵK|k > 𝑘2 + 1).

𝑐𝑘𝑡

Cost in [mu/worker] associated to the category k in period t. [∀t; ∀kϵK]

𝑣𝑡

Cost in [mu/hour] associated to part time lecturers in period t. [∀t]

𝐶𝑢𝑡

Required capacity for the unit u, in period t. [∀t; ∀u]

ℎ𝑘𝑡

Capacity associated to each worker in the category k in period t. [∀t; ∀kϵK].

𝐿𝑢𝑘𝑡

Expected personnel cuts (for instance, due to retirement) in the unit u, category k, in period t. [∀t; ∀u; ∀kϵK]

𝛤𝑘+

Set of categories to which it is possible to access from the category k. [∀kϵK]

𝛤𝑘−

Set of categories from which it is possible to access to the category k. [∀kϵK]

𝑟𝑢𝑠𝑘𝑡

Proportion of workers in unit u, that can promote, as maximum, from the category s to the category k, in period t. [∀t]

𝑈𝑃𝑘𝑡 , 𝐿𝑃𝑘𝑡

Preferable bounds for the proportion of academic staff that belongs to the category k in the period t. This condition is not rigid, but non-compliance is penalized.

328

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) Data base description Parameter

Description

𝛼𝑢𝑡

Excess of capacity that should have, at least, the unit u in the period t [∀t]. Note that, even if it is not usual, this parameter could be negative (if a shortage in the capacity is allowed, this would mean a worsening in the service level).

𝜆𝑘𝑡

Penalty associated to the discrepancy between the preferable and the actual composition of academic staff of the category k, in the period t. [∀t]

𝜇𝑡

Penalty associated to the maximum discrepancy between the preferable and the actual composition of the academic staff, in the period t. [∀t]

𝜔

Penalty associated to the maximum discrepancy between the preferable and the actual workforce.

𝐵𝑡

Planned budged of the salaries of the academic staff for the period t. [∀t]

Table 2 Variables of the model Variable

Description

wukt

Integer variable that indicates the number of workers of the unit u, category k and period t. [∀t; ∀u; ∀kϵK]

Aut

Integer variable that indicates the number of hours given by part time workers in the unit u in period t. [∀t; ∀u]

Quklt

Integer variable that indicates the number of workers who access to the category l from the category k, in the unit u, in the period t. [∀t; ∀u; ∀kϵK]

+ wukt

Integer variable that indicates the number of new workers in the unit u and category k, in the period t from the labor market. [∀t; ∀u; ∀kϵK]

− wukt

Integer variable that indicates the number of off workers (excluding the previously forecasted) in the unit u and the category k, in the period t. [∀t; ∀u; ∀kϵK]

− δ+ kt , δkt

Positive and the negative discrepancy, respectively, between the preferable and the actual composition of the academic staff in the category k in the period t. [∀t; ∀kϵK]

δt

Maximum discrepancy (positive or negative), between the preferable and the actual composition of the academic staff in all categories in period t (i.e. δt = − 𝑚𝑎𝑥𝑘 (δ+ kt , δkt )). [∀t]

∆

Maximum discrepancy between the preferable and the real composition of the academic staff (i.e. ∆= 𝑚𝑎𝑥𝑡 (δt )).

Model + − )] [𝑀𝐼𝑁]𝑧 = ∑∀𝑢,𝑡[𝐴𝑢𝑡 · 𝑣𝑡 + ∑∀𝑘(𝑤𝑢𝑘𝑡 · 𝑐𝑘𝑡 )] + ∑∀𝑘,𝑡[𝜆𝑘𝑡 · (𝛿𝑘𝑡 + 𝛿𝑘𝑡 + ∑∀𝑡 𝜇𝑡 · 𝛿𝑡 + 𝜔 · Δ

(1)

∑∀𝑘 𝑤𝑢𝑘𝑡 · ℎ𝑘𝑡 + 𝐴𝑢𝑡 ≥ (1 + 𝛼𝑢𝑡 ) · 𝐶𝑢𝑡

(2)

∀𝑢, 𝑡 −

′

𝑤𝑢𝑘𝑡 ≤ 𝑟𝑢𝑠𝑘𝑡 · 𝑤𝑢𝑠𝑡 − 𝐿𝑢𝑘𝑡

∀𝑢, 𝑡; 𝑠𝜖Γ , 𝑘𝜖𝐾 ∖ 𝑘 = {1, 𝑘1 }

(3)

+ 𝑤𝑢𝑘𝑡 ≤ 𝑟𝑢𝑠𝑘𝑡 · 𝑤𝑢𝑠𝑡 − 𝐿𝑢𝑘𝑡 + 𝑤𝑢𝑘𝑡

∀𝑢, 𝑡; 𝑠𝜖Γ− , 𝑘𝜖𝐾 ′ ; 𝑘 = {1, 𝑘1 }

(4)

329

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. + − 𝑤𝑢𝑘𝑡 = 𝑤𝑢𝑘𝑡−1 − 𝐿𝑢𝑘𝑡 + ∑𝑠𝜖Γ−𝑘 𝑄𝑢𝑠𝑘𝑡 − ∑𝑙𝜖Γ𝑘+ 𝑄𝑢𝑘𝑙𝑡 + 𝑤𝑢𝑘𝑡 − 𝑤𝑢𝑘𝑡

∀𝑢, 𝑡; ∀𝑘𝜖𝐾′′

(5)

𝑄𝑢𝑠𝑘𝑡 ≤ 𝑟𝑢𝑠𝑘𝑡 · 𝑤𝑢𝑠𝑘𝑡

+ ∀𝑢, 𝑡; ∀𝑠𝜖𝐾′′|Γ+ 𝑠 ≠ {∅}; ∀𝑘𝜖Γ𝑠

(6)

− ∑∀𝑢 𝑤𝑢𝑘𝑡 ≥ (𝐿𝑃𝑘𝑡 · ∑∀𝑢,𝑘 𝑤𝑢𝑘𝑡 ) − 𝛿𝑘𝑡

∀𝑡; ∀𝑘𝜖𝐾

(7)

∑∀𝑢 𝑤𝑢𝑘𝑡 ≤ +

+ 𝛿𝑘𝑡


(8)

+ 𝛿𝑡 ≥ 𝛿𝑘𝑡


(9)

− 𝛿𝑘𝑡


(10)

Δ ≥ δt

∀𝑡

(11)

∑∀𝑢[𝐴𝑢𝑡 · 𝑣𝑡 + ∑∀𝑘(𝑤𝑢𝑘𝑡 · 𝑐𝑘𝑡 )] ≤ 𝐵𝑡

∀𝑡

(12)

𝛿𝑡 ≥

+ − 𝑤𝑢𝑘𝑡 , 𝐴𝑢𝑡 , 𝑄𝑢𝑘𝑙𝑡 , 𝑤𝑢𝑘𝑡 , 𝑤𝑢𝑘𝑡 ≥0

(13)

− 𝛿𝑘𝑡

(14)

,

+ 𝛿𝑘𝑡

, 𝛿𝑡 , Δ ≥ 0

Equation (1) presents the objective function. The aim is to minimize the costs associated to the salaries as well as the discrepancies between the ideal and the actual composition of the academic staff. Equation (2) limits the minimum available capacity; (3) and (4) balances the number of temporary staff members of each unit, category and time of the university; the permanent staff members of each unit, category and time of the university are balanced in (5); (6) imposes an upper bound to the number of workers to be promoted. Constraints regarding the ideal composition of the academic staff are included in equations (7) and (8). Constraints (9) to (11) correspond to the maximum discrepancies between all categories and periods, to avoid, insofar as possible, that the discrepancy be concentrated in few categories or periods (assuming that it is preferable a regular distribution of the discrepancy). Constraint (12) limits the personnel costs per period. Finally, (13) and (14) impose that variables are non-negative.

5 Conclusions This paper presents a methodology to deal with the problem of the Strategic Capacity Planning in universities and illustrate one the steps by presenting a mixed integer lineal programming model for a variant of the problem. The methodology can be used not only for planning capacity, but also for assessing the impact of different university strategies (personnel policies, studies offered by the university, etc.). This can be done by changing some parameters of the model. For instance, in case of assessing the impact of personnel policies, it is necessary to modify the proportion of workers that can promote (𝑟𝑢𝑠𝑘𝑡 ), the preferable bounds for the composition staff (𝑈𝑃𝑘𝑡 , 𝐿𝑃𝑘𝑡), and the planned budget of the salaries (𝐵𝑡 ).

330


6 References Agasisti, T, Arnaboldi, M, Azzone, G (2008). Strategic management accounting in universities: the Italian experience. Higher Education, 55(1):1-15. Clark, BR (1998). Creating Entrepreneurial Universities: Organizational Pathways of Transformation. Oxford: IAU Press by Pergamon. Clark, BR (2003). Sustaining Change in Universities: Continuities in Case Studies and Concepts. Tertiary Education and Management, 9:99-116. Corominas A, Sacristán V (2010). The strategic crossroads of Spanish public university. Revista de Educación, 355:57-81. Hunt, CM, Oosting, KW, Stevens, R, Loudon, D, Migliore, RH (1997). Strategic Planning for Private Higher Education. Binghamton, NY: Haworth. Jarzabkowski, P (2003). Strategic Practices: An Activity Theory Perspective on Continuity and Change. Journal of Management Studies, 40:1. Llinàs-Audet X, Girotto M, Solé F (2010). University strategic management and the efficacy of the managerial tools: the case of the Spanish universities. Revista de Educación, 355:33-54. Lounsbury, M (2001). Institutional sources of practice variation: Staffing College and university recycling programs. Administrative Science Quarterly, 46(1):29-56. Martinez, M, Lusa, A, Mas, M, De La Torre, M, Mateo, M (2012). Strategic Capacity Planning in KIOs: A Classification Scheme. In 6th International Conference on Industrial Engineering and Industrial Management, Vigo, Spain. Rowley, D, Lujan, H, Dolence, M (1997). Strategic Change in Colleges and Universities: Planning to Survive and Prosper. San Francisco: Jossey-Bass. Santiago, P, Brunner, JJ, Haug, G, Malo, S, Pietrogiacomo, P (2009). OECD Reviews of Tertiary Education: Spain. Paris: OECD. Shattock, M (2003). Managing successful universities. London, UK: Society for Research in Higher Education & Open University Press.

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A MILP Event Based Formulation for a Realworld Multimode RCSP with Generalized Temporal Constraints Borreguero T1, García A2, Ortega M 3 Abstract Scheduling is becoming much more important in every industry. However, the standard RCSP usually does not cover all the characteristics of real world problems. In this work, we present an Event Based MILP formulation for a Multimode Resource Constraint Problem of direct application for some industries, as aeronautical assembly lines. Taking as a starting point of the last MILP formulations for standard RCSP, our contribution is to provide a formulation which covers the multimode case and more general temporal constraints than the ones usually referred to in the literature.

Keywords: Scheduling, Multimode, Event Based Formulation, Temporal Constraints, MILP.

1 Introduction Over the last years, the continuous changes on every industry have forced enterprises to explore new manufacturing methods in order to comply with the OTOQOC paradigm (On time, On Quality, On Cost). Production systems based on the Toyota Production System have spread worldwide as a means of reducing 1Tamara Borreguero Sanchidrián ( [email protected]) Grupo IOL. Dpto. Ingeniería de Organización, Administración de Empresas y Estadística -. ETSII. UPM Madrid 2

Álvaro García Sánchez ( [email protected]) Grupo IOL. Dpto. Ingeniería de Organización, Administración de Empresas y Estadística -. ETSII. UPM Madrid.

3

Miguel Ortega Mier ([email protected]) Grupo IOL. Dpto. Ingeniería de Organización, Administración de Empresas y Estadística -. ETSII. UPM Madrid.

332


waste and optimizing manufacturing processes. The aeronautical industry, since the 1990’s has been including the lean techniques into its production systems. In terms of Boeing, in a Lean production system the right resources and the right tools must be applied to achieve three key Lean principles: Takt Paced Production, One Piece Flow and Pull Production (Gastelum, 2002). Scheduling and line balancing have therefore become two main enablers for lean implementation. Aeronautical Final Assembly Lines consist on different platforms or stations. Each platform has a fixed team of workers with different skills. The line balancing enables the distribution of the work tasks among the different platforms. Afterwards, the work tasks from each platform must be scheduled in order to complete them within the required Takt Time using the minimum number of operators. We will refer to the scheduling of the tasks as the Aeronautical Platform Scheduling Problem. This detailed scheduling has the structure of a Resource Constrained Scheduling Problem (RCSP), which was defined by Brucker (Brucker, 1999) as the allocation of scarce resources to dependent activities over time. It is a NP Hard optimization problem and is actually one of the most intractable classical problems in practice. For both its industrial relevance and its challenging difficulty, solving the RCPSP has become a flourishing research theme. (Artigues, 2010). There have been a wide range of studies on both heuristic and metaheuristic methods for solving the RCSP, as well as different MILP models. Recently, Koné (Koné et al, 2011) proposed the use of Event Based Formulations for the RCSP. He provided a benchmark of different models (including MILP and an heuristic) and concluded that event based formulations outperformed the previous MILP models and performed even better than the heuristic for some instances. However, Koné’s Event Based Formulations deals with the standard RCSP, which includes some assumptions that are too restrictive for many practical applications (Hartmann, 2010). Therefore, it is of great interest to improve this kind of formulations so that they can be used on industrial applications. On this work, we have developed a new Event Based Formulation that covers the characteristics of an aeronautical Assembly Platform scheduling problem. Actually, its main contribution is the allowance of multiple modes per task as well as the use of more general temporal constraints. Furthermore, the alternative objective approach, focused on minimizing the cost is more suitable for nowadays industries where the total Lead Time is usually fixed by the client Takt Time. Section 2 provides the general classification of the Aeronautical Platform Scheduling problem. Section 3 gives an overview of existing exact formulations for the RCSP. In section 4 we propose the event based multimode formulation with additional temporal constraints. Section 5 contains the results and conclusions of tests performed on several instances and Section 6 some conclusions and future research directions.

333


2 The Aeronautical Platform Scheduling Problem The RCSP is a combinatorial optimization problem, defined by a 6-tuple (V, p,E,R,B,b), where V is a set of activities, p a vector of processing times per activity, E the set of temporal constraints, R the set of resources, B the resource capacity vector and b the demand matrix (resource consumption per activity) (Koné, 2009). The objective is to identify a feasible schedule, which assigns a start /completion time (Sj / C j) to each activity as well as a resource allocation, taking into account the temporal constraints and minimizing the total project lead time. Until 1999, there was not a common notation for RCSP. Brucker (Brucker1999) proposed a notation based on the extension of the α| β|γ generalized scheme for the machine scheduling literature. In this notation, α refers to the resource environment, β to the activity characteristics and γ to the objective function. According to this notation, the Aeronautical Platform Scheduling is classified as MPSm, σ, r | temp | ∑ 𝑐𝑘 max 𝑟𝑘 (𝑆, 𝑡):  α = MPSm, σ, r. This stands for a multimode resource constraint project where each activity can be processed in several alternative modes and exists a set of renewable resources available for each time period during the project execution: m being the resources, σ the units of each resource available and r the maximum number of units of the resources demanded by an activity. For our particular problem, the activities are the work tasks assigned to each platform. The renewable resources are the number of operators (each of them belonging to a particular skill) and the space on the working areas, as platforms are divided into smaller areas where a limited number of operators can work simultaneously. As well as this, each mode for an activity defines a combination of operator skills, number of operators and durations. All the operators assigned to an activity must be from the same skill and the range of possible numbers of allocated operators per tasks is independent of the chosen skill.  β = temp. Among the temporal constrains, there are precedence constraints (task w’ can not start until task w has been completed), non-parallel constraints (tasks w and w’ cannot be in progress at the same time, but there is no precedence relation between them), and maximal time lags between tasks (task w’ must start within a maximal time after w has been completed).The maximal time lag, if it exists, will be zero for all the pairs of activities. All the temporal constraints are independent from the mode in which a task is executed.  γ=∑ 𝑐𝑘 max 𝑟𝑘 (𝑆, 𝑡). The objective function is to minimize the resource investment. The total lead time is fixed by the assembly line Takt Time, as stated on Section 1. Therefore, the objective function is to minimize the labor cost of the assembly. The operators, once assigned to a platform stay working on it for all the Takt Time and thus minimizing the labor cost is equivalent to minimizing the maximum number of operators needed throughout the Takt Time.

334


3 Exact Formulations for the RCSP Most of the research on RCSP has focused on the core single-mode problem with precedence and resource constraints. In this section, we will review MILP formulations for this core problem. They can be divided on three main groups:  Discrete Time Formulations: In them, the time horizon is divided into time slots. The basic discrete time formulation was proposed by Pritsker (Pritsker, 1969). Afterwards, Christofides (Christofides, 1987) proposed the Disaggregated Discrete Time formulation (DDT) that implies a larger number of constraints but, on the other hand, is a tighter formulation and therefore its linear relaxation provides a better LB. The main drawback of discrete time formulations is the increase in the number of variables as the time horizon grows.  Continuous time formulation: In this formulations, the time is represented by continuous variables: Alvarez-Valdés and Tamarit, (Alvarez-Valdés and Tamarit, 1993) studied Forbidden Sets Formulations which involve a high number of constraints that grows exponentially and cannot be used in practice. Flow-Based Continuous time constraints, described by Artigues. (Artigues et al, 2003) provide a poor relaxation, compared to discrete time formulations, although it can be preferable to them for instances involving large time scale.  Event Based Formulations: Event Based Formulations for the RCSP where developed by Koné in 2009 (Koné, 2009), from a model introduced by Zapata. (Zapata , 2008). These formulations define a series of events which correspond to the start or end of the different activities. They are based on the fact that for the RCSP it always exists an optimal semi-active schedule in which the start time of an activity is either 0 or coincides with the completion time of another activity (Sprecher, 1995). Therefore, at most 𝑛 + 1 events have to be considered. They have the advantage of not depending on the time horizon, making them especially relevant for long time projects, as is the case. Among Event Based Formulations, the Start/End Event Based Formulation involves two types of binary variables, 𝑥𝑤𝑒 and 𝑦𝑤𝑒 , that are equal to 1 if task 𝑤 starts (in the case of 𝑥𝑤𝑒 ) or ends (𝑦𝑤𝑒 ) at event 𝑒 and 0 otherwise.

4 Model Formulation The Start/End Event Based Formulation (SEE) has been used as a starting point for an extended formulation that copes with the multimode problem and the additional maximal separating time and non-parallel constraints as explained on Section 2. The resulting formulation uses four sets: O stands for the operator profiles, W for the work Tasks, A for the Working Areas and E for the events. The model parameters are defined in Table 1. 335


Due to the new characteristics of our model, we replace the original SEE variables 𝑥𝑤𝑒 and 𝑦𝑤𝑒 with variables 𝑥𝑤𝑒𝑜𝑛 and 𝑦𝑤𝑒𝑜𝑛 , to be set to 1 if task 𝑤 starts or ends on event 𝑒, using 𝑛 operators of profile 𝑜. As well as this, we define the non∗ negative variables 𝑟𝑜𝑒 to represent the amount of resource 𝑜 needed immediately ∗ after event 𝑒 and non-negative variables 𝑠𝑎𝑒 to represent the number of operators working on area 𝑎 immediately after event 𝑒. A binary variable 𝛼𝑤𝑤′ is defined for tasks with non-parallel constraints (𝑤, 𝑤 ′ ∈ 𝑊 𝑎𝑛𝑑 𝑁𝑂𝑁𝑃𝑤𝑤′ = 1 𝑎𝑛𝑑 𝑤 < 𝑤′) set to 1 if 𝑤 ends before 𝑤′ starts and 0 vice versa. A continuous variable 𝑡𝑤𝑖 ≥ 0 defines the starting time of a task. This will be used for maximal time lag constraints, and defined ∀𝑤, 𝑤 ′ ∈ 𝑊 𝑎𝑛𝑑 ∑𝑤′ 𝑀𝑇𝐿𝑤𝑤′ + 𝑀𝑇𝐿𝑤′𝑤 > 0. The continuous non-negative variable 𝑡𝑒 represents the time of event 𝑒, and the 𝑜𝑝

free variable 𝑛𝑢𝑚𝑜

is used for the total number of operators of profile 𝑜 needed.

Table 1 Parameters Parameter

Definition

𝐷𝑤

Total amount of working hours for task 𝑤 ∈ 𝑊, if assigned only to one operator

𝐺𝑛𝑤

Reduction coefficient to the work task 𝑤’s makespan when it is done 𝑜𝑝 𝑜𝑝 by 𝑛 operators, 𝑤 ∈ 𝑊, 𝑀𝐼𝑁𝑤 < 𝑛 < 𝑀𝐴𝑋𝑤

𝑃𝑜𝑤

1 if task 𝑤 ∈ 𝑊 can be done by operators with profile 𝑜 ∈ 𝑂, 0 otherwise

𝑀𝐴𝑋𝑤

𝑜𝑝

Maximum number of operators that can work on task 𝑤

𝑜𝑝 𝑀𝐼𝑁𝑤

Minimum number of operators that can work on task 𝑤

𝑃𝑅𝐸𝑤𝑤′

1 if the precedence graph includes a precedence relationship between work tasks 𝑤 and 𝑤′, 𝑤,𝑤′ ∈ 𝑊

𝑁𝑂𝑁𝑃𝑤𝑤′

1 if the precedence graph includes a non-parallel constraint between work tasks 𝑤 and 𝑤’: 𝑤,𝑤′ ∈ 𝑊 and 𝑤 < 𝑤′.

𝑀𝑇𝐿𝑤𝑤′

1 if the precedence graph includes a maximal time lag constraint between 𝑤’ and 𝑤, 𝑤,𝑤′ ∈ 𝑊 ( 𝑀𝑇𝐿𝑊𝑊′ ≤ 𝑃𝑅𝐸𝐶𝑊𝑊′ )

𝐴𝑅𝑎𝑤

1 if work task 𝑤 is done on area 𝑎, 0 otherwise

𝐶𝐴𝑃𝑎

Maximum number of operators that can work on area 𝑎, 𝑎 ∈ 𝐴

𝐿𝑇

Lead time

𝑀

Big enough number

The formulation can be written as follows (domain restrictions omitted): 𝑜𝑝

min.(∑𝑜 𝑛𝑢𝑚𝑜 )

(1)

Subject to: 𝑡0 = 0

(2) 336


𝑡𝑒+1 − 𝑡𝑒 ≥ 0 ∀ 𝑒 ∈ 𝐸 𝑙𝑎𝑠𝑡(𝑒)

(3)

𝑡𝑒 ≤ 𝐿𝑇 ∀ 𝑒 ∈ 𝐸

(4)

∑𝑒𝑜𝑛 𝑒𝑦𝑤𝑒𝑜𝑛 – ∑𝑒𝑜𝑛 𝑒𝑥𝑤𝑒𝑜𝑛 ≥ 1 ∀ 𝑤 ∈ 𝑊

(5)

∑𝑒𝑜𝑛 𝑥𝑤𝑒𝑜𝑛 = 1 ∀ 𝑤 ∈ 𝑊

(6)

∑𝑒𝑜𝑛 𝑦𝑤𝑒𝑜𝑛 = 1 ∀ 𝑤 ∈ 𝑊

(7)

𝑡𝑓 − 𝑡𝑒 − ∑𝑤𝑜𝑛 𝐷𝑤 𝐺𝑛𝑤 𝑥𝑤𝑒𝑜𝑛 + 𝐷𝑤 𝐺𝑛𝑤 (1 − ∑𝑤𝑜𝑛 𝑦𝑤𝑓𝑜𝑛 ) ≥ 0 ∀ 𝑓 > 𝑒, 𝑤 ∈ 𝑜𝑝 𝑜𝑝 (8) 𝑊, 𝑀𝐼𝑁𝑤 ≤ 𝑛 ≤ 𝑀𝐴𝑋𝑤 ∑𝑒𝑜 𝑥𝑤𝑒𝑜𝑛 = ∑𝑒𝑜 𝑦𝑤𝑒𝑜𝑛 ∀ 𝑤 ∈ 𝑊, 𝑀𝐼𝑁𝑤𝑜𝑝 ≤ 𝑛 ≤ 𝑀𝐴𝑋𝑤𝑜𝑝

(9)

∑𝑒𝑛 𝑥𝑤𝑒𝑜𝑛 = ∑𝑒𝑛 𝑦𝑤𝑒𝑜𝑛 ∀ 𝑤 ∈ 𝑊, 𝑜 ∈ 𝑂 / 𝑃𝑂𝑤 = 1

(10)

𝐸 ′ ∑𝑒−1 𝑒 ′′ =0 𝑥𝑤𝑒′′𝑜𝑛 + ∑𝑒 ′ =𝑒 𝑦𝑤𝑒′𝑜𝑛 ≤ 1 ∀ w, w / 𝑃𝑅𝐸𝑤𝑤′ = 1, ∀e ∈ E

(11)

𝑡𝑤𝑖 ≥ 𝑡𝑒 − 𝑀 (1 − ∑𝑜𝑛 𝑥𝑤𝑒𝑜𝑛 ) ∀𝑒 ∈ 𝐸, ∀𝑤 / ∑𝑤′ 𝑀𝑇𝐿𝑤𝑤′ + 𝑀𝑇𝐿𝑤′𝑤 > 0

(12)

𝑡𝑤𝑖 ≥ + 𝑀 (1 − ∑𝑜𝑛 𝑥𝑤𝑒𝑜𝑛 ) ∀𝑒 ∈ 𝐸, ∀𝑤 / ∑𝑤′ 𝑀𝑇𝐿𝑤𝑤′ + 𝑀𝑇𝐿𝑤′𝑤 > 0

(13)

𝑖 𝑡𝑤′ − 𝑡𝑤𝑖 − ∑𝑒𝑜𝑛 𝐺𝑛𝑤 𝐷𝑈𝑅𝑤 𝑥𝑤𝑒𝑜𝑛 ≤ 0, ∀𝑤, 𝑤 ′ / 𝑀𝑇𝐿𝑤𝑤′ = 1

(14)

∑𝑒𝑜𝑛 𝑒𝑦𝑤𝑒𝑜𝑛 − ∑𝑒𝑜𝑛 𝑒𝑥𝑤′𝑒𝑜𝑛 ≤ 𝑀(1 − 𝛼𝑤𝑤′ ) ∀ 𝑤, 𝑤 ′ / 𝑁𝑂𝑁𝑃𝑤𝑤′ = 1

(15)

∗ 𝑟𝑜0 − ∑𝑤𝑛 𝑛𝑥𝑤0𝑜𝑛 = 0 ∀ 𝑜 𝜖 𝑂

(16)

𝑜𝑛

𝑜𝑛

∗ ∗ 𝑟𝑜𝑒 − 𝑟𝑜𝑒−1 + ∑

𝑤 (∑𝑛 𝑛𝑦𝑤𝑒𝑜𝑛 𝑃𝑜𝑤=1

− ∑𝑛 𝑛𝑥𝑤𝑒𝑜𝑛 ) = 0 ∀ 𝑜 ∈ 𝑂, 𝑒 ∈ 𝐸

𝑜𝑝

(17)

∗ 𝑟𝑜𝑒 ≤ 𝑛𝑢𝑚𝑜 ∀𝑜 ∈ 𝑂, 𝑒 ∈ 𝐸

(18)

∗ 𝑠𝑎0 − ∑𝑤𝑜𝑛 𝑛𝑥𝑤0𝑜𝑛 𝐴𝑅𝑎𝑤 = 0 ∀ 𝑎 𝜖 𝐴

(19)

∗ ∗ 𝑠𝑎𝑒 − 𝑠𝑎𝑒−1 + ∑𝑤(∑𝑜𝑛 𝑛𝑦𝑤𝑒𝑜𝑛 𝐴𝑅𝑎𝑤 − ∑𝑜𝑛 𝑛𝑥𝑤𝑒𝑜𝑛 𝐴𝑅𝑎𝑤 ) = 0 ∀ 𝑎 ∈ 𝐴, 𝑒 ∈ 𝐸(20) ∗ 𝑠𝑎𝑒 ≤ 𝐶𝐴𝑃𝑎 ∀𝑎 ∈ 𝐴, 𝑒 ∈ 𝐸

(21)

Equation (1) is the objective function: to minimize the total number of operators. Constraint (2) forces the first event to begin at t=0 and constraint (4) assures 337


that there is no delay in the task completion. The order of the events on time is imposed by constraint (3). Constraint (5) states that the start event of a task must precede its end event. Constraints (6) and (7) limit to one the start and end per work task. Constraint (8) fixes the minimum time difference between the start and the end events to the duration of the task. A single mode for performing the task is imposed by constraints (9) and (10). As for the relations between tasks: (11) is the multimode expression for the precedence constraints. Maximal time lags equal to zero for consecutive events are expressed on constraints (12) to (14). Non-parallel constraints are (15). Resource needs are expressed on equations (16) to (18) in the case of operators and (19) to (21) for the available capacity per area.

5 Results The computational results were obtained using CPLEX12.4 solver. The tests were carried out on an Intel-Core i7-2630QM processor with 2GHz and 4 GB RAM, running Windows 7. As the standard PSPLIB instances are not valid for the structure of the problem, four different sets of 8 task instances were used. Table 2 shows the main instance characteristics. Sets 3 and 4 were also extended in order to create instances of up to 11 tasks. All instances were solved up to optimality, taking times from seconds to fifteen minutes. The solution time grew exponentially with the number of events, even when solving the same set of instances, see Figure 1. Defining fewer events has also a high impact on the first LP bound, which is tighter. There is always a optimal solution with no more than a number of events equal to Card(W)+1. However, all the tested instances had an optimal solution with fewer events than that minimum number. For each of the eight-task instances, different lead times were tested. On average, the solution time also grew as the objective Lead Time approached to the Critical Path Lead Time, see Table 3. Most of the instances require more solution time with the same number of events when new tasks are added. Withal, some were solved faster with more tasks. This shows that in some cases the structure of the problem is more important than the number of tasks itself. The detailed instances and computational results are available on (APSP). Table 2 Instance Characteristics Set

Precedences

∑MTL

Areas

No.Modes

Set1

6

1

∑NONPL Op. Profiles 1

2

2

12

Set2

8

1

1

2

2

16

Set3

7

1

1

2

2

17

Set4

7

1

1

2

2

16

338

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 Sample solving time for different Lead Times Instance

LT=31.5

LT=33

LT=34.75

LT=41

Set2_8 Tasks

10.2s

6,65s

1,79s

0.83s

1200 8Tasks_Set1_LT11.5

Solving Time (seconds)

1000

8Tasks_Set1_LT15 8Tasks_Set2_LT31.5

800

8Tasks_Set2_LT33 8Tasks_Set2_LT34.75

600

8Tasks_Set3_LT14 400

8Tasks_Set4_LT13

200

0 5

7

9

11

13

Number of Events

Fig. 1 Solution Time per instance with different number of events

6 Conclusions This work provides a new MILP formulation for a real case of MRCSP. It is a first insight on the problem and has helped us identify directions for a further research. In order to extend it to bigger instances it is necessary to make a focus on the use of pre-processing to calculate the needed number of events. As well as this, the solution times have been different for each set of instances, although they had the same task dimension. A characterization of Aeronautical Scheduling Problem instances is required in order to improve the formulation and develop pre-processing techniques suitable for both the formulation and the data sets.

7 References Alvarez-Valdés, R., Tamarit, J.M. (1993): The project scheduling polyhedron: Dimension, facets and lifting theorems, European Journal of Operational Research 67, 204–220 Artigues, C., Michelon, P., Reusser, S. (2003): Insertion techniques for static and dynamic resource-constrained project scheduling, European Journal of Operational Research 149, 249– 267. Artigues, C., Demassey, S., Néron, E. (2008): Resource-Constrained Project Scheduling – Models, Algorithms, Extensions and Applications, ISTE Ltd and John Wiley

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Brucker,P , Drexl. A, Mhring. R, Neumann. K, Pesch. E (1999). Resource-constrained project scheduling: Notation, classification, models and methods. European Journal of Operational Research, 112 (1): 3-11 Brucker P. and Knust S. (2011). Complex Scheduling. GOR-Publications. Springer Gastelum V.E (2002) Application of Lean Manufacturing Techniques for the Design of the Aircraft Assembly Line, Massachusets Institute of Technology. Master Thesis. APSP: https://www.dropbox.com/sh/9070da1dz6typ2o/V0jCAtR_8y Christofides, N., Alvarez-Valdés, R., Tamarit, J.M. (1987): Project scheduling with resource constraints: a branch and bound approach,European Journal of Operational Research 29, 262–273 Gastelum V.E (2002) Application of Lean Manufacturing Techniques for the Design of the Aircraft Assembly Line, Massachusets Institute of Technology. Master Thesis. Hartmann S. and Briskorn D. (2010) A survey of variants and extensions of the resourceconstrained project scheduling problem. European Journal of Operational Research, 207: 114. O. Kone (2009). Nouvelles approches pour la résolution du problème d’ordonnancement de projets à moyens limités. PhD thesis, Université Toulouse III -Paul Sabatier O. Kone, C. Artigues, P. Lopez, and M. Mongeau.(2011) Event-based MILP models for resource-constrained project scheduling problems. Computers and Operations Research, 38(1):3 – 13 Sprecher A, Kolisch R, Drexl (1995) A. Semi-active, active, and non-delay schedules for the resource-constrained project scheduling problem. European Journal of Operational Research; 80:94–102. Pritsker, A., Watters, L., Wolfe, P. (1969): Multiproject scheduling with limited resources: A zero-one programming approach, Management Science 16, 93–107. Zapata JC,Hodge BM, Reklaitis GV (2008) The multimode resource constrained multiproject scheduling problem: alternative formulations. AIChEJournal;54(8):2101–19.

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A Model of Makespan Flow-shop Scheduling under Ergonomic Requirements Asensio-Cuesta S1, Gomez-Gasquet, P2, Andrés C3, Alemany M.M.E4 Abstract This paper address the recent growing interest the industrial environment has put over the healthy work. The ergonomics studies worker´s fatigue and muscular stress risks. It shows the need to measure and evaluate risks to improve the efficiency and reduce the costs. Based on a literature review from the scheduling and ergonomics point of view implications are highlighted. The paper presents a MILP mathematical model to minimize makespan in an n-job flow shop problem with sequence dependent setup times considering recovery times.

Keywords: Flow-shop, Setup Time, Makespan, Ergonomic, Recovery Time

1Sabina

Asensio Cuesta ( e-mail: [email protected]) Departamento de Proyectos de Ingeniería. Escuela Técnica Superior de Ingeniería de Diseño. Universitat Politècnica de València Cno. De Vera s/n, 46022 Valencia, Spain. 2

Pedro Gómez Gasquet ( e-mail: [email protected]) Centro de Investigación de Gestión e Ingeniería de la Producción (CIGIP). Universitat Politècnica de València Cno. De Vera s/n, 46022 Valencia, Spain 3

Carlos Andrés Romano ( e-mail: [email protected]) Research Group in Reengineering, Operations Management, Group Work and Logistics Excellence, Industriales. Universitat Politècnica de València Cno. De Vera s/n, 46022 Valencia, Spain. 4

María del Mar Eva Alemany Díaz ( e-mail: [email protected]) Centro de Investigación de Gestión e Ingeniería de la Producción (CIGIP). Universitat Politècnica de València Cno. De Vera s/n, 46022 Valencia, Spain * This research has been carried out in the framework of a project funded by the Spanish Ministry of Economy and Competitiveness (Ref. DPI2011-23597) and two projects funded by Universitat Politècnica de Valencia Program for the Support of Research and Development 2011: “Methods and models for operations planning and order management in supply chains characterized by uncertainty in production due to the lack of product uniformity” (Ref. PAID-0611/1840 ); “Analysis of the interactions of ergonomic risk factors in the development of work related musculoskeletal disorders and a predictive model design”. (Ref. PAID-06-11/2063).

341


1 Introduction to Ergonomic Flow-shop Scheduling Design decisions made in the production system design phase can affect both ergonomics and productivity in the resulting system (Neumannetal et al., 2002 ; Neumann et al., 2006). It has been demonstrated how ergonomic risks at the workplace cause a lot of damage to health and quality of life of workers, deteriorate economic results of employers and of the economy as a whole (Otto and Scholl , 2011). An inadequate ergonomic work conditions are mainly associated with work-related musculoskeletal disorders (MSDs), and those disorders are a major cause of work-related illnesses (Asensio-Cuesta, 2012). MSDs are associated with maintenance of awkward postures, lifting loads, performing repetitive movements, exposure to vibration, deficient psychosocial conditions (Bernard et al., 1997; Diego-Mas, 2009; Asensio-Cuesta, 2012) and stress (Faragher et. al., 2005). Moreover these risks factors worsen when there are not adequate rest periods for workers or, “lack of recovery periods” (Colombini et al. 2002). This “lack of recovery periods” increase muscle fatigue and therefore workers´ probability of suffer MSDs. Mathiassen (2006) states that the proper recovery of muscles is crucial to prevent the occurrence of musculoskeletal injuries, breaks at work decrease the likelihood of musculoskeletal pain (Rundcrantz et al., 91). Work-related MSDs are a cause of concern not only because of the health effects on individual workers, but also because of the economic impact on organizations and the social costs. MSDs involve direct costs such as costs due to the management of identified musculoskeletal disorders and include insurance, compensation, medical and administrative costs. MSDs also have indirect costs such as costs attributed to sick leave, hiring and training of new employees, reduced productivity levels and the effects on production and quality of work (e.g. possible loss of customers due to delays or dissatisfaction) (European Agency for Safety and Health at Work, 2011). From an economic perspective data related to MSDs that underline the importance of avoiding mentioned illnesses exist. Thus, in the United States there were 317,440 MSDs in 2008 requiring an average of 10 days away from work, two more days than the average for all days-away-from-work cases (Bureau of Labor Statistics, 2009). Taking into account MSDs indirect costs the total yearly cost of all workplace injuries at well over $1 trillion or 10% of United States Gross Domestic Product (Melhorn et al., 2001). In Spain, according to the VII National Survey of Working Conditions conducted in 2011, 77.5% of workers report feeling a musculoskeletal disorder (National Institute for Safety and Health at Work, 2011). Even some studies estimate that this problem involves a cost of 1.6% European Gross Domestic Product (Díez-of-Ulzurrun et al., 2007). A relationship between modifiable health risk factors and health care costs is supported by research. Health promotion interventions appear to provide positive financial returns, most notably for health care costs and absenteeism reduction (Golaszewski, 2001). Effective prevention at workplace of illnesses (musculoskel342


etal disorders) through active intervention is necessary and also decreases costs significantly by reducing the disability experienced by the individual employee (Melhorn et al., 2001). MSDs prevention can be done by re-designing the tasks to eliminate potential risks, like lack of recovery periods, or when task re-design is not possible due to production, technical or economic constraints organizational strategy must be implemented. Winkel et al. (1992) demonstrated that the ergonomic exposure risk of a worker depends on three factors: the magnitude of the risk, exposure time and frequency. On these basis the correct workstation and tools ergonomic design will decrease the amplitude of the risk, and an adequate distribution of rest breaks in worker´s schedule will decrease the duration of their exposure and fatigue. The question of rest breaks and the determination of their duration and scheduling has long been a focus of ergonomic studies in industry. Many studies have been conducted to examine the optimal time period for breaks and the effects on productivity and musculoskeletal discomfort symptoms. However, no univocally defined criteria already exist to establish work-rest periods. Furthermore the duration of the recovery periods depend on ergonomic risk factors present in each case: awkward or static postures, repetitive movements, lifting tasks, etc. Rohmert (1973) suggested that with the exponential increase of fatigue during work the rule for rest breaks is 'little and often'. Kogi (1982) recommended that to decrease fatigue with repetitive work there must be brief intra-work pauses where the muscles are rested from static load and there must be a break after a period of continuous work. The Australian Health and Safety Commission (Victorian Occ. HSH, 1988) indicates that working periods with repetitive movements exceeding 60 minutes, without recovery periods (breaks, pauses, change or total rest muscle group previous by employed), cannot be considered acceptable. Colombini et al. (2002) establish that the ratio between working time (with repetitive movements) and recovery time must be of at least 5:1 (50 minute ‘work and 10 recovery). On the basis of this optimal distribution of work-rest authors evaluates the risk due to the lack, or inadequacy, of the distribution of recovery periods in case of repetitive tasks and also calculate recovery periods for operations requiring isometric contractions (albeit occasional) by times and level of force required. The problem to establish an adequate recovery period design changes when lifting tasks are involved, in lifting tasks the risk level not only depends on duration of the task, it also depend on other factors such as weight of the load lifted, lift position, grip of the load and frequency (Waters et al., 93). Therefore, a profound evaluation of the positions involving lifting must be done to establish suitable recovery periods to achieve a tolerable risk level for workers. For that assessment Niosh equation can be applied (National Institute for Occupational Safety and Health, 1991). On the other hand, lack of physical activity can adversely affect musculoskeletal health (Bernard, 1997), for instance, work with visual display terminal VDT exposes workers to a static charge, although low intensity can cause musculoskeletal disorders in the neck and shoulders (Visser, 04). Dul et al (1991) developed a model to find the 343


optimum work-rest schedule for static work. Bystrom et al. (1991) proposed a method for establishing the optimum work-rest ratios in cases where intermittent static muscle actions are involved. The model predicted that for a given total work time and total rest time, many short work-rest periods are better than fewer long work-rest cycles. For 8 hour workday, Commissaris et al. (2007) recommend a recovery period after 1 hour continuous standing, and a recovery after 2 hour continuous sitting, and total time at this position does not exceed 4 hours. This recommendation is based on the ISO 11226 standard (International Organization for Standardization, 00). On 8 hour work day workers should have a recovery period of at least 7.5 minutes in the morning, and at least 10 minutes in the evening, after each work shift of at most 1 ½ hours. The micro-pauses, for example, every 20 minutes work 30 seconds pause, also limit the accumulation of fatigue in neck and shoulders (McLean et al., 2001). In conclusion, to determinate the number, duration and time of recovery periods in a work scheduler to prevent MSDs a previous and exhaustive ergonomic risk analysis should be done. At this stage, it is important to highlight that repetitive tasks are very often required to be performed in industry working environments where work in flowshop configurations are performed. Design flow-shop scheduling considering productivity and ergonomic criteria to prevent work related MSDs is the aim of this paper. Many years have passed since the first paper about flow-shop was published (Johnson, 1954), where an optimal solution for the case of two machines and n jobs was presented. Since then many researchers have studied the different possibilities of flow-shop problems which may involve. A comprehensive review of flow-shop scheduling problems focus on makespan minimization was presented in Hejazi and Saghafian (2005). Also Gupta and Stafford (2006) reviewed over the last 50 years, where it is shown the wide scope of problems have been treated and where they conclude that still exists a gap between the theoretical-abstract modelling and the development of models which are closer to real-life production systems. Some papers (Framinan et al., 2004), (Ruiz and Maroto, 2005) and (GomezGasquet et al., 2012) have contributed to reduce the gap. In-between different operations in a flow-shop configuration, setup times to reconfigure each resource to the next sublot; this sublot may be part of the same job or even from a different one. To reduce the gap, setup concept has been widely tackled in flow-shop environments (Allahverdi et al., 1999). In this paper, setup times will be sequence dependent (SDST); setups depend not only on the job to be processed next, but also on its immediately preceding job on the same resource. Other setup consideration was published in Cheng et al. (2000) where an extend review of flow-shop problem with setup times. Considering setup times in flow-shop is an approach to industrial environment but some times is not enough. The establishment of work and rest periods in line with ergonomic requirements have influence on the productive scheduling. Our proposal is based on setup time sequence dependent on flow-shop where processing and setup times could be increased due to the ergonomic requirements. 344


The ergonomic requirements, we are focused on, are worker´s adequate recovery periods. Thus, ergonomic requirements modify the sequences scheduling, the best no-ergonomic sequences could not be the best now. Moreover, rest periods are added during a processing time the concept of sublot emerges, this means dividing a job into a number of smaller sublots, but not overlapping operations between successive machines. Whereby it cannot be considered lot-streaming (Reiter, 1966). Therefore, flow-shop scheduling designing under ergonomic work-rest requirements should be taken into account sublots schedule. In scheduling sublots can be addressed in different ways. A fashionable concept is Lot Streaming (LS) that allows splitting jobs in smaller entities, sublots, what makes easier material transfer between stages. In the flow-shop, LS makes possible makespan or Cmax reduction (Sarin and Jaiprakash, 2007). Although it is a concept wich we will want to apply in the future, has not been considered in this work, in order to avoid interactions.

2 Approach to an Ergonomic Assessment in Flow-shop Scheduling As it has been introduced in the previous section, in a wide range of industrial situations companies usually work in flow-shop configurations, where there are m resources in series. Each job has to be processed on each one of the m resources (worker or machines). All jobs have to follow the same route, i.e., they have to be processed first on worker 1, then on machine 2, and so on. After completion on one resource a job joins the queue at the next resource (Brucker, 2004). In order to determine a quantitative ergonomic risk value in a flow-shop scheduling due to inadequate recovery periods for workers our proposal applied (Colombini et al., 2002) approach. In (Colombini et al., 2002) two methods to assess ergonomic risk level due to inadequate work-rest distribution are described. First method considers the optimal distribution ratio of repetitive tasks and recovery as 50 minutes work and 10 recovery. Under those criterion, the maximum continued period that can be spent carrying out repetitive task in condition defined as “acceptable” are 50 minutes. All extra minutes, continue with respect to those periods, which are spent without significant recovery periods, are considered as periods of potential overload. In proposed second method each hour is defined as being “risk-free” or “at risk”. An overall risk is determined by the overall number of hours at risk. If the ratio between time work-recovery periods is 5:1 to 6:1, the hour is considered as being risk-free (risk 0). If ratio is between 7:1 and 11:1, the risk assessed is 0.5. If the work-recovery ratio exceeds 11:1, the risk factor is 1, because the ratio is judged as being unsatisfactory. Over an 8-hour shift, interrupted by lunch break, but with no other pauses at all, the maximum score of 6 will be counted: in fact, the hour of work which is followed by the lunch break and the last hour of work in 345


the sift, can be considered as “not risk”, because they are followed by sufficient recovery periods. Figure 1 illustrate an example of task and breaks schedule and Table 1 shows total work time, rest time and risk values. 1º h. A

2º h. A

3º h.

4º h.

A

A

5º h. Lunch

6º h.

7º h.

A

A

Pause 10 min. (Setup)

8º h.

9º h.

A

A

Pause 10 min. (Setup)

Fig. 1 Working scheduler with a single repetitive task is carried out (Adapted from Colombini et al. (2002)) Table 1 Counting time respectively in good recovery or in potential overload and the risk level due to “lack of recovery” for every hour (Adapted from (Colombini et al., 2002)). Hour

Work

Recovery

Risk Minutes spent Minutes spent in after recovery potential overload

1

60 min

0 min

1

50

10

2

50 min

10 min (setup time)

0

-

50

3

60 min

0 min

1

50

10

4

60 min

0 min

0

-

60

5

0 min

60 min (lunch break) 0

-

-

6

60 min

0 min

1

50

10

7

50 min

10 min (setup time)

0

-

50

8

60 min

0 min

1

50

10

9

60 min

0 min

0

-

60

Total

460 min

80 min

4

200

260

In figure 1 job A schedule lasts 460 minutes in that worker has 200 minutes of recovery and 260 minutes are spent in conditions of potential overload. In order to illustrate the complexity and the change of paradigm that is proposed, an example is shown in Figure 2. In the upper part of figure jobs are scheduled without considering recovery periods, in the schedule 1 the sequence is A-B, in the schedule 2 is B-A, where process and setup times are indicated in the figure. The makespan of permutation sequence B-A is 225 minutes, the best. But at the bottom, a rest period of 10 minutes is added every 50 minutes of work in both sequences. Considering ergonomic aspects the makespan A-B is the best option with 240 minutes. As it has been mentioned before, as a result of adding rest periods during a processing time sublot appear, job A is divided into 3 sublots A(50), A(30) and A(20) in schedule 1.e (Figure 2).

346


Fig. 2 An example of setup time sequence dependent flow-shop scheduled without consider rest periods (Schdule 1 and 2) and considering ergonomic rest period (Schedule 1-e and 2-e)

Applying (Colombini et al., 2002) methods flow-shop schedules can be assessed to determine ergonomic risk level due to inadequate work-rest distribution. In Figure 3 that illustrates an example of flow-shop schedule without ergonomic restrictions worker 1 (Wk1) spent 30 minutes in potential overload and the first hour has Risk level 1 (50 minutes without recovery), worker 2 (Wk2) 20 minutes with potential overload and there are not hours under risk. While in figure 4 after ergonomic restriction added workers are not in potential overload any minute.

Fig. 3 Scheduler 1 ergonomic risk assessment due to work-rest distribution.

Fig. 4 Scheduler 1-e ergonomic risk assessment due to work-rest distribution.

Figure 5 shows a schedule with an makespan of 225 where a worker 1 is under ergonomic risk 30 minutes because of not adequate rest periods are including and a worker 2 is in the same situation 20 minutes. However in schedule 2-e (Figure 6)

347


designed with ergonomic work-rest satisfactory ratio (5:1) workers a not exposed to overload due to lack of recovery period risk.



Thus, consider in the design of flow-shop schedules appropriate breaks is compatible with makespan optimization and also brings prevention of MSDs benefits.

3 Model Definition In this section, a proposed MILP for a flow-shop scheduling problem is presented. Sequence dependent setup time and operations standby for a recovery time when exceeding the maximum recommend continuous working period considering the ergonomic aspect are the main characteristics of the proposed problem. In the problem modelled resources are worker or are worker-depended. The objective function is minimizing the makespan and ergonomic work-recovery requirements are included as model constraints. Using the classical notation the model will be presented as n/F/SRW,SDST/Cmax. This model consists in a flow-shop (F) of r stages (R), one worker each stage, where n jobs (N) must be processed. The following assumptions are made: (1) all jobs are available at time zero; (2) the processing and setup time of each item is known and deterministic; (3) no preemption is allowed; (4) machines are available at any time; (5) each machine can process at most one job at a time; (6) each job can be processed on one machine at a time; (7) sequence dependent setup times (SDST) are considered; (8) and, job operation could be paused, standby recovery worker (SRW). In the MILP model jobs are divided in sublots if some recovery time is required in order to avoid working periods larger than emax. In this case sublots are separate by a fixed recovery period T R. The transfer unit between operations is the job, not the sublot. In other case, one sublot by job is considered. Setup times are always 348


considered time for recovery the workers, so setup time are forced to be at least T R period large. The problem consists to decide the job schedule to minimize makespan. With the aim of constructing a general mathematical model, the information will be presented using the following indexes: i,t index set of jobs {1..n}; l, v index set sublots of i job in r stage {1..Zi}. r index set of stages on the shop {1..R} Parameters in the model are the data known beforehand: Zi number of units in job i Pi,r processing time for one unit of job i at stage r St,i,r setup time for job i, preceded by a job t, at the stage r TR recovery time for any worker after a working period emax ergonomic working time. Maximum working time after a recovery M a positive number larger than makespan M’ a positive number larger than maximum processing time of any job in any stage + TR MILP model determines the following variables: Xl,i,r (integer) number of units in sublot l of job i at stage r Cl,i,r (integer) completion time of sublot l of job i at stage r SXt,i,r (integer) extended setup time for job i, preceded by a job t, at the stage r 1, if job 𝑡 is performed before job 𝑖 at stage 𝑟 qt,i,r = { 0, otherwise 𝐡𝐥,𝐯,𝐢,𝐫 = {

𝟏, 𝐢𝐟 𝐬𝐮𝐛𝐥𝐨𝐭 𝒍 𝐢𝐬 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐞𝐝 𝐛𝐞𝐟𝐨𝐫𝐞 𝐬𝐮𝐛𝐥𝐨𝐭 𝐯 𝐨𝐟 𝐣𝐨𝐛 𝒊 𝐚𝐭 𝐬𝐭𝐚𝐠𝐞 𝒓 𝟎, 𝐨𝐭𝐡𝐞𝐫𝐰𝐢𝐬𝐞

1, if sublot 𝑙 of job 𝑖 at stage 𝑟 𝑖𝑠 𝑝𝑟𝑜𝑐𝑒𝑠𝑠𝑒𝑑 (𝑋𝑙,𝑖,𝑟 > 0) Yl,i,r = { 0, otherwise

With these notations, the problem can be formulated as the following MILP model. The objective is to minimize makespan (1): 𝐹. 𝑂. 𝑚𝑖𝑛 𝑧 = 𝐶𝑚𝑎𝑥

(1)

The constraints of the model are presented below in two sets, each representing one type of system constraint. The model is subject to: Precedence constraints: This set of constrains ensures the processing order of jobs and sublots.

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𝐶𝑚𝑎𝑥 ≥ 𝐶𝑙,𝑖,𝑟

∀𝑙, ∀𝑖, ∀𝑟

(2)

𝑋 𝐶𝑙,𝑖,𝑟 ≥ 𝐶𝑣,𝑡,𝑟 + 𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟 + 𝑆𝑡,𝑖,𝑟 + 𝑀 ∗ (𝑞𝑡,𝑖,𝑟 − 1) ∀𝑙, ∀𝑣, ∀𝑡, ∀𝑖, ∀𝑟 𝑡 ≠ 𝑖 (3) 𝑋 𝐶𝑙,𝑖,𝑟 ≥ 𝐶𝑣,𝑡,𝑟 + 𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟 + 𝑆𝑡,𝑖,𝑟 − 𝑀 ∗ 𝑞𝑖,𝑡,𝑟

∀𝑙, ∀𝑣, ∀𝑡, ∀𝑖, ∀𝑟 𝑡 ≠ 𝑖

𝐶𝑙,𝑖,𝑟 ≥ 𝐶𝑣,𝑖,𝑟 + 𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟 + 𝑇𝑅 ∗ 𝑌𝑣,𝑖,𝑟 + 𝑀′ ∗ (ℎ𝑣,𝑙,𝑖,𝑟 − 1) ∀𝑙, ∀𝑣, ∀𝑖, ∀𝑟 > 1 𝑙 ≠ 𝑣

(4)

(5)

𝐶𝑙,𝑖,𝑟 ≥ 𝐶𝑣,𝑖,𝑟 + 𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟 + 𝑇𝑅 ∗ 𝑌𝑣,𝑖,𝑟 − 𝑀′ ∗ ℎ𝑙,𝑣,𝑖,𝑟 ∀𝑙, ∀𝑣, ∀𝑖, ∀𝑟 > 1 𝑙≠𝑣

(6)

𝐶𝑙,𝑖,𝑟 ≥ 𝐶𝑣,𝑖,𝑟−1 + 𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟 𝐶𝑙,𝑖,𝑟 ≥ 𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟

∀𝑙, ∀𝑣, ∀𝑖, ∀𝑟 > 1

∀𝑙, ∀𝑖, ∀𝑟

(7) (8)

The constraint set (2) determines maximum completion time or makespan. Constraint (3) y (4) ensures that a job cannot start before the previous job at the same stage r has been completely processed. Constraint (5) y (6) ensures that any two sublots of any job are processed simultaneously and between both a recovery time TR is added. Constraint (7) ensures that any sublot of a job can start in the next stage before all sublots have been completed in the actual stage. Constraint (8) ensures first sublot start time is not negative. Constraints related to sublot sizes and duration of working and recovery periods: 𝐿

𝑖 ∑𝑙=0 𝑋𝑙,𝑖,𝑟 = 𝑍𝑖

∀𝑖, ∀𝑟

𝑃𝑖,𝑟 ∗ 𝑋𝑙,𝑖,𝑟 ≤ 𝑒𝑚𝑎𝑥 𝑋 𝑆 𝑡,𝑖,𝑟 ≤ 𝑆𝑡,𝑖,𝑟 𝑋 𝑆 𝑡,𝑖,𝑟 ≤ 𝑇𝑅

(9)

∀𝑙, ∀𝑖, ∀𝑟

(10)

∀𝑡, ∀𝑖, ∀𝑟 𝑖 ≠ 𝑡

(11)

∀𝑡, ∀𝑖, ∀𝑟 𝑖 ≠ 𝑡 ′

𝑋𝑣,𝑖,𝑟 − 𝑍𝑖 ∗ 𝑌𝑙,𝑖,𝑟 ≤ 𝑀 ∗ (1 − ℎ𝑙,𝑣,𝑖,𝑟 )

(12) ∀𝑙, ∀𝑣, ∀𝑖, ∀𝑟 𝑙 ≠ 𝑣

(13)

Constraint (9) ensures that all the units are processed for all jobs at all the stages. Constraint (10) ensures that the processing time of each sublot will remain less than ergonomic time for all jobs at all stages. Constraint (11) and (12) ensures setup time considered between two jobs includes at least a recovery time period. And

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constraint (13) ensures that if a sublot v is processed (Xv,i,r=0) after a sublot l of any job then the value of Yl,i,r let add a recovery time TR in constraint (5) and (6).

4 Conclusions The proposed model is a suitable tool for designing of shop-flow schedules where the makespan is minimized and, at the same time, ergonomic work-recovery periods are included in order to prevent work related MSDs. The suggested model requires an initial effort for the evaluation of the ergonomics risks factors presented in each machine (workstations) to establish the adequate relation between work and recovery periods while preventive benefits outweigh the effort. After the comparison between a flow-shop with and without considering ergonomic aspect, we can conclude that the problem presented is, as it is highlighted in section 2, an interesting challenge from research point of view, where further research needs to be carried out in order to exploit this technic/concept properly. This approach might improve companies’ efficiency it allows us to reflect reality and thus include restrictions on models up often avoided. And we should not forget that these problems, once we introduce SDST combined with lot splitting, are probably NP-hard. In the introduction point the relevance of differentiating between the machine and the operator resource has emphasized. New requirements based on healthrelated and working conditions have emerged. Although the industrial reality is complex, has shown an example that serves to illustrate some effects on the makespan when considering new restrictions. However, its industrial application needs to be validated using experimental analysis, cases studies, etc. But modelling is the first step on this path, and this work has helped to build it. In the future two paths are open. On one hand, contribute with new methods that should be capable of providing solutions in a reasonable time for realistic problems. On the other hand, our research will introduce and consider more realistic approaches such as Hybrid FS environments (HFS) or HFS/FS and lot streaming combination. Moreover, future research in this area could focus on an extended model to minimize both makespan and ergonomic risk by means of introducing ergonomic risk measures into the objective function. Also, another possible line of research would be developed a method (model or metaheuristic algorithm) that provides flow-shop scheduling where makespan is minimized and a worker´s rotation schedule is proposed where the content of the jobs to be performed by workers involve an effective change of activity. In this way, the risk of suffering musculoskeletal disorders may be reduced.

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5 References Allahverdi A, Gupta J N D Aldowaisan T (1999). A review of scheduling research involving setup considerations. Omega, 27(2), 219–239. doi:10.1016/S0305-0483(98)00042-5 Asensio-Cuesta S, Diego-Mas J A, Canós-Darós L (2012). A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria. Int J Adv Manuf Technol, 60:1161–1174 Diego-Mas JA, Asensio-Cuesta S, Sanchez-Romero M A, Artacho-Ramirez MA. (2009). A multi-criteria genetic algorithm for the generation of job rotation schedules. Intl J Ind Ergon,39(1):23-33 Bernard B. (1997). Musculoskeletal disorders and workplace factors: A critical review of epidemiological evidence for work-related musculoskeletal disorders of the neck, upper extremity, and low back. Cincinnati, Ohio. National Institute for Occupational Safety and Health (NIOSH), Brucker, P. (2004). Scheduling Algorithms. 4th edition Springer. Berlin Heidelberg New York. Bureau of Labor Statistics (2009). Nonfatal occupational injuries and illnesses requiring days away from work, 2008. Economic news release. Bystrom, S. (1991). Physiological response and acceptability of isometric intermittent handgrip contrations. Arbete och alsa – Niosh (Sweden) Cheng, TCE., Gupta, JND., Wang, GQ. (2000). A review of flowshop scheduling research with setup times, Production and Operations Management , 9 (3):262282 WOS:000167983500004 Colombini D, Occhipinti E, Grieco A. (2002). Risk Assessment and Management of Repetitive Movements and exertions of upper limbs, Oxford: Elsevier. Commissaris DA, Douwes M, Looze M P. (2007). Recommendations for sufficient physical activity at work. C. Berlin and L-O. Bligård (Eds): Proceedings of the 39th Nordic Ergonomics Society Conference, Lysekil, Sweden. Díez-de-Ulzurrun M, Garasa-Jimenez A, y Eransus-Izquierdo J, (2007). Work related musculoskeletal disorders. Navarro Institute of Occupational Health. Government of Navarre. Dul J, Douwes M, Smitt P. (1991). A work-rest-model for static postures. In: Y.Queinnec and F.Daniellou (Eds) Designing for Everyone: Proceedings of the 11th Congress of the International Ergonomic Association, volume 1, New York, Taylor and Francis, 93-95 European Agency for Safety and Health at Work. (2011). OSH in figures: Occupational safety and health in the transport Sector — An Overview. European Risk Observatory Report Faragher, E. B., Cass, M., Cooper C. L.(2005). "The relationship between job satisfaction and health: a meta-analysis". Occupational Environent Medicine, 62, 105-112 Framinan JM, Gupta JND, Leisten R. (2004). A review and classification of heuristics for permutation flow-shop scheduling with makespan objective. Journal of the Operational Research Society, 55 (12), 1243–1255. Doi: 10.1057/palgrave.jors.2601784 Golaszewski T. (2001) Shining Lights: Studies That Have Most Influenced the Understanding of Health Promotion's Financial Impact. American Journal of Health Promotion: May/June 2001, Vol. 15, No. 5, pp. 332-340. Gomez-Gasquet P, Andres C,. Lario FC (2012). An agent-based genetic algorithm for hybrid flowshops with sequence dependent setup times to minimise makespan. Expert Systems with Applications. 39(9): 8095-8107, doi: 10.1016/j.eswa.2012.01.158 Hammerschmidt DM. (2008). The Prevalence of Work-related Musculoskeletal Disorders in Certified Members of the National Athletic Trainers' Association. ProQuest. Hejazi, SR Saghafian, S (2005). Flowshop-scheduling problems with makespan criterion: a review, International Journal of the Operational Research, 43(14):2895-2929 DOI: 10.1080/0020754050056417

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Hilla, W. (2006). Produktivität und Ergonomie gemeinsam entwickeln. Erfahrungen aus der betriebsärztlichen Tätigkeit bei Audi AG. Presentation at MTM Bundestagung 26.10.2006, Stuttgart. International Organization for Standarization, (2000). ISO 11226, Ergonomics - Evaluation of static working postures. ISO, Geneva, Swizerland, Mark Melhorna JM, Larry KW, O'Malleyc MD. (2001). Successful Management of Musculoskeletal Disorders, Human and Ecological Risk Assessment: An International Journal, 7(7): 1801-1810 Johnson, S. M. (1954). Optimal two and three stage production schedules with setup times included. Naval Research Logistics Quarterly, 1(1), 61–68. doi:10.1002/nav.3800010110 Kogi K (1982) Finding appropriate work-rest rhythm for occupational strain on the basis of EMG and behaviour changes. In: P.A. Buser, W.A Cobb, T. Okuma (eds) Kyoto Symposium: Electroencephanolography and clinical neurophysiology, Amsterdam, Elsevier, Biomedical Press, 738-49 MacLeod D., Kennedy E. (2008). Job Rotation System. Available via: http://www.lni.wa.gov/wisha/ergoideas/DocumentsFiles/idea719.pdf, last access date: May / 2008 Mathiassen SE. (2006). Diversity and variation in biomechanical exposure: What is it, and why would we like to know?, App Ergon. 37:419-427 National Institute for Ocuppational Safety and Health. (1991). FL THorpe & CO. Innc:, Health Hazard Evaluation, HETA 90-0273-2130 (Washington, DC: NIOSH) National Institute for Safety and Health at Work. (2011). VII National Survey of Working Conditions. Available via: http://encuestasnacionales.oect.es/enge/EngeCuestionarios.jsp, last access date: March/ 2013 Neumann WP, Kihlberg S, Medbo P, Mathiassen SE, Winkel J. (2002). A case study evaluating the ergonomic and productivity impacts of partial automation strategies in the electronics industry. Int J Prod Resh, 40(16):4059-75 Neumann WP, Winkel J, Medbo L, Magneberg R, Mathiassen SE. (2006). Production system design elements influencing productivity and ergonomics: A case study of parallel and serial flow strategies. Int J Oper Prodn Man. 26(8):904 – 923 Otto A, Scholl A. (2011). Incorporating ergonomic risks into assembly line balancing. Eur J Oper Res 212: 277-286 Reiter S. (1966). A System for Managing Job-Shop Production. The J Business, 39(3):371-393. Rohmert, W. (1973) Problems of determination of rest allowances. Part 2: Determining rest allowances in different human tasks. Applied Ergonomics 4,3,158-162 Ruiz R, Maroto C (2005). A comprehensive review and evaluation of permutation flowshop Heuristics. Eur J Oper Res, 165 (2), 479–494, doi: 10.1016/j.ejor.2004.04.017 Rundcrantz BL, Johnsson B, Moritz U. (1991). Occupational cervico-brachial disorders among dentists. Analysis of ergonomics and locomotor functions, Swed Dent J 15(3):105-15. Sarin SC, Jaiprakash P. (2007). Flow Shop Lot Streaming. Springer. Victorian Occupational HSH (Australia). (1988). Draft code of practice. Occupational Overuse Syndrome. Visser B. (2004). Upper extremity in low-intensity tasks. Thesis. Vrije Universiteit Amsterdam. Waters TR, Putz-Anderson V, Garg A, Fine LJ. (1993) Revised NIOSH equation for the design and evaluation of manual lifting tasks, Ergon 7: 749-776

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Solving the Car Resequencing Problem with Mix Banks Valero-Herrero M1, Garcia-Sabater J.P 2, Vidal-Carreras P3, Canos-Daros L4 Abstract Automotive industry has employed mixed-model assembly lines to obtain efficient production flows. Although the sequence in which products appear on the line is contemplated at the beginning of the process, perturbations in production frequently occur in the sequence. Hence, resequencing is necessary. This work addresses the resequencing version of car sequencing with mix-banks, where the quality sequence is in-depth analysed. Buffer input and output algorithms are proposed, which are verified by the simulation models implemented in SIMIO. A sensitivity analysis is also done for the different operational factors.

Keywords: Mixed Model Assembly Lines, Car Sequencing Problem, Simulation, In-depth Analysis, Dynamic Algorithm

1 Introduction Mixed-model assembly lines, which are used in car manufacturing, allow the efficient production of a large quantity of different models. The use of these lines requires overcoming the sequencing problem, to which the literature has paid con1Maria Valero Herrero ( e-mail: [email protected]) Grupo ROGLE - Departamento. de Organización de Empresas. Universitat Politècnica de València. Camino de Vera S/N, 46022 Valencia 2Jose

P. Garcia-Sabater ( e-mail: [email protected])

3Pilar

I. Vidal-Carreras ( e-mail: [email protected])

4Lourdes

Canos-Daros ( e-mail: [email protected])

* The work described in this paper has been supported by the project "Corsari Magic DPI201018243" by Ministerio de Ciencia e Innovación del Gobierno de España within the Program "Proyectos de Investigación Fundamental No Orientada". This paper also has been supported from the Project PAID-06-12-SP20120717 of the Universitat Politècnica de València and the project TIN2008-06872-C04-02/TIN.

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siderable attention (Boysen et al., 2009). The objective of the sequencing problem is to determine the succession order of models appearing on the line by considering different objectives such as components consumption levelling, levelling the appearance of models on the line, workloads on stations and total line stoppage time (Xiaobo et al., 1999). The components levelling is important for both internal (Valero-Herrero et al., 2012) and external logistics. In (Garcia-Sabater et al., 2008; Garcia-Sabater et al., 2010) is showed the effects of suppliers sequence. As suggested by Boysen et al. in (2010), the problem considered in practical applications tends to be a resequencing problem in which reordering the appearance sequence is sought rather than the sequencing problem as set out in most works in the literature. On automobile assembly lines, resequencing is necessary for two main reasons. Firstly, the different sections making up the process have different sequencing objectives (Poler et al., 1999). Secondly, a series of unforeseen events may occur which amend the initial sequence considered. Other causes can be given to the rupture of the sequence as the regulation buffers existence or existence of parallel lines where products are branched and reintroduced on a line later (García et al., 1999). According to the classification established by Boysen et al. (2012) for resequencing problems (Figure 1), the problem contemplated in the present work can be considered physical operational and dynamic resequencing, because decisions are made in real time. It can also be classified as reactive and proactive; proactive because it is performed in a buffer situated between two sections requiring different sequences; reactive because it may be due to perturbations in the sequence caused by breakdowns in former sections, shortages of material, urgent orders and defects. Regarding configuration, it is a parallel line buffer, and the objective would be Car Sequencing, avoiding disregarding the constraints fixed by the assembly line by employing sequencing rules.

Fig. 1 Graph depicting the resequencing problems classification (Boysen et al., 2012).

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This work is arranged as follows: having presented the literature on the use of parallel lines buffers, there is a description of how the buffer operates. Section 4 describes the model for resequencing by using the algorithms implemented in buffer inputs and outputs. Section 5 presents the simulation model implemented in SIMIO. Finally, Section 6 provides the results of the experimentation done for the model performance study and the conclusions drawn from this work.

2 Resequencing by a Mix Bank Mix banks, also called parallel line banks or selectivity banks in the literature, consist in several parallel lines, with a limited capacity, which are used to store products. Products are introduced into the lines with available capacity and products are extracted from those situated at the front (the first position) of each line. The literature contains different applications of parallel line buffers which are situated before the paints section where the objective is to minimize changes in colour (Cicirello y Smith, 2004; Moon et al., 2005a; Spieckermann et al., 2004). Nevertheless, there are very few works on resequencing by parallel lines before the assembly line. The objective of the majority of works involves reordering (Boysen y Zenker, 2013; Meissner, 2010); that is, reordering the sequence to obtain the initial sequence. Very few authors (Choi y Shin, 1997; Moon et al., 2005b; Valero-Herrero et al., 2011a; Valero-Herrero et al., 2011b) have set the objective in sequencing of disregarding the constraints established by the assembly line as little as possible. Resequencing in such buffers with several lines in which to store products has, in turn, two decision problems: buffer input and buffer output. In this sense, Moon (2005b) selects the cars which exceed the maximum allowed time at the front of the line, and the maximum storage time allowed. Of these, see if any car disregards the constraints. Of those that do not, selects the one with the lowest smooth ratio. Choi and Shin (1997) employ lines that are assigned to certain products. If the product has no assigned line or if the corresponding line is full, the product is introduced into the line whose last product is the least similar. For outputs, the intention is to minimize the number of constraints.

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3 Model for Resequencing CSP in a Mix Bank

3.1 A Detailed Description of the Problem The buffer that is the object of this study is a parallel line buffer, which is situated between the trim assembly lines and the final assembly line. This buffer is employed to compensate the stoppages that arise in various assembly line areas. As it has parallel L lines, we can resequence because there are as many vehicles available as the number of buffer lines at all times. Extraction candidates will be located at the front of each line. Each vehicle will be assembled according to customer specifications, who will have previously defined them depending on whether or not a specific option (k) is necessary. The Vijk property of a product located at position j on line i takes a value of 1 if it requires option k, and a value of 0 if not. For each option, which assumes a spacing constraint, also known as physical constraints (Garcia-Sabater, 2001), an Mk:Nk-type sequencing rule is available. The usual way to express these constraints, this being a generalisation of the proposal put forward by Monden (1993), is: “No more k-type M cars for each consecutive N units”. For all the rules, a Zk penalisation applies in accordance with each rule’s restrictiveness.

3.2 Notation The notation employed in developing the algorithms is presented in Table 1. Table 1 Notation Index i (L) j (C)

The index referring to buffer lines. The index referring to the position within each line, with the first position being closest to the output. The index referring to product properties.

k (NR) Parameters V0,j,k Value of property k of the product situated at position j of the line before the buffer. It takes value 1 if it has this property, and 0 otherwise. Vi,j,k Value of property k at position j of buffer line i. It takes value 1 if it has this property, and 0 otherwise. Bj,k Value of property k at position j of the buy-off, a line before the final assembly line. It takes value 1 if it has this property, and 0 otherwise. L Number of buffer parallel lines. C Capacity of each buffer line. R Number of constraints.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) Notation Parameters P Depth. Number of units used to make comparisons. Zk Weight associated with disregarding constraint k. Mk:Nk Sequencing rule. No more Mk products of the consecutive N k with option k. MIXk Proportion of products whose k property is equal to 1. It is calculated in relation to the total products. Data defined in the products input Variables qi Quantity of products on one line. wi A value that quantifies the weight of each line to assign a product to a line. sjk Value of property k at position j of the sequence to be evaluated. ni Quantity of extracted product of one line during a simulation. z Total penalisation of a sequence. Zp Penalisation of a sequence with depth p. zmin Penalisation of the sequence with depth 1, whose sequence with depth p has penalisation minimum. zminp Minimum penalisation of one sequence with depth p. s Sequence to be evaluated, with number line. v Sequence to be evaluated, with buffer position. l Line assigned

3.3 Input Algorithm The input algorithm is executed when a product is situated at position V 01 after deciding the line on which the product will be stored. To place products in the buffer, the space available on each line and a criterion relating the line content with the product to be inputted are taken into account. A weight per line is obtained in accordance with the decision rule considered. Finally, the line with a heavier weight will be assigned to the product: Next, details of each rule are provided independently, although combinations of them are possible. Rule 1: The emptier line: The weight assigned to each line is inversely proportional to the quantity of products already on this line. Rule 2: The line more similar: The product about to be inputted is compared with the last one on the line for each property. This rule can apply in-depth; that is to say, by comparing not only with the last product on the line. For example, if depth is considered to be 3, it is compared with the three last products on each line. If on any line the number of products is less than the depth value taken, it is compared with all the products on the line. Rule 3: The more similar line by weighting according to the likelihood of disregarding and/or penalisation: Weighting can be achieved by bearing in mind the following variables and a combination of these variables (Penalisation; A product mix with this property; A Space among Products according to Constraints). The heavier the weight the higher the M/N quotient. 358


3.4 Output Algorithm The output algorithm is executed every takt time, and it returns the line from which the following product will be extracted. To extract buffer products, the quality of the obtained sequence is taken into account. Sequence quality is measured according to the total penalisation obtained from disregarding constraints. The lower the penalisation obtained (z), the better this sequence is considered. The quality sequence is in-depth analysed, that is, the available sequences after remove a product are also analysed. When depth is equal to 1, the sequences obtained from the extraction of one product are only analysed. When P>1 is considered, the penalisation of a sequence would be also consider the penalisations of all previous sequences. Also, the sequence with minimum penalisation is chosen. The sequence obtained is evaluated applying for each constraint the equation (1):  Nk 1    S jk  1  M k   Vi1k  1  zi  zi  Z k    j 1 

(1)

Now the logic of the output algorithm is described.    

For each line (x), we see that there are enough pieces in the line, considering the virtually extracted pieces and add a piece to the sequence to evaluate Sequence (S) is evaluated and the penalty of that sequence is obtained (z). If the penalty is lower than the minimum penalty obtained with a sequence with p units, continue adding pieces to the sequence until to obtain a sequence of p pieces. Finally, take the sequence of p pieces with minimum penalisation and extract the first piece of that sequence. Output Algorithm 1 Initialization: Set zmin=M; zminp=M; S={B1,B2,…, Bqb} 2 for x=1 to L do [nx=0; calcule qx; actualise Vxyk;] 3 for x=1 to L do 4 if (qx>nx) {Execute Evaluate(S) with S=S+vpx;vpx=Vxy; y=nx+1; 5 zp= z (z=result of Evaluate(S)); z = z1 + …+ zp 6 if (z 𝑐), reducing the available time of the workstation for processing the next product unit. When it is not possible to complete all of the work required, it is said that an overload is generated. The objective of the MMSP-W is to maximize the total work completed (Yano and Rachamadugu, 1991), or minimizing the total overload generated (Scholl et al., 1998), being equivalent both objectives (see Theorem 1 in Bautista and Cano, 2011). ∘ , are considUsually, deterministic and fixed operation processing times, 𝑝𝑖,𝑘 ered in sequencing problems. These times are initially determined, through the MTM system (Methods and Time Measurement) in JIT (Just In Time) and DS (Douki Seisan) manufacturing environments and correspond to the time required by an average skilled operator, working at normal pace or normal speed, to perform a specified task using a prescribed method, allowing time for personal needs, fatigue, and delay. Therefore, these operation processing times correspond to the predetermined standard times (Zandin, 2001). The present study aims the extension of reference models for the MMSP-W considering variable processing times of the operations regarding the operator activation or work pace. In particular, we focus on minimizing the work overload, increasing the work pace at certain intervals of the workday, taking into account the usual conditions of the automotive companies and the relationship between the performance of the operator and his level of activation or stress level.

428


2 MMSP-W with Variable Work Pace Large automotive companies negotiate with representative employees a set of work conditions, once established the processing times of operations according to the MTM system with a work speed 100, MTM_100. Among these conditions we found the selection of work pace considered as normal for the company. Typically, the processing times accepted are the corresponding to MTM_110, which are obtained as follows: 𝑝(𝑀𝑇𝑀_110) = 𝑝(𝑀𝑇𝑀_100) ∙

100 110

= 𝑝∘ ⋅

100 110

∀𝑖 ∈ 𝐼 ∀𝑘 ∈ 𝐾

(1.1)

Obviously, from the reference times determined with the normal work pace accorded by the company, MTM_110, we can establish a correspondence between the processing times regarding any pair of work paces. To do this, we define the factor work pace, 𝛼, of an operation as the division between the processing times measured at normal work pace (𝑝) and those at the work pace that is carried out (𝑝̂ ); that is: 𝛼 = 𝑝⁄𝑝̂ . Therefore, if we consider that the processing times obtained through MTM_100 correspond with the standard work pace and the times MTM_110 with the normal ̂ (standard) and 𝛼 𝑁 = 1 (normal), respectively. pace, we can determine 𝛼 0 = 0. 90 Similarly, the companies set an activity or optimum work speed, which typically corresponds to 20% above the normal work pace (𝛼 ∗ = 1.2, MTM_132). This activity is considered the maximum work pace that a worker can develop without loss of working life, working 8 hours a day. Thus, considering that the work pace can vary throughout the workday and therefore operations can expand or contract over time, we can establish a new model for the MMSP-W from the reference model (Bautista et al. 2012). The parameters and variables of the model are: Parameters 𝐾

Set of workstations (𝑘 = 1, … , |𝐾|).

𝑏𝑘 𝐼

Number of homogeneous processors at workstation 𝑘. Set of product types (𝑖 = 1, … , |𝐼|)

𝑑𝑖

Programmed demand of product type 𝑖.

𝑝𝑖,𝑘

Processing time required by a unit of type i at workstation k for each homogeneous processor (at normal pace or activity). |𝐼|

𝑇

Total demand; obviously, ∑𝑖=1 𝑑𝑖 = 𝑇.

𝑡

Position index in the sequence (𝑡 = 1, … , 𝑇).

𝑐

Cycle time, the standard time assigned to workstations to process any product unit.

𝑙𝑘

Time window, maximum time that each processor at workstation 𝑘 is allowed to work on any product unit, where 𝑙𝑘 − 𝑐 > 0 is the maximum time that the work in progress (WIP) is held at workstation 𝑘.

429

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. 𝛼𝑘,𝑡 𝛼𝑡

Work pace factor associated with the 𝑡 𝑡ℎ operation of the product sequence (𝑡 = 1, … , 𝑇) at workstation 𝑘 (𝑘 = 1, … , |𝐾|). Work pace factor associated with the period 𝑡 (𝑡 = 1, … , 𝑇 + |𝐾| − 1) of the extended workday that includes 𝑇 manufacturing cycles (total demand) more |𝐾| − 1 additional cycles needed to complete the required work by all the units at all workstations. Note that if we associate the same factor to each moment of workday in all workstations, we have: 𝛼𝑘,𝑡 = 𝛼𝑡+𝑘−1 (∀𝑘, ∀𝑡). If 𝛼𝑘,𝑡 = 1 (normal work speed) we will use the MTM_110 scale; for 𝛼𝑘,𝑡 = 1.1 and 𝛼𝑘,𝑡 = 1.2 we will use MTM_121 and MTM_132, respectively.

Variables 𝑥𝑖,𝑡

Binary variable equal to 1 if a product unit 𝑖 (𝑖 = 1, … , |𝐼|) is assigned to the position 𝑡 (𝑡 = 1, … , 𝑇) of the sequence, and to 0 otherwise

𝑠̂𝑘,𝑡

Positive difference between the start instant and the minimum start instant of the 𝑡 𝑡ℎ operation at workstation 𝑘.

𝑤𝑘,𝑡

Overload generated for the 𝑡 𝑡ℎ unit of the product sequence at station 𝑘 for each homogeneous processor (at normal activity); measured in time.

𝑣𝑘,𝑡

Processing time applied to the 𝑡 𝑡ℎ unit of the product sequence at station 𝑘 for each homogeneous processor at normal work pace or activity.

𝑣̂𝑘,𝑡

Processing time reduced by a work pace factor 𝛼𝑘,𝑡 . We impose here: 𝑣𝑘,𝑡 = 𝛼𝑡+𝑘−1 ∙ 𝑣̂𝑘,𝑡

Model 𝑀_4 ∪ 3_𝛼1: |𝐾|

|𝐾|

𝑀𝑖𝑛 𝑊 = ∑𝑘=1(𝑏𝑘 ∑𝑇𝑡=1 𝑤𝑘,𝑡 ) ⇔ 𝑀𝑎𝑥 𝑉 = ∑𝑘=1(𝑏𝑘 ∑𝑇𝑡=1 𝑣𝑘,𝑡 )

(1.2)

Subject to: ∑|𝑇| 𝑡=1 𝑥𝑖,𝑡 = 𝑑𝑖

(∀𝑖 = 1, … , |𝐼|)

(1.3)

∑|𝐼| 𝑖=1 𝑥𝑖,𝑡 = 1

(∀𝑡 = 1, … , 𝑇)

(1.4)

|𝐼|

𝑣𝑘,𝑡 + 𝑤𝑘,𝑡 = ∑𝑖=1 𝑝𝑖,𝑘 𝑥𝑖,𝑡

(∀𝑘 = 1, … , |𝐾|); (∀𝑡 = 1, … , 𝑇)

(1.5)

𝛼𝑡+𝑘−1 ∙ 𝑣̂𝑘,𝑡 − 𝑣𝑘,𝑡 = 0

(∀𝑘 = 1, … , |𝐾|); (∀𝑡 = 1, … , 𝑇)

(1.6)

𝑠̂𝑘,𝑡 ≥ 𝑠̂𝑘,𝑡−1 + 𝑣̂𝑘,𝑡−1 − 𝑐

(∀𝑘 = 1, … , |𝐾|); (∀𝑡 = 2, … , 𝑇)

(1.7)

𝑠̂𝑘,𝑡 ≥ 𝑠̂𝑘−1,𝑡 + 𝑣̂𝑘−1,𝑡 − 𝑐

(∀𝑘 = 2, … , |𝐾|); (∀𝑡 = 1, … , 𝑇)

(1.8)

𝑠̂𝑘,𝑡 + 𝑣̂𝑘,𝑡 ≤ 𝑙𝑘

(∀𝑘 = 1, … , |𝐾|); (∀𝑡 = 1, … , 𝑇)

(1.9)

𝑠̂𝑘,𝑡 , 𝑣𝑘,𝑡 , 𝑣̂𝑘,𝑡 , 𝑤𝑘,𝑡 ≥ 0

(∀𝑘 = 1, … , |𝐾|); (∀𝑡 = 1, … , 𝑇)

(1.10)

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𝑥𝑖,𝑡 ∈ {0.1}

(∀𝑖 = 1, … , |𝐼|); (∀𝑡 = 1, … , 𝑇)

𝑠̂1,1 = 0

(1.11) (1.12)

In the model, the equivalent objective functions (1.2) are represented by the total work performed (𝑉) and the total work overload (𝑊). Constraint (1.3) requires that the programmed demand be satisfied. Constraint (1.4) indicates that only one product unit can be assigned to each position of the sequence. Constraint (1.5) establishes the relation between the processing times applied to each unit at each workstation and the overload generated in each unit at each workstation. Constraint (1.6) reduces the processing times applied regarding the work pace factor. Constraints (1.7) – (1.9) constitute the set of relative start instants of the operations at each station and the processing times reduced to the products for each processor. Constraint (1.10) indicates the non-negativity of the variables. Finally, constraint (1.11) requires the assigned variables to be binary, and the equality (1.12) fixes the start instant of the operations.

2.1 Function of the Work Pace Factor throughout the Workday The relationship between an operator’s performance and his or her level of “activation” or “arousal”, reflected in his level of stress, can be considered curvilinear. (Muse et al., 2003). The “Yerkes–Dodson law” argues that it is an inverted-U. From this idea in this work, we associate the operator’s efficiency with the work pace, by a direct correlation between the work pace factor and the stress. Thus, considering the Yerkes-Dodson‘s optimum stress curve, we determine a function of the factor work pace throughout time (see figure 1). In this way, on one hand, the first and last product-units sequenced will be processed with less activation of stress and, therefore, with a work speed similar to normal work pace. While, on the other hand, the time periods in which the operator reaches the routine, stress is increased by increasing the work pace factor until reach the fatigue that is a characteristic of the end of the workday.

431


Fig. 1 Function of work pace factor.

In our case, we define a step function of work pace factor, where 𝛼 0 is the activity factor corresponding with the MTM_100, 𝛼 𝑁 with MTM_110 (work pace established as normal by companies) and 𝛼 𝑚𝑎𝑥 with MTM_121. Thus we set the values of the work pace factor over time. Specifically: 𝛼𝑡 = {

𝛼 𝑁 = 1.0, 𝑖𝑓 (1 ≤ 𝑡 ≤ 𝑡0 ) ⋁ (𝑡∞ + 1 ≤ 𝑡 ≤ 𝑇 + |𝐾| − 1) 𝛼 𝑚𝑎𝑥 = 1.1, 𝑖𝑓 (𝑡0 + 1 ≤ 𝑡 ≤ 𝑡∞ )

(1.14)

3 Computational Experience To evaluate the influence of the incorporation of the work pace factor into the MMSP-W on the total work overload generated, we compare the obtained results by the new model 𝑀_4 ∪ 3_𝛼1 with the obtained results by the reference model 𝑀_4 ∪ 3. To do this, we use a case study that corresponds to an assembly line from Nissan's plant in Barcelona. That line has 21 workstations with an effective cycle time of 𝑐 = 175 𝑠, a time window of 𝑙𝑘 = 195 𝑠 ∀𝑘, and an identical number of homogeneous processors 𝑏𝑘 = 1 ∀𝑘. The line assembles nine types of engines (𝑝1 , … , 𝑝9 ) grouped into three classes: 4x4 (𝑝1 , … , 𝑝3 ); vans (𝑝4 , 𝑝5 ); trucks (𝑝6 , … , 𝑝9 ). Each engine class has different processing times, therefore we use several instances corresponding to different demand plans associated with a single workday of 13.127 hours with 2 shifts. Each one of these instances has a total demand of 270 engines with different production mixes. Specifically, for this manuscript we have selected 7 instances that correspond, each one, to a representative situation of the demand (see table 1).

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 NISSAN-9ENG instances and demand plans. Demand 4x4 plan 𝑝1

Vans 𝑝2

𝑝3

Trucks

𝑝4

𝑝5

𝑝6

𝑝7

𝑝8

𝑝9

1

30

30

30

30

30

30

30

30

30

2

30

30

30

45

45

23

23

23

23

3

10

10

10

60

60

30

30

30

30

6

50

50

50

30

30

15

15

15

15

9

70

70

70

15

15

8

8

7

7

12

24

23

23

45

45

28

28

27

27

18

60

60

60

30

30

8

8

7

7

In addition, considering the function of work pace defined in section 2 and the conditions of Nissan, in the computational experience we fixed the values of work pace factor as follows:

Fig. 2 Function of Nissan’s work pace factor.

To implement the two models, the Gurobi v4.6.1 solver was used on a Apple Macintosh iMac computer with an Intel Core i7 2.93 GHz processor and 8 GB of RAM using MAC OS X 10.6.7. The solutions from this solver were obtained by allowing a maximum CPU time of 7200 𝑠 for each model and for each of the 7 demand plans selected from the NISSAN-9ENG set. Table 2 shows the obtained results by each model. Table 2 Work overload (W) of the 7 NISSAN-9ENG instances selected given by Gurobi for models 𝑀_4 ∪ 3 and 𝑀_4 ∪ 3_𝛼1 with a execution time of 7200 𝑠. Optimal solutions are marked with *. # instance

#1

#2

#3

#6

#9

#12

#18

𝑉01

807,420

807,370

807,260

807,505

807,615

807,360

807,535

𝑊𝑀_4∪3

228

384

425

477

782

326

678

𝑊𝑀_4∪3_𝛼1

0*

12

0*

84

239

0*

198

100

70.80

100 96.88 100 82.39 69.44 ∆𝑊(%) The total work performed can be calculated as 𝑉 = 𝑉0 − 𝑊.

1

433


From Table 3, we can see how the incorporation of work pace factor decreases the obtained value of overall work overload, regarding the obtained value by the model 𝑀_4 ∪ 3, at all instances tested. In particular, we see that the fact of passing from a factor of 1 to a factor of 1.1, in the second third of the work shift, reduces the work overload a 96.88%, 82.39%, 69.44% and 70.80% in instances #2, #6, #9 and #18, respectively, and a 100% in instances #1, #3 and #12, reaching, in these three cases, the optimal solution.

4 Conclusions In this paper we have presented a new model, the 𝑀_4 ∪ 3_𝛼1, from the reference model, 𝑀_4 ∪ 3, proposed by (Bautista et al., 2012). This new model for the MMSP-W incorporates variable processing times of operations according to the work pace factor or activity. Specifically, it has set a staggered function of this factor throughout the workday, based on Yerkes-Dodson’s optimal stress function. This function sets the normal work pace, fixed by the company 𝛼 𝑁 = 1 at the beginning and end of the work shift, and increases this value to 𝛼 𝑚𝑎𝑥 = 1 in intermediate moments of the shift. Defined the model and work pace function, we have performed a computational experience linked to the assembly line of Nissan Powertrain plant in Barcelona. We have selected 7 instances that are representative of different demand plans that can be found and the results obtained by the new model have been compared with those obtained with the reference model. After computational experience, we have observed that an increase in the work pace of 10%, for a third of the work, shift reduces the total work overload generated, on average, 88.5%, a maximum of 100% and a minimum of 69.44%. In addition, by the incorporation of work speed concept into the MMSP-W, we have reached the optimal solution in three instances, the #1, #3 and #12, in which the overload is 0. Moreover, if we consider that the loss of an engine supposes a cost of 4000 €⁄𝑢𝑛𝑖𝑡, the cycle time is 175 𝑠 and the work schedule contains 225 workdays, we can obtain savings by a maximum of 2.79, a minimum of 1.17 and an average of 2.03 𝑀€⁄𝑌𝑒𝑎𝑟 .

434


5 References Bautista, J, Cano, A (2011) Solving mixed model sequencing problem in assembly lines with serial workstations with work overload minimisation and interruption rules. European Journal of Operational Research, 210(3), 495–513. Bautista, J, Cano, A, Alfaro, R (2012) Models for MMSP-W considering workstation dependencies: A case study of Nissan’s Barcelona plant. European Journal of Operational Research, 223(3), 669-679 Boysen, N, Fliedner, M, Scholl, A (2009) Sequencing mixed-model assembly lines: Survey, classification and model critique. European Journal of Operational Research, 192(2), 349– 373. Muse L A, Harris S G, Feild H S (2003) Has the Inverted-U Theory of Stress and Job Performance Had a Fair Test? Human Performance, 16(4), 349-364. Scholl, A, Klein, R, Domschke, W (1998) Pattern based vocabulary building for effectively sequencing mixed-model assembly lines. Journal of Heuristics, 4(4), 359–381. Yano, C A, Rachamadugu, R (1991) Sequencing to minimize work overload in assembly lines with product options. Management Science, 37(5), 572–586. Zandin K B (2001) Maynard’s industrial engineering handbook. 5 th ed.

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Impact of Ergonomic Risk Reduction in the TSALBP-1 Bautista J1, Batalla C2, Alfaro R3, Cano A4 Abstract In this paper, we present an extension to the TSALBP problem (Time and Space constrained Assembly Line Balancing) with ergonomic risk restrictions and two models to aggregate elemental tasks. We perform a study linked to Nissan to evaluate the impact that produces the ergonomic risk reduction on the number of workstations required by the line in the particular case of TSALBP-1.

Keywords: Automobile Industry, Ergonomics, Task-Blocks, Assembly Line Balancing

1 Introduction Assembly line in automobile industry is composed by different workstations arranged in series and connected by a transport system, which allows movement of the work in progress at constant speed. At each workstation is assigned a subset of

1

Joaquín Bautista ( e-mail: [email protected]) Cátedra PROTHIUS. Dpto. de Organización de Empresas. Universitat Politècnica de Catalunya. Avda. Diagonal, 647, 7th floor, 08028 Barcelona, Spain. 2

Cristina Batalla ( e-mail: [email protected]) Cátedra PROTHIUS. Dpto. de Organización de Empresas. Universitat Politècnica de Catalunya. Avda. Diagonal, 647, 7th floor, 08028 Barcelona, Spain. 3

Rocío Alfaro ( e-mail: [email protected]) Cátedra PROTHIUS. Dpto. de Organización de Empresas. Universitat Politècnica de Catalunya. Avda. Diagonal, 647, 7th floor, 08028 Barcelona, Spain. 4

Alberto Cano ( e-mail: [email protected]) Cátedra PROTHIUS. Dpto. de Organización de Empresas. Universitat Politècnica de Catalunya. Avda. Diagonal, 647, 7th floor, 08028 Barcelona, Spain. * This work is supported by the Spanish Ministerio de Educación y Ciencia under Project DPI2010-16759 (PROTHIUS-III) including EDRF fundings.

436


tasks, called workload of the station, (𝑆𝑘 ), which requires a process time that can not exceed a time, called cycle time (𝑐). In the literature we find a problems family under the acronym TSALBP (Time and Space constrained Assembly Line Balancing Problems) (Chica et al. 2010, 2011). These problems are focused on assign a set, 𝐽, of task to a set, 𝐾, of workstations, such that: (1) No area required by the station is greater than the available area per station (A), (2) all the precedence constraints are satisfied and (3) no station workload time is greater than the cycle time. In addition, if we consider the need to attain the safety and welfare of the workers assigned to workstations, we must understand and integrate the Ergonomics. This discipline studies the relation between the human and different elements of their environment. There are many methods that evaluate physical demands to which a worker is exposed throughout the workday, as: postural load (Karhu et al., 1977); repetitive movements (Colombini et al., 2002); manual handling (Waters et al., 1997). In this work we incorporate aspects related with the ergonomic risks, into the TSALBP family, adding new constraints and a particular case of TSALBP-1 is studied.

2 The TSALBP with Ergonomic In literature we can find works that have incorporated the concept of ergonomics in line balancing problems. Specifically, Otto and Scholl (Otto and Scholl, 2011) employ two techniques to incorporate the ergonomic risks to the problem SALB-1. In a first approximation, they establish, through new constraints (1.1), a maximum value for the ergonomic risk, Erg, associated to the workload, 𝑆𝑘 , of a workstation 𝑘(𝑘 = 1, … , |𝐾|), taking into account the monotony property 𝐹(𝑆𝑘 ) ≤ 𝐹(𝑆𝑘 ∪ {𝑖}) (∀𝑆𝑘 , ∀𝑗 ∈ 𝐽: 𝑗 ∉ 𝑆𝑘 ). 𝐹(𝑆𝑘 ) ≤ Erg

𝑘(𝑘 = 1, … , |𝐾|)

(1.1)

The same authors proposed an alternative to the conditions (1.1), that is the problem ErgoSALBP-1. In this case, they incorporate a new objective function composed by two terms into the problem: 𝑚𝑖𝑛 𝐾 ′ (𝑥) = 𝐾(𝑥) + 𝜔 ∙ 𝜉(𝐹(𝑆𝑘 ))

(1.2)

Where 𝐾(𝑥) is the number of workstations; 𝜔 is a nonnegative weight and 𝜉(𝐹(𝑆𝑘 )) is a function that includes the ergonomic risk 𝐹(𝑆𝑘 ), ∀𝑘 ∈ 𝐾. Similarly, we can incorporate the concept of ergonomics within TSALB problems. Therefore, from the TSALBP-1 model (Bautista and Pereira, 2007), we de437


fine a new model, the 𝑇𝑆𝐴𝐿𝐵𝑃_1_𝜎, that considers somatic factors (Bautista et al., 2012) and whose parameters and variables are the following: Parameters |𝐾|, 𝑚𝑚𝑎𝑥 Maximum number of workstations (𝑘 = 1, … , 𝑚𝑚𝑎𝑥 ). 𝑐

Cycle time, the standard time assigned to workstations to process its workload.

𝐴

Available space or area assigned to each workstation. Set of ergonomic risk factors (𝜙 = 1, … , |Φ|).

Φ 𝐹𝜙𝑚𝑎𝑥

𝐽

Maximum ergonomic risk allowed to each workstation under the factor 𝜙 (𝜙 = 1, … , |Φ|) Minimum ergonomic risk allowed to each workstation under the factor 𝜙 (𝜙 = 1, … , |Φ|) Set of elemental tasks (𝑗 = 1, … , |𝐽|).

𝑡𝑗

Processing time required by the elemental task 𝑗 (𝑗 = 1, … , |𝐽|).

𝑎𝑗

Linear area required by the elemental task 𝑗 (𝑗 = 1, … , |𝐽|).

𝐹𝜙𝑚𝑖𝑛

𝜒𝜙,𝑗

Category of the task 𝑗 (𝑗 = 1, … , |𝐽|) associated to the risk factor 𝜙 (𝜙 = 1, … , |Φ|). It is a non-negative integer value.

𝐹𝜙,𝑗

Ergonomic risk of task 𝑗 (𝑗 = 1, … , |𝐽|) associated to the risk factor 𝜙 (𝜙 = 1, … , |Φ|). Here, 𝐹𝜙,𝑗 = 𝑡𝑗 ∙ 𝜒𝜙,𝑗 . Set of direct precedent tasks of the task 𝑗 (𝑗 = 1, … , |𝐽|).

𝑃𝑗 Variables 𝑥𝑗,𝑘

Binary variable equal to 1 if the elemental task 𝑗 (𝑗 = 1, … , |𝐽|) is assigned to the workstation 𝑘 (𝑘 = 1, … , 𝑚𝑚𝑎𝑥 ), and to 0 otherwise.

𝑚

Number of workstations.

Model 𝑇𝑆𝐴𝐿𝐵𝑃_1_𝑒𝑟𝑔: 𝑀𝑖𝑛 𝑍1 = 𝑚

(1.3)

Subject to: 𝑚

𝑚𝑎𝑥 𝑚 − ∑𝑘=1 𝑘 ∙ 𝑥𝑗,𝑘 ≥ 0 𝑚𝑎𝑥 ∑𝑚 𝑘=1 𝑥𝑗,𝑘 = 1

(𝑗 = 1, … , |𝐽|)

(1.4)

(𝑗 = 1, … , |𝐽|)

(1.5)

∑|𝐽| 𝑗=1 𝑡𝑗 ∙ 𝑥𝑗,𝑘 ≤ 𝑐

(𝑘 = 1, … , 𝑚𝑚𝑎𝑥 )

(1.6)

∑|𝐽| 𝑗=1 𝑎𝑗 ∙ 𝑥𝑗,𝑘 ≤ 𝐴

(𝑘 = 1, … , 𝑚𝑚𝑎𝑥 )

(1.7)

|𝐽|

𝐹𝜙𝑚𝑖𝑛 ≤ ∑𝑗=1 𝐹𝜙,𝑗 ∙ 𝑥𝑗,𝑘 ≤ 𝐹𝜙𝑚𝑎𝑥 𝑚𝑎𝑥 ∑𝑚 𝑘=1 𝑘(𝑥𝑖,𝑘

𝑥𝑗,𝑘 ∈ {0,1}

− 𝑥𝑗,𝑘 ) ≤ 0

(𝑘 = 1, … , 𝑚𝑚𝑎𝑥 ; 𝜙 = 1, … , |Φ|)

(1.8)

(1 ≤ 𝑖; 𝑗 ≤ |𝐽|: 𝑖 ∈ 𝑃𝑗 )

(1.9)

(𝑗 = 1, … , |𝐽|) ∧ (𝑘 = 1, … , 𝑚𝑚𝑎𝑥 )

(1.10)

438


In the model, the objective function (1.3) to minimize the number of workstations (𝑚). Constraint (1.4) leads to determine the last no empty workstation. Constraint (1.5) indicates that each elemental task only can be assigned to one workstation. Constraints (1.6) and (1.7) indicates that the set of elemental task assigned to each workstation do not exceed the cycle time and the available area, respectively. Constraint (1.8) limits the maximum and minimum ergonomic risk allowed to the set of elemental task assigned to one workstation. Constraint (1.9) forces the assignment of tasks to workstations satisfies the set of precedences. Finally, constraint (1.10) requires the assigned variables to be binary.

3 Models for the Aggregation of Elementary Tasks in Taskblocks Usually, hundreds and even thousands of elemental tasks (𝑗 ∈ 𝐽) are developed in manufacturing and assembly lines used in automotive. Only, the assembly of engines in line supposes 400 elemental tasks; that volume of information difficults the aggregation of these task in workstations unless we have a reasonableaggregation method available. In the object study environment, there are subsets of tasks that can be grouped naturally, because they must or can be advisable to perform consecutively. In any case, before balancing, a previous aggregation of the tasks would be useful to simplify the present problem and thus solve it in two phases: (1) generation of task-blocks and (2) line balancing from these task-blocks. Obviously, not all aggregations will be possible. Therefore, we propose the following feasibility model that can be useful when no automatic procedure is available to create the task-blocks. The additional parameters and variables of the model are the following: Parameters ℋ 𝑇ℎ𝑚𝑎𝑥 𝐴𝑚𝑎𝑥 ℎ 𝑚𝑎𝑥 𝐹𝜙,ℎ ° 𝑥𝑗,ℎ

Set of task-blocks (ℎ = 1, … , |ℋ|) Maximum processing time allowed for the task-block ℎ (ℎ = 1, … , |ℋ|). Maximum available area for the task-block ℎ (ℎ = 1, … , |ℋ|). Maximum ergonomic risk for the task-block ℎ (ℎ = 1, … , |ℋ|) associated to the risk factor 𝜙 (𝜙 = 1, … , |Φ|). Assignment of the elemental task 𝑗 (𝑗 = 1, … , |𝐽|) to the task-block ℎ (ℎ = 1, … , |ℋ|).

Variables 𝑥𝑗,ℎ

Binary variable equal to 1 if the elemental task 𝑗 (𝑗 = 1, … , |𝐽|) is assigned to the workstation 𝑘 (𝑘 = 1, … , 𝑚𝑚𝑎𝑥 ), and to 0 otherwise.

Model 𝑀_𝐵𝑙𝑜𝑐𝑘_𝐹: 439

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. ° 𝑥𝑗,ℎ = 𝑥𝑗,ℎ

(𝑗 = 1, … , |𝐽|; ℎ = 1, … , |ℋ|)

(1.11)

∑|ℋ| ℎ=1 𝑥𝑗,ℎ = 1

(𝑗 = 1, … , |𝐽|)

(1.12)

∑|𝐽| 𝑗=1 𝑥𝑗,ℎ ≥ 1

(ℎ = 1, … , |ℋ|)

(1.13)

𝑚𝑎𝑥 ∑|𝐽| 𝑗=1 𝑡𝑗 ∙ 𝑥𝑗,ℎ ≤ 𝑇ℎ

(ℎ = 1, … , |ℋ|)

(1.14)

𝑚𝑎𝑥 ∑|𝐽| 𝑗=1 𝑎𝑗 ∙ 𝑥𝑗,ℎ ≤ 𝐴ℎ

(ℎ = 1, … , |ℋ|)

(1.15)

𝑚𝑎𝑥 ∑|𝐽| 𝑗=1 𝐹𝜙,𝑗 ∙ 𝑥𝑗,ℎ ≤ 𝐹𝜙,ℎ

(ℎ = 1, … , |ℋ|; 𝜙 = 1, … , |Φ|)

(1.16)

∑|ℋ| (1 ≤ 𝑖; 𝑗 ≤ |𝐽|: 𝑖 ∈ 𝑃𝑗 ) (1.17) ℎ=1 ℎ(𝑥𝑖,ℎ − 𝑥𝑗,ℎ ) ≤ 0 In the model the equation (1.11) sets the values of the variables from the prede° (∀𝑗 ∈ 𝐽, ∀ℎ ∈ ℋ), of elemental tasks in task-blocks termined assignment, 𝑥𝑗,ℎ which is desired to know the feasibility. Constraint (1.12) indicates that each elemental task only can be assigned to one task-block. Constraint (1.13) establishes that no task-block is empty. Constraints (1.14) (1.15) and (1.16) impose the limits of time, area and ergonomic risk to each task-block. Finally, constraint (1.17) maintains consistency in the order of precedence of the tasks. Although with the previous model we can test whether a group of elementary tasks is feasible or not, this does not guarantee that the resulting task-blocks are balanced with respect to any reasonable criterion, such as ergonomic risk of each task- block. For this reason, we propose another model, which aggregates elemental tasks such that all blocks have a similar ergonomic risk. The additional parameters and variables for the new model are: Parameters 𝐹𝜙𝑚𝑒𝑑

Medium ergonomic risk generated by the sets of assigned tasks to each taskblock, regarding the risk factor 𝜙 (𝜙 = 1, … , |Φ|). 1

|𝐽|

That is: 𝐹𝜙𝑚𝑒𝑑 = |ℋ| ∙ ∑𝑗=1 𝐹𝜙,𝑗 𝐹𝜙,ℎ Variables + (𝐹) 𝛿𝜙,ℎ

Ergonomic risk for the task-block ℎ (ℎ = 1, … , |ℋ|) regarding the risk factor 𝜙 (𝜙 = 1, … , |Φ|). That is: 𝐹𝜙,ℎ = ∑𝑗∈ℎ 𝐹𝜙,𝑗

Real variable that measures the positive difference between 𝐹𝜙,ℎ and 𝐹𝜙𝑚𝑒𝑑 . +

+ (𝐹) 𝛿𝜙,ℎ = [𝐹𝜙,ℎ − 𝐹𝜙𝑚𝑒𝑑 ] − (𝐹) 𝛿𝜙,ℎ

(ℎ = 1, … , |ℋ|; 𝜙 = 1, … , |Φ|)

Real variable that measures the positive difference between 𝐹𝜙𝑚𝑒𝑑 and 𝐹𝜙,ℎ . +

− (𝐹) 𝛿𝜙,ℎ = [𝐹𝜙𝑚𝑒𝑑 − 𝐹𝜙,ℎ ]

(ℎ = 1, … , |ℋ|; 𝜙 = 1, … , |Φ|)

Model 𝑀_𝐵𝑙𝑜𝑐𝑘_𝐹 𝑚𝑒𝑑 : |ℋ|

|Φ|

+ − (𝐹) + 𝛿𝜙,ℎ (𝐹)]] 𝑀𝑖𝑛 ∆𝑅 (𝐹) = ∑ℎ=1[∑𝜙=1 𝜆𝜙 [𝛿𝜙,ℎ

440

(1.18)


Subject to: (1.12) to (1.17) from 𝑀_𝐵𝑙𝑜𝑐𝑘_𝐹. 𝑚𝑒𝑑 + − ∑|𝐽| 𝑗=1 𝐹𝜙,𝑗 ∙ 𝑥𝑗,ℎ − 𝛿𝜙,ℎ (𝐹) + 𝛿𝜙,ℎ (𝐹) = 𝐹𝜙

𝑥𝑗,ℎ ∈ {0,1}

(∀𝜙 ∈ Φ), (∀ℎ ∈ ℋ)

(1.19)

(𝑗 = 1, … , |𝐽|; ℎ = 1, … , |ℋ|)

(1.20)

In the model, the objective function ∆𝑅 (𝐹) represents the overall discrepancy of between the real and medium value of aggregate ergonomic risk by task-block and 𝜆𝜙 is a scalar coefficient associated to the factor risk 𝜙 ∈ Φ, satisfaying ∑𝜙∈Φ 𝜆𝜙 = 1 and 𝜆𝜙 ≥ 0 (∀𝜙 ∈ Φ).

4 Computational Experience A study has been realized on a Nissan engine’s plant in Barcelona with purpose to analyze the impact that the reduction of the maximum allowed ergonomic risk produces on the number of workstations of the line. This reduction of the ergonomic risk, supposes an improvement at the job place (workstation), which have a beneficial effect on workers, avoiding injuries, and to the company, reducing absenteeism. We begun with 140 operations of the line obtained from the 378 elementary tasks, including fast test (Chica et al. 2011 and http://www.prothius.com) to create two sets of 36 task-blocks, ℋ1 (aggregation realized from result from to the configuration of workstations for the best solution of TSALBP-1) and ℋ2 (aggregation realized through the 𝑀_𝐵𝑙𝑜𝑐𝑘_𝐹 𝑚𝑒𝑑 ) (see table 1 and 2). We solved the 𝑇𝑆𝐴𝐿𝐵𝑃_1_𝑒𝑟𝑔, only considering the physical factor (|Φ| = 1; 𝑇𝑆𝐴𝐿𝐵𝑃_1_𝜎) for both sets, ℋ1 and ℋ2 , with the following parameters: (1) cycle time equal to 180 s; (2) required area, A, at each workstation equal to 400 cm; and (3) several maximum ergonomic risks (depending on the safety requirements), 𝐹 𝑚𝑎𝑥 = { 320, 325, 330, 335, 340, 345, 350, 355, 360 } 𝑒 − 𝑠 (ergoseconds). Table 3 shows the results obtained by the two sets of task-blocks. Table 1 Set of 36 task-blocks ℋ1 ℎ

𝑗 ∈ h ⊆ ℋ1

ℎ

𝑗 ∈ h ⊆ ℋ1

1 1, 5, 9

19 68

2 3, 8, 10, 11, 13, 14, 20

20 69, 70, 71, 72, 73

3 7

21 74, 75, 76, 77, 78, 79, 80

4 4, 15, 18, 19

22 81, 82, 83, 84, 86

5 6, 12, 16, 17, 21

23 85, 87, 88, 91

6 22, 26, 27

24 89, 90, 92, 99

441

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1(continued) Set of 36 task-blocks ℋ1 ℎ

𝑗 ∈ h ⊆ ℋ1

ℎ

𝑗 ∈ h ⊆ ℋ1

7 23, 24, 25, 28

25 93, 94

8 29, 30, 31, 32

26 95, 96, 97

9 2

27 98, 100, 101, 102, 103, 106

10 33

28 104

11 34, 35, 36, 37, 38, 40

29 105, 108, 109, 110, 111, 112, 113, 114, 115, 116

12 39, 42, 43

30 107

13 41, 59

31 117, 118, 119, 120, 128

14 44, 45, 46, 47, 49, 60

32 121, 122

15 48, 51

33 131, 132, 134

16 50, 52, 53, 54, 55, 56, 57

34 123, 124, 125, 126

17 58, 63, 64

35 127, 129, 130, 133, 135, 136, 137

18 61, 62, 65, 66, 67

36 138, 139, 140

Table 2 Set of 36 task-blocks ℋ2 ℎ

𝑗 ∈ h ⊆ ℋ2

ℎ

𝑗 ∈ h ⊆ ℋ2

1 1, 9, 10

19 67, 68, 71

2 5, 7, 8, 11, 13

20 69, 70, 72, 73

3 3, 14, 15, 16, 18, 19, 20

21 74, 75, 76, 77, 78, 79

4 17, 21

22 80, 81, 82, 83, 84, 85

5 4, 22, 23, 24, 26, 27

23 87, 88, 90

6 25, 28, 29, 30

24 86, 89, 91

7 6, 31, 32, 35, 36

25 92, 99

8 33, 34, 37

26 94, 98

9 2, 39, 40

27 93, 100, 101, 102, 103

10 38, 42, 43, 60

28 95, 104, 106, 108, 110, 113

11 41

29 105, 109, 112, 114, 115

12 44, 45, 46

30 107, 111, 116, 119

13 12, 48, 49, 59

31 117, 118, 131

14 47, 55

32 97, 120, 121, 132

15 52, 53, 56

33 122, 123, 124, 125, 126, 127, 134, 135

16 50, 51, 54

34 128, 129, 130

17 57, 58, 61

35 136, 137, 138, 139

18 62, 63, 64, 65, 66

36 96, 133, 140

For the experience we used the CPLEX solver v11.0 (single-processor license) running on a MacPro computer with an Intel Xeon 3.0 GHz CPU and 2 GB RAM using Windows XP without limit on the CPU time. 442

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3 Number of workstation obtained by 𝑇𝑆𝐴𝐿𝐵𝑃_1_𝜎 for sets ℋ1 and ℋ2 F

360

355

350

345

340

335

330

325

𝑚 (ℋ1 ) 𝑚 (ℋ2 )

24

24

25

--

--

--

--

--

320 --

27

27

28

28

32

32

33

35

36

From table 3 we can see that the number of workstations increases with the reduction of the maximum ergonomic risk allowed. In addition we observe that for the first group of elemental tasks, ℋ1 , aggregated without consider multi-criteria, there is not possible solution when the ergonomic risk limitation is upper than 350e-s. However for the second set, ℋ2 , we find solution for all values analyzed.

5 Conclusions We presented an extension for the TSALBP models that incorporates the ergonomic risk concept. In addition, we presented two models that allowed us to create task-blocks from elementary tasks. We have studied a case of line balancing in the Nissan engine plant in Barcelona and we have observed that the impact of the ergonomic risk reduction on the assembly line is very significant. If we want to improve the quality of jobs, the assembly line must be reconfigured. If we considered that the loss of an engine supposed a cost of 4000€, the cycle time is 180s and there are two work shifts in a day, this reconfiguration represented a cost of about 1.3 million euros for lossesramp, every time we made a new balance.

6 References Bautista J, Batalla C, Alfaro R (2012) Incorporating Ergonomics Factors into the TSALBP, Comunicación, Proceedings(CD), International Conference on Advances in Production Management Systems (APMS 2012), Rodas (Grecia). Bautista J, Pereira J (2007) Ant algorithms for a time and space constrained assembly line balancing problem. European Journal of Operational Research, 177/3: 2016-2032. Chica M, Cordón O, Damas S, Bautista J (2010) Multiobjective constructive heuristics for the 1/3 variant of the time and space assembly line balancing problem: ACO and random greedy search. Information Sciences, 180/18: 3465–3487 Chica M, Cordón O, Damas S (2011) An advanced multiobjective genetic algorithm design for the time and space assembly line balancing problema. Computers & Industrial Engineering, 61: 103-117. Chica M, Cordón O, Damas S, Bautista J (2011) Including different kinds of preferences in a multiobjective and algorithm for time and space assembly line balancing on different Nissan scenarios. Expert Systems with Applications, 38/1: 709-720.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Colombini D, Occhipinti E, Grieco A. (2002) Risk Assessment and Management of Repetitive Movements and Exertions of Upper LimbsJob Analysis, Ocra Risk Indices, Prevention Strategies and Design Principles. ISBN: 978-0-08-044080-4 Karhu O, Kansi P, Kuorinka L (1977) Correcting working postures in industry: A practical method for análisis. Applied Ergonomics, 8: 199-201 Otto A, Scholl A (2011) Incorporating ergonomic risks into assembly line balancing. European Journal of Operational Research 212/2: 277-286. Waters T R, Baron S L, Kemmlert K (1997) Accuracy of measurements for the revised NIOSH lifting equation. Applied Ergonomics 29/6: 433-438.

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Order Promising Process for Supply Chains with Lack of Homogeneity in the Product Alemany MME1, Boza A2, Ortiz A3, Poler R4 Abstract Traditionally, during the Order Promising Process (OPP), the homogeneity of different available units of the same finished good to be committed to customers has been assumed. However, this homogeneity assumption is not valid for manufacturing contexts with Lack of Homogeneity in the Product (LHP) like ceramics. In this paper, special LHP-dimensions that affect the OPP are outlined. Based on them, the specific LHP availability levels to consider during the OPP as well as the definition of allocation rules for these availability levels are described.

Keywords: Lack of Homogeneity in the Product, Order Promising Process

1

Mª Mar Alemany ( e-mail: [email protected]) Centro de Investigación de Gestión e Ingeniería de Producción (CIGIP). Universitat Politècnica de València. Camino de Vera s/n, 46022, Valencia. 2

Andrés Boza García ( e-mail: [email protected]) Centro de Investigación de Gestión e Ingeniería de Producción (CIGIP). Universitat Politècnica de València. Camino de Vera s/n, 46022, Valencia.

3

Angel Ortiz Bas ( e-mail: [email protected]) Centro de Investigación de Gestión e Ingeniería de Producción (CIGIP). Universitat Politècnica de València. Camino de Vera s/n, 46022, Valencia.

4 Raúl Poler Escoto ( e-mail: omp.upv.es) Centro de Investigación de Gestión e Ingeniería de Producción (CIGIP). Universitat Politècnica de València. Camino de Vera s/n, 46022, Valencia.


445


1 Introduction The OPP refers to the set of business activities that are triggered to provide a response to customer order requests. During the OPP, when a new customer order request arrives, it is necessary to compute whether there are enough uncommitted real or planned FGs, materials and/or resources available to fulfill the new order on time. Traditionally, the homogeneity of different available units of the same FG to be promised to customers has been assumed. This homogeneity characteristic has allowed the accumulation of uncommitted FG availabilities from different resources and time periods to satisfy the same customer order. However, this homogeneity assumption is not valid for manufacturing contexts with Lack of Homogeneity in the Product (LHP). LHP contexts are characterized by the existence of units of the same FG that differ in some characteristics (subtypes) that are relevant for the customer. LHP appears in certain industries like ceramics, textile, wood, marble, horticulture, tanned hides and leather goods (Alemany et al., 2013). These firms are obliged to include a classification stage whose localization in the production process and the classification criteria depend on each industry. The result is that the same FG originates different subsets of homogeneous quantities (subtypes). LHP has a direct impact on the OPP in several ways. On the one hand, classifying one same FG into several subtypes increases the number of references and the information volume to be processed, thus complicating system management. On the other hand, the alternatives for allocating real or planned uncommitted subtypes quantities to customer orders substantially increases and the homogeneity requirement complicates the search for a feasible and optimal solution. This is due to the fact that different subtypes of the same FG cannot be used to promise a specific customer order. Therefore, the typical way of calculating the accumulated ATP will not be valid. Not accomplishing this homogeneity requirement can lead to returns, product image and company deterioration, which may involve less customer satisfaction and even loss of customers. Furthermore, the real homogeneous quantities available of the same FG to be promised to customers are not known until their production has finished. This aspect proves a problem when customers’ orders have to be promised, reserved and served from the homogeneous units available derived from the planned production. Therefore, it is necessary to anticipate as much as possible the future availability of homogeneous quantities (subtypes) in order to serve customers with the required quantities and homogeneity level required on time. For this reason, the main purpose of this paper is to explicitly highlight the inherent characteristics of LHP manufacturing systems that impact the OPP by the definition of the so called LHP-dimensions (section 2). Based on this dimensions it will be possible to decide the most suitable way of considering the different LHP availability levels during the OPP in order to made reliable commitments

446


with customers (section 3). Finally, the impact of allocation rules of uncommitted homogeneous quantities to customers is analyzed (section 4).

2 LHP-Dimensions for OPP Different dimensions should be analyzed in order to determine the impact of LHP specific situation to the OPP. With the aim of better understanding the concepts, the OPP in ceramic sector (Alemany et al., 2013) is taken as an example.  LHP Customer Order Characteristics Dimension It is important to keep in mind that LHP becomes a managerial problem due to the homogeneity requirements of customers. As in most companies it will be essential to know from the customer order, the requested products (one, several or a product-pack), the unit measure for each product (that can be dependent on the customer class: units, pallets or trucks), the quantity and the due date. But LHP introduces a new customized aspect in order proposals: the homogeneity type required by the customer among the ordered products. The customer may require uniformity between components of a product (pearls on a necklace) or between units of the same product (ceramic tiles) or between different products of a product-pack (chairs and a dining table). In addition, the customer can specify the value of the homogeneity attributes required or, in case there are subtypes of the same item with different value, the maximum price willing to pay. The homogeneity tolerance makes reference to the customer sensibility in the permissible range of variation of LHP attributes to consider that two units of a subtype are homogeneous. This order characteristic can be or not explicitly defined by customers. For instance, in ceramic sector, customers specify the quality of the product (value) but though for each quality, several subtypes exist (the same quality tile with different tone and gage), they do not specify other homogeneity attributes (like tone and gage). Note that the order size becomes a very relevant order proposal aspect for LHP environments because the larger the orders size, the more difficult will be to meet the uniformity requirement among all their units.  LHP origin Dimension: Raw Materials & Transformation Activities LHP origin provides us with information about the inclusion or not of LHP characteristics in the availability levels. LHP can be originated by the heterogeneous characteristics of raw materials and/or components, for instance when they are directly originate from nature. LHP can also appear due to the own transformation activities (LHP-activities) or environmental characteristics (LHP-factors) that introduce certain variability in the processed items even when the input material is homogeneous. With the aim of being more exhaustive in the determination of the LHP origin, we extend the LHP definition introducing the terms Lack of 447


Homogeneity in Raw Materials (LHRM), Lack of Homogeneity in Intermediate Products (LHIP) and Lack of Homogeneity in Finished Goods (LHFG). For instance, in the ceramic sector LHP is originated for the different characteristics of the raw materials (clays) and components (glazes) but also for the production lines and kilns (LHP-activities) due to temperature and humidity (LHPfactors). Therefore, in ceramic sector, LHRM, LHIP and LHFG exist.  Subtypes Dimension: LHP Items & Classification Stages In order to ensure that customers are served with the required homogeneity, LHP supply chains are obliged to introduce one or several classification (sorting) stages along their productive process. Figure 1 shows the relationship among customer order characteristics and the definition of subtypes. The number and location of classification stages can be influenced by the homogeneity type required by customer (i.e. among components, among units of the same finished good or among different finished goods). For each sorted item, the classification criteria and the values they can take (discrete or continuous) should be identified. This provides us with the number of subtypes of the same LHP-item. The classification criteria maintains a closely relationship with the homogeneity attributes in FG required by the customer. At the same time, the possible values allowed of each attribute depend on how exigent customers are (homogeneity tolerance). Finally, it is important to know not only the existing subtypes but also their appearance in the processed quantities by the SC transformation activities. This aspect provide us information about if different subtypes can be found either in the same lot or among lots of the same resource or among different resources at the same or different point of time. Furthermore, it will be interesting to found if the relation between the input quantity of a LHP-item and the subtype output quantities are constant or variable. The subtype appearance jointly with the order size will condition not only the units to be produced in planned lots (master plan) but also the anticipation of future homogeneous quantities available (LHP availability Levels) used during the OPP. CUSTOMERS

HOMOGENEITY REQUIREMENTS

SUPPLY CHAIN CLASSIFICATION (SORTING) STAGES

Homogeneity Type

Location

Homogeneity Attributes

Classification criteria

Homogeneity Tolerance

Criteria values

Classification Stages Number

Subtypes Number

Order Size

Subtypes Appearance

Fig. 1 Relationship between homogeneity requirements and classification stages.

448


In ceramic sector, the homogeneity type is among tiles of the same model. Subtypes are classified only once at the end of the manufacturing process based on their surface defects, color and thickness. This classification criteria provide subtypes of the same FG that differ in quality (first, second, third and waste), tone and gage. Subtypes appear among lots processed in different resources and even in the same resource at different points of time due to environmental conditions.

3 Characterizing LHP Availability Levels The above LHP dimensions present a direct impact on the way of representing and calculating the different LHP uncommitted availability levels to answer customer requests. In this section traditional availability levels are first described in order to better understand the differences with respect LHP availability levels.  Traditional Availability Levels During the OPP, when a new customer order request arrives, it is usually to check whether there are enough uncommitted quantities of different availability levels for the due date requested. Three usual availability levels are defined: ATP (Available-To-Promise), CTP (Capable-To-Promise) and MATP (MaterialAvailability-To-Promise) (Figure 2). PRODUCTION STAGE -N

PRODUCTION STAGE 1

PROCESS

SUPPLY

ÍTEMS

RAW MATERIALS COMPONENTS

SUBASSEMBLIES

MATP

CTP-MP

AVAILABILITY LEVELS PLANS LEAD TIMES

MRP

CRP

FINAL ASSEMBLY

CODP- ÍTEMS

FINISHED GOODS

ATP

CTP-FAS

MASTER PLAN

MANUFACTURING LEAD TIME of CODP-ITEMS

FAS

LEAD TIME of FAS

Fig. 2 Availability levels for traditional OPP

Available-To-Promise (ATP) includes the calculation of the uncommitted quantity, either real or planned, of the items stocked at the customer order decoupling point, which is based on the master production schedule. In principal ATP can be represented on any stage of the supply chain, e. g. finished goods, components, or raw materials. The decision where to represent ATP best for a certain business is strongly linked with the location of the decoupling point (Kilger and

449


Meyr, 2008): finished goods for MTS, main component and subassemblies for ATO and raw materials for MTO. If there is not enough ATP to commit an order, the calculation of the CapableTo-Promise (CTP) quantities can be required. CTP represents the uncommitted available capacity, either real or planned, of those productive resources involved in the product fulfillment of a customer order. CTP can be checked either to produce additional quantities of CODP-items or to ensure that there is enough resources capacity to assembly CODP-items for obtaining finished goods. In the reviewed literature these two concepts are not clearly differentiate. For this reason, it is our proposal to define two kinds of CTP: CTP-MP and CTP-FAS. CTP-MP represents the uncommitted capacity of productive resources upstream the CODP to produce additional quantities of CODP-items. Consuming CTP-MP implies modify the Master Plan. CTP-FAS represents the uncommitted capacity of productive resources downstream the CODP to carry out the Final Assembly Schedule. Finally, there are authors (Meyr, 2004) that distinguish between uncommitted capacity (CTP) and Material-Available-To-Promise (MATP). In this case MATP represents the not yet assigned net capacities of materials.  LHP Availability Levels Taking as the starting point the traditional availability levels defined to promise orders, the impact of LHP in their definition and calculation is analyzed. The question is to determine in which LHP situations make sense to compute LHP availability levels with the aim of more precisely anticipating the future uncommitted homogeneous quantities. When modeling future planned LHP availabilities it is possible to define them in terms of specific subtypes or simply try to estimate the future subsets of homogeneous quantities without anticipating the specific subtype. As it will be shown it strongly depends on the customer order characteristics. The decision about defining availability levels taking into account the LHP aspect is influenced not only by the CODP location, as usual, but also by its relative position as regards the classification stages. Figure 3 shows by column when makes sense to express the uncommitted availability levels in LHP terms. Upstream the CODP it is possible to consider MATP-LHP if LHRM and classification stages upstream the CODP just at the supply activity exist. The ATP-LHP consideration is recommendable when LHRM or LHIP and classification stages exist upstream the CODP. Furthermore, the strong relationship existing between the Master Plan and the ATP should be taken into account when modeling the ATP. If the Master Plan is expressed in terms of specific subtypes or homogeneous quantities, the ATP-LHP should be expressed in concordance. However, in certain circumstances it is possible to disaggregate the Master Plan expressed in CODP-items to CODPLHP items if it is known the appearance of subtypes in lots and the splitting of quantities. Modeling MATP-LHP or ATP-LHP at the level of subtype will be necessary when:1) customer not only requires homogeneity but also defines the required 450


subtype in the order, 2) different MATP-LHP or ATP-LHP subtypes once classified do not present the same value (qualities) 3) later transformation activities can be dependent on the subtype and 4) it is known the way MATP-LHP or ATP-LHP subtypes affect the ATP-LHP and LHP finished goods, respectively. Modeling CTP-MP-LHP and CTP-FAS-LHP makes sense when there are LHP activities upstream and/or downstream the CODP, respectively, and it is known the LHP-factors and their impact on homogeneity. Along these lines, it is very important to keep in mind not only the existing subtypes but also their appearance in the processed quantities by the SC transformation activities. This aspect provide us information about if different subtypes can be found either in the same lot or among lots of the same resource or among different resources at the same or different point of time and helps us to determine the level of detail when calculating the uncommitted capacity (per resource, group of resources, etc.) and its utilization to produce additional uncommitted availability of items. When using the above CTP-LHP levels to plan new production quantities, it will be necessary to consider the constant or variable relation between the input quantity of a LHP-item and the subtype output quantities. PROCESS CLASSIFICATION STAGES

SUPPLY

PRODUCTION

YES

LHP ACTIVITIES

CODP

ASSEMBLY

YES

YES

YES

YES

LHP-ITEMS

LHMP

LHIP

CODP-LHP LHIP

LHIP

AVAILABILITY LEVELS

MATP-LHP

CTP-MP-LHP

ATP-LHP

CTP-FAS-LHP

LEAD TIMES

MANUFACTURING LEAD TIME of CODP-ITEMS

LHFG

LEAD TIME of FAS

Fig. 3 LHP availability levels for OPP.

Ceramic sector mainly follows an MTS strategy with one classification stage at the end of the process. Usually, customers only specify the FG quality within their orders and they do not specify the subtype. The ATP-LHP is obtained for the first quality quantities of the Master Plan and different lots produced by different machine or by the same machine in different periods of time are considered non homogeneous. In other words, ATP-LHP is not expressed in terms of subtypes but only homogeneous subsets are anticipated based on the same lot, resource and time period, not being possible to accumulate them to serve a customer order.

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4 Allocation rules for ATP-LHP When discrete ATP-LHP is defined in terms of subtypes, different ATP-LHP subtypes cannot be mixed to serve the same customer order. When discrete ATP-LHP is only defined by subsets of homogeneous quantities without differentiating the subtype, the only constraint consists of not allowing accumulate discrete nonhomogeneous ATP-LHP quantities. Therefore, as it has been described, the ATPLHP existence restricts the possible ways of accumulating ATP-LHP. For instance, in ceramic sector due to LHP it will impossible to accumulate ATPs from different production lines or different time periods for the same FG. For this case, the choice of reserving ATP from a specific homogeneous subset of a FG affects subsequent promises, being necessary to define allocation rules. As an illustrative example, let us assume for specific time period t for given FG that there are two homogeneous ATPs, one with a value of atp1 = 800 units and the other with a value of atp2 = 320 units. Let us also assume that the arrival of three orders (o1, o2, o3) takes place one after another with due date ddo1 = ddo2 = ddo3 = t, and that the first includes a requested quantity of 250 units (qo1), the second has a requested quantity of 600 units (qo2) and the third a requested quantity of 70 units (qo3), for all of which a real-time response must be given. In figure 4 two possible alternatives to assign ATP to the incoming orders are shown. SOLUTION A

qo1=250

qo2=600

qo3=70

Committed orders= o1, o3

atp1=800

atp1’=550

atp1’=550

atp1’’=480

atp2=320

atp2=320

atp2=320

atp2=320

SOLUTION B

qo1=250

qo2=600

qo3=70

Committed orders= o1,o2, o3

atp1=800

atp1=800

atp1’=200

atp1’=200

atp2=320

atp2’=70

atp2’=70

atp2’’=0

Fig. 4 Impact of allocation rules of ATP-LHP on committed orders

When promising the first order, it is possible to reserve the ATP of both the homogeneous quantities atp1 and atp2. Solution A assigns 250 units of atp1 meanwhile solution B assign 250 units of atp2 for the first order, being the updated atp equal to atp1’=550 and atp2’=70, respectively. Solution A cannot commit the second order, meanwhile solution B assign ATP from atp1, being the updated atp1’=200. Finally, the third order can be committed in two cases. From the examples above, we may deduce that when there are several alternatives to assign homogeneous ATPs of different subtypes to an order, the policy formulated to select one of these alternatives affects future commitments and, therefore, system 452


performance. Therefore, for maximizing customer service level and supply chain performance, properly ATP-LHP allocation rules should be defined.

5 References Alemany M.M.E., Lario Francisco-Cruz, Ortiz A., Gómez F. (2013) Available-To-Promise modeling for multi-plant manufacturing characterized by lack of homogeneity in the product: An illustration of a ceramic case. Applied Mathematical Modelling 37:3380–3398 Kilger C, Meyr H (2008) Demand Fulfilment and ATP. In: Stadtler H, Kilger C (ed) Supply Chain Management and Advanced Planning. Concepts, Models, Software, and Case Studies.,4th edn. Springer, pp 191-198. Meyr H (2004) Supply chain planning in the German automotive industry. OR Spectrum 26(4):447-470.

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Modeling the Master Plan for Supply Chains with Lack of Homogeneity in the Products Alemany MME1, Cuenca L, Ortiz A, Pérez D Abstract Master Planning of Supply Chains (SCs) with Lack of Homogeneity in the Products (LHP) strongly differs from other SCs. Although LHP affects SCs of different sectors, an absence of a common research body exists. In this paper, the characterization of LHP dimensions for Master Planning and their modeling is described. To validate the proposal an application to the fruit SC is presented.

Keywords: Master Planning, Supply Chains, Lack of Homogeneity in the Product, Model

1 Introduction Supply chains (SCs) master planning is a complicated task due to the existence of a huge number of decisions, constraints, objectives (sometimes conflictive), possible alternatives to be evaluated and the presence of uncertainties. For the case of SCs with Lack of Homogeneity in the Product (LHP), this planning task becomes even more complex as it can be described below. One of the main LHP consequences is the existence of units of the same finished good that differ in some characteristics originating the existence of subtypes. LHP becomes a managerial problem when FGs are not homogeneous and customers require homogeneity in the requested quantities. Though LHP is present in SCs of a variety of sectors (ceramic, tanned hides, leather goods, ..) and some models have been developed 1Maria

de Mar Eva Alemany Díaz ( e-mail: [email protected]) Centro de Investigación en Gestión e Ingeniería de Producción (CIGIP). Universitat Politècnica de València. Camino de Vera s/n Ed 8G -1º y 4º planta Acc D. Valencia, Spain. * This research has been carried out in the framework of the project funded by the Spanish Ministry of Economy and Competitiveness (Ref. DPI2011-23597) and the Polytechnic University of Valencia (Ref. PAID-06-11/1840) entitled “Methods and models for operations planning and order management in supply chains characterized by uncertainty in production due to the lack of product uniformity” (PLANGES-FHP)

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(Mundi et al., 2013) there is not a common body of research that allows study the relevant characteristics to take into account for properly define the SC Master Planning. In this paper the LHP dimensions relevant for master planning (section 2) and their modeling (section 3) are described. To validate the proposed framework and to clarify concepts, an application to the fruit supply chain is reported (section 4).

2 LHP Dimensions for Supply Chain Master Planning In this section, the different dimensions characterizing LHP that are relevant for the Master Planning of Supply Chains modeling point of view are described. The objective is to provide a guideline about what LHP characteristics are merely of being considered during the Master Planning and then, how to model them. To achieve this objective four dimensions are identified: 1) Transformation Activities, 2) Items, 3) Customers/Market and 4) the Customer Order Decoupling Point (CODP). In figure 1, the different elements composing each dimension, their attributes as well as the relationship among them are shown. For LHP contexts, two types of transformation activities additional to the typical ones are crucial: the classification activities and the LHP activities. After classification activities different subsets of homogeneous items are obtained. In fact, the key LHP element will be the location of classification stages along the SC as well as items classified in each one of them. Furthermore, with the aim of anticipating the homogeneous quantities available in production plans, it will be necessary to identify the transformation activities that introduce heterogeneity in the process (LHP-activities) and the variables that cause it (LHP-factors). It will be important to define the relationship between the heterogeneity origin and the productive resources (on the same machine, between machines, in time). This helps us to know the degree of detail for modeling resources in the master planning (see section 3). As regards Items, two kinds can be distinguished: LHP-items and NO-LHPitems. LHP-items are those non homogeneous items that affect the lack of homogeneity in finished goods. We distinguished between the Lack of Homogeneity in Raw Materials (LHRM), Lack of Homogeneity in Intermediate Products (LHIP) and Lack of Homogeneity in Finished Goods (LHFG), respectively. Only LHP items are classified in different subtypes based on certain classification criteria. A subtype of an item presents a specific value of the aspects of the classification criteria. Certain attributes are inherent to the subtypes like its number, status and value. The number of subtypes will depend on the classification criteria for sorting LHP items and their possible values. If the value of all the attributes defining a subtype remains the same along time, the status of the subtype will be static, otherwise it will be considered as dynamic. Furthermore, different subtypes of the 455


same LHP-item can have the same or different economic value. Usually, different economic values imply the existence of several qualities and the appearance of undesirable stocks for subtypes with low economic value. Finally, it is important to know not only the existing subtypes but also their appearance in the processed quantities by the SC transformation activities. The subtype appearance provide us information about if different subtypes can be found either in the same lot or among lots of the same resource or among different resources at the same or different point of time. Furthermore, it will be interesting to found if the relation between the input quantity of a LHP-item and the output quantities of each subtype are constant or variable. CODP

TRANSFORMATION ACTIVITIES CODP-LHP LOCATION VS CLASSIFICATION ACTIVITIES

LHP ACTIVITIES

• LHP FACTORS

•SC LOCATION

Determines

REQUIRED PRODUCTS

ORDER SIZE

REQUIRED HOMOGENEITY

CODP-LHP LOCATION PER SUBTYPE

CODP-LHP LOCATION VS LHP ACTIVITIES

Determines

•VALUE OF THE HOMOGENEITY •MAXIMUM PRICE

CLASSIFICATION ACTIVITIES

•BETWEEN COMPONENTS •BETWEEN UNITS •BETWEEN DIFFERENT PRODUCTS

OTHER ACTIVITIES

SPECIFIED HOMOGENEITY

MARKET/CUSTOMERS PER SUBTYPE

HOMOGENEITY TOLERANCE

CUSTOMERS CLASSES PER SUBTYPE

Classify CUSTOMER ORDER LHP CHARACTERISTICS

Originates

MARKET/CUSTOMERS LHP DEFINITION

Influence

Require Define

Include

NO LHPITEMS

LHP-ITEMS

Appear

SUBTYPES OF LHP-ITEMS

ITEMS

NUMBER OF SUBTYPES

STATUS OF SUBTYPES

VALUE OF SUBTYPES

SUBTYPES QUANTITIIES

SUBTYPE APPEARANCE

INPUT-OUTPUT RATIO OF SUBTYPES

•CONSTANT • VARIABLE

•IN THE SAME LOT •AMONG LOTS OF THE SAME RESOURCE •AMONG RESOURCES •SAME OR DIFFERENT POINT OF TIME

•THE SAME •DIFFERENT

•STATIC •DYNAMIC

•CLASSIFICATION CRITERIA • POSSIBLE VALUES OF EACH CRITERION

•LHRM,LHIP or LHFG

Fig. 1 Master Plan LHP-dimensions and their relationship.

As regards the customers, different SC Markets and Customers can exist depending on the subtypes they require. Because LHP management problem arises from the homogeneity requirement imposed by customers, it is crucial to identify the customizable parameters of order proposals affecting LHP. As in most companies it will be essential to know from the customer order, the requested products (one, several or a product-pack), the unit measure for each product (that can be dependent on the customer class: units, pallets or trucks), the quantity and the due date. But LHP introduces a new customized aspect in order proposals: the homogeneity type required by the customer among the ordered products. The customer may require uniformity between components of a product (pearls on a necklace) or between units of the same product (ceramic tiles) or between different products of 456


a product-pack (chairs and a dining table). In addition, the customer can specify the value of the homogeneity attributes required or, in case there are subtypes of the same item with different value, the maximum price willing to pay. The homogeneity tolerance makes reference to the customer sensibility in the permissible range of variation of LHP attributes to consider that two units of a subtype can be considered homogeneous. Note that the order size becomes a very relevant factor for LHP because the larger the orders size, the more difficult will be to meet the uniformity requirement among all their units. The SC strategy for accomplishing with customer requirements will be defined by the Customer Order Decoupling Point location. For LHP SC, different CODP locations can exist depending on the subtypes. Furthermore, for modeling the master plan it will be essential to know the relative position between the CODP and the classification activities and the CODP and the LHP location activities. Figure 1 shows the main relationships among the different dimensions and their elements. As it can be observed, LHP activities originate LHP-items that are sorted into different subtypes by classification activities. Subtypes of LHP items appear in processed quantities. Customer order LHP characteristics influence the subtype definition. Indeed, subtypes classification criteria will be conditioned by the homogeneity characteristics required by customers in products. The customer homogeneity tolerance is determinant for defining the number of subtypes, i.e. lower the homogeneity tolerance, higher the number of subtypes to be defined. When defining the quantities of subtypes to be obtained the required quantities of subtypes become crucial. Finally, for LHP SC management, different CODP can be defined depending on the subtype. Furthermore, for LHP manufacturing environments it is crucial not only the CODP location but also its relative position as regards the classification stages and LHP-Activities. This aspect represents the starting point to analyze LHP implications in the master plan that, in turn, will constitute the basis for choosing the LHP characteristics relevant to be modeled.

3. Modeling LHP for SC Master Planning The objective is to derive a master plan (MP) that anticipate the expected homogeneous quantities of each subtype (LHP Master Plan) and made properly decisions in order to accomplish with the customer requirements in terms of homogeneity, quantity and due dates. For LHP MP modeling purposes we distinguish five SC planning elements: Items, Transformation Activities (resources), LHP-factors, Time and Market/Customers. The Time element (not previously considered in the LHP dimensions) is included for introducing the own meaning of planning. Two questions are of relevance when modeling the Master Plan: 1) what SC elements of each dimension should be considered and 2) what is the level of detail for representing them. To answer the first question, the CODP position in the SC 457


is crucial. As in the traditional SC Master Planning, only those SC transformation activities upstream the CODP and their processed items are object of our analysis and, therefore, are susceptible of being modeled. Additionally the LHP-factors affecting the SC physical system upstream the CODP could be also taken into account in order to anticipate the different subtypes quantities and the subtype evolution in case dynamic state of subtypes. As regards the second question, the level of detail for representing the different SC elements in the Master Planning will be conditioned to a certain extent by the LHP characteristics chosen to be modeled. In the following paragraphs we provide with a guideline about what LHP characteristics are susceptible to be modeled in the Master Plan for the different elements described above. The existence or not of Classification and LHP Activities upstream the COPD provides us with the key for answering the question about the level of detail for representing the different SC elements (items, transformation activities, LHP-factors, Time and Market/Customers) in the LHP Master Plan.  ITEMS: When to model the Master Plan in terms of subtypes? : Two kinds of items are of relevance for Master Planning purposes: the items stored at the CODP (CODP-items) and the other items belonging to the BOM of CODPitems (i.e. items supplied or processed upstream the CODP). If there are classification activities upstream the CODP, the Master Plan should be expressed in terms of CODP-LHP items and other LHP items upstream the CODP. This is equivalent to deal with subtypes of items in the Master Plan instead of the typical items. The number of subtypes for each item will be known for the LHP dimension. To deal with subtypes in the MP increases the number of references and, therefore, increases the MP complexity. Therefore, to consider subtypes in the MP makes sense if one or more of the following situations occurs: – CODP-LHP items forecasts anticipate some LHP customer order characteristics like:  Forecasts are expressed in terms of CODP-LHP items. This will be the maximum degree of detail.  Forecasts are expressed in terms of customer classes which will be defined based on the order size, type of homogeneity and/or value of the homogeneity required. – To deal with LHP items helps better defining the lot sizes in order to serve an integer number of the different customer orders classes with homogeneous quantities. In this case, the sizing of the planned subtype quantities will allow a better balance between supply and demand, increasing customer service level and SC costs. – There are data, objectives or constraints in the MP that strongly depend on the subtypes. For instance different economic values for subtypes could imply to consider different costs of supplied material or different revenues for each subtype. 458


 TRANSFORMATION ACTIVITIES: What Transformation Activities include in the LHP Master Plan? Analogously to items, only those transformation activities upstream the CODP-LHP are candidate to be modelled. Traditionally the bottleneck resources are considered in the MP. For LHP contexts, additional considerations are made. It would be interesting to model the LHP Activities and Classification Stages of this SC part if the impact of LHP activities on the LHP items upstream the CODP is known: for instance, if there is some information about the appearance of subtypes in planned production quantities in order to anticipate them. It will be sense to model the divergent flow of items at classification activities when it is possible to estimate the input-output ratio of subtypes (i.e. subtype quantities in a lot or between lots, for instance, in terms of percentages is known).  LHP-FACTORS: When to consider LHP factors in the Master Plan?: If there is a known relationship about how certain factors, for instance, temperature or humidity, affects the LHP appearance (subtypes), either in the static or dynamic state, the MP could be taken these LHP factors into account. For this situation some classification criteria could be expressed by a function of the LHP factors for anticipating the appearance of the different subtypes.  TIME: Which is the time unit to be used in the Master Plan?: The time unit used in the master plan, i.e, the planning period length is influenced by the periodicity of decisions considered. But when the subtype state is dynamic (perishability, obsolescence,...) and it is known the magnitude of the time period that influence its state (LHP-time unit), the MP can be expressed in this LHP time unit depending on the level of detail to be achieved. If the LHP time unit is higher than the MP horizon, it not will be sense to model the dynamic state of the subtype.  CUSTOMER/MARKET ORDER: When to consider customer/market classes based on the subtypes in the Master Plan?: If the location of the CODP depends on the subtype, it will be necessary to express the MP in terms of subtypes. Traditionally, the forecast demand of CODP-items has been expressed in aggregate terms. However, to better match subtypes supply with demand it will be interesting to model different customer classes based on the subtype, order size and required homogeneity type. This is recommendable if we are able to forecast the demand of customers in terms of subtypes. To model different customer classes make sense when the profit heterogeneity of demand depends on the subtype revenue (different values of subtypes), costs (different value of LHP items of subtypes) and customer strategic importance.

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3 Fruit Supply Chain Application and Conclusions In order to better understand the described concepts and to validate them, an application to the fruit supply chain is presented. LHP Dimensions for Fruit Supply Chain: The basic transformation activities in fruit supply chains are (Verdouw et al., 2010): a) growing and harvesting, b) processing, c) washing, sorting and grading, d) packaging and labelling, e) storage and distribution and f) retailing. There are several classification (sorting and grading) activities located in different points along the productive process with the aim of eliminate waste and classify fruits into several qualities based on different attributes. Blanco et al. (2005) distinguishes the following classification activities: 1) a pre-classification stage where non-tradable fruit (waste) is separated for juice production, 2) a quality classification stage where tradable fruit is separated in several categories, and some waste is also produced at this stage, 3) the different qualities are further classified by size or weight (depending on the available technology) in several types at the gauge classification stage where some waste is also produced. There are several LHP-transformation activities along the Fruit SC that impact on the LHFG, especially on the decay and therefore, on the fruit quality: harvesting, fruit treatment (washing and classification) and handling, storage and transport. LHP-factors can be dependent on the resource (landscape), the time (harvesting period) and the environmental conditions (temperature and humidity).The LHP origin in Fruit SC is mainly due to the lack of homogeneity in the raw materials (LHRM), i.e. the fruit obtained directly from the nature. This LHRM jointly with LHP-Activities originates the existence of LHIP and LHFG. FGs in the fruit sector mainly differ in variety, quality, packaged and labeling. The existing subtypes of LHP-items depend on the classification stage and the classification attributes. There are several classification attributes in the fruit sector (Ahumada et al., 2011; Blanco et al., 2005; Mowat and Collins, 2000) that in this work we have categorized into: inherent (fruit variety), sanitary (fungus presence), esthetic (color, shape, ripeness, imperfections, …) and functional (shelf life, juice quantity, …) issues. The number of subtypes depends on the possible combinations of the above attributes that originates different qualities for a specific fruit variety. The worst values of these attributes define the non-tradable fruit (byproducts: separated for other purposes) and the waste fruit. The status of the fruit is dynamic because quality depends on the time (perishable goods). Amorim et al. (2012) distinct two perishable goods classes: those with fixed and random lifetime. Obviously the value of subtypes (qualities) is different and dynamic. As regards LHP subtype quantities, subtypes appears among different producers (fruit from different landscapes), different production lots (fruit of collected from the same landscape at different time), and among units of the same production lot. The input/output relation is variable but can be estimated, for instance, by fixed percentages (Blanco et al., 2005). In relation to the Market/customer LHP definition, the high uncertainty in the quantities and qualities obtained of each fruit variety lead 460


to the market diversification (local, national and international) (van der Vorst, 2000). There is also a great importance of the spot market to face with the supply uncertainty. Each market presents order characteristics that are different in terms of quantities, subtypes, packaging, labeling, lead times, distribution modes and sales price. Finally, multiple CODP-locations are possible for Fruit SCs. Van der Vorst (2000) and Verdouw et al. (2010) indicates that there are several elements that influence the CODP positioning upstream (perishability, decay, divergent product flows, high demand uncertainty and high degree of customization). Therefore, in the most general case, classification and LHP-activities exist upstream the CODP. Modeling LHP for Fruit Supply Chain Master Planning: There are several reasons to define the Fruit SC Master Plan in terms CODP-LHP items (subtypes) (Blanco et al., 2005): 1) independently of the CODP location, there will be always CODP-LHP items because LHP Fruit SC is always originated from the raw material, 2) several classification activities usually exist upstream the CODP, 3) customer requires different fruit qualities and each quality has different value (cost and selling price). Because different classification stages exist upstream the CODP it is recommendable to consider them for properly modeling the subtypes flow by taking into account the different balance equations at different classification stages. Different approaches exist to model the perishability aspect and their associated LHP-factors. In case perishability exists two cases could be formulated: (1) when the shelf-life is fixed beforehand, and (2) when the shelf-life is indirectly a decision variable influenced by the environmental setting. For this last case manufacturers can estimate the shelf-life of products throughout the supply chain based on external factors using the knowledge of predictive microbiology (see Amorim et al., 2012). Different customer classes should be considered based on the required quantities and subtypes, and therefore, there is recommendable to express demand forecasts based on customer classes. This paper puts forward the relevant characteristics that it is necessary to take into account for properly define the SC Master Planning.

4 References Mundi I., Alemany MME, Boza A., Poler R. (2013) A Model-Driven Decision Support System for the Master Planning of Ceramic Supply Chains with non Uniformity of Finished Goods Studies in Informatics and Control Journal, in press. Ahumada O., Villalobos J.R. (2011) Operational model for planning the harvest and distribution of perishable agricultural products Int. J. Production Economics 133:677–687 Amorim P., Günther H., Almada-Lobo B., (2012), Multi-objective integrated production and distribution planning of perishable products. International Journal of Production Economics, doi:10.1016/j.ijpe.2012.03.005 A.M. Blanco, G. Masini, N. Petracci, J.A. Bandoni (2005), Operations management of a packaging plant in the fruit industry, Journal of Food Engineering 70, 299–307Mowat and

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Mowat A., Collins R. (2000) Consumer behaviour and fruit quality: supply chain management in an emerging industry, Supply Chain Management: An International Journal, 5 (1): 45-54 van der Vorst, JGAJ, (2000). Effective food supply chains: generating, modeling and evaluating supply chain scenarios, doctoral thesis, Wageningen University. Verdouw C.N., Beulens A.J.M., Trienekens J.H., Wolferta J. (2010), Process modelling in demand-driven supply chains: A reference model for the fruit industry. Computers and Electronics in Agriculture 73:174–187

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A Design Framework for Flexible Automated Warehouses Marín L.F.1, Carrasco-Gallego R2 Abstract Reducing operational costs in e-commerce logistics by having few distribution warehouses is a competitive approach that requires strategic investments on automation. But this technology is usually highly specific and implies facing the risk of running a warehouse unable to handle a shifting demand after a period of time. This work addresses flexibility as an issue to be faced when designing automated warehouses. An approach to flexibility in this context and its relation with throughput is given, to finally obtain an eight-step procedure that allows us to include this concept in automated warehouses’ design process.

Keywords: E-commerce, Automated Warehouse, Flexibility, Warehouse Design, Material Handling

1 Background, Objectives and Methodology Flexibility in distribution warehouses has become more important than ever. Customer requirements are continuously changing while demanding low costs and high-rate service in terms of quality and time. The range of products sold on-line has widened to almost everything that we can need. All this makes e-commerce business quite demanding for logistics, and automated distribution warehouses are options to be considered due to their high throughput, fulfillment quality and compact storage. Flexibility is an additional objective that has become increasing-

1Luis-Felipe

Marín ( e-mail: [email protected]) Department of Industrial Engineering, Management and Statistics. School of Industrial Engineering (ETSII). Technical University of Madrid (UPM). 2Ruth

Carrasco-Gallego ( e-mail: [email protected]) Department of Industrial Engineering, Management and Statistics. School of Industrial Engineering (ETSII). Technical University of Madrid (UPM).

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ly interesting, but seems to be difficult to achieve within the rigid, specific and specialized world of automation. Gaining insight to face the flexibility-throughput trade-off and including it in a warehouse (re) design process are the aims of this research work, and thus two objectives are targeted: to develop a theoretical model to define flexibility and explain its sources within warehouses, and to translate it into a procedure to (re) design warehouses. The method applied is based on two pillars: one is the authors’ professional experience on a real case of design of an automatic warehouse, the other are the insights provided by the review of scientific papers. This combination of hands-on experience and scientific framework has enabled us to get the best out of each approach. This paper is organized as follows: in section 2, state-of-the art in academic research is provided in a Literature Review which covered scientific databases (IEEE Xplore, Web of Science ISI, Elsevier), leading to a gap identification after comparing the needs of professional practice and the answers given by academic literature. In sections 3 and 4 we propose our conceptual model for defining flexibility and its relationship with throughput via item’s characteristics. In section 5 a self-developed methodology for including the flexibility in warehouse design is deployed, based on the previous framework. Finally, our conclusions and further research are presented in section 6.

2 Literature Review and Gap Identification We have reviewed academic papers dealing with the following issues: (1) literature devoted to flexibility in supply chains or specifically in warehouses, (2) references that mention flexibility in the design process of warehouses, and (3) papers that discuss automation and material handling selection. Information systems and pure organizational issues that may not involve automation are excluded from this study. Christopher and Peck (2004), discuss the need to create resilient supply chains and mention robustness and resilience as synonyms of flexibility and adaptability. Resilience is defined as “the ability of a system to return to its original state or move to a new, more desirable state after being disturbed”. On the other hand, Brockmann and Godin (1997) define flexibility as the capability to easily adapt to change, mentioning specifically warehouses. The idea of flexibility in a system in general is then understood as the ability to cope with external changes keeping integrity, while adaptability is related to change internally in order to react to those external changes. Manzini (2005) and Brockmann & Godin (1997) study the multiple, rapid external changes that warehouses face, that can take place in cost or in customer demand, meaning shifting items, increasing the number of SKUs and including high variability in products’ shape, dimensions and weight. Richardson 464


(1998) identifies new products, new customer demands or volume growth as changes to be faced. Customization is a trend that impacts warehousing, especially in e-fulfillment for business to consumer (B2C), as Lederer, Mirchandani and Sims (2001) observe. The ability to cope with those changes is clearly conditioned in the warehouse design process, which includes decisions about level of automation and selection of handling material. Rouwenhorst et al. (2000) present a reference framework and classification of warehouse design and control problems, in which processes, resources and organization have to be defined. Brockmann and Godin (1997) analyze and compare different options in material storage and handling equipment and rank automated systems as the less flexible and more expensive option, while offering the highest storage density and selectivity in case of unit load or small items. Bartholdi and Hackman (2008) describe the equipment that serves to automate warehouses and how it is linked with product characteristics, and also point out the lack of flexibility as a main characteristic of automatic devices. Naish and Baker (2004) study pros and cons of automation, and claim that those systems can cope very well with changes within a limited range in throughputs and order profiles, but there is a dramatic lack of flexibility out of the set of scenarios considered during design. Related to the specifics of material handling selection Eldemir, Graves and Malmborg (2004) identify a set of parameters to be considered in developing APS, a sort of complex automation systems, and Wong (2007) addresses how automated material handling systems (AMHS) can be designed with reconfiguration features to maximize utilization and to enhance its flexibility. Centered on specific configurations, Yu and De Koster (2008) study the effects on performance of varying certain constructive parameters and operational alternatives in a so called pick-and-pass system composed by conveyor systems and pick stations. After this literature review we concluded that, although flexibility is considered a desirable characteristic of warehouses, the concept has not yet been clearly defined in academic literature. However, we can identify different views of the flexibility as the capacity to absorb product’s physical changes, accommodate variations in the volume of orders in the short and long term, deal with changes in the scheduled inputs or outputs of products and re-organize internally the resources to surmount system failures. Flexibility is considered to be related to performance, and thus it is expected to be fairly conditioned at design stage, when the automation degree is determined and resources are selected. Nevertheless, we have not found works that establish a measurement of the flexibility itself nor the relation between this and other design parameters like performance or storage capacity, thus regarding flexibility the following issues have to be addressed: what is flexibility in automatic warehouses, what flexibility depends on and how are flexibility and throughput inter-related.

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3 A Proposal of a Conceptual Model to Study System’s Flexibility In this work we will face flexibility studying the response of a warehouse to changes in inputs like products, order profiles and work volume, being focused on the adaptation of a warehouse to specific product characteristics. This requires a deep understanding of how item characteristics influence or condition processes and systems3. Besides, the design task consists in deciding what processes, systems and organizational policies are to be implemented, thus the relations between product, system and process have to be the driving forces in design and operation of a warehouse. As a consequence, and as illustrated in Fig. 1, the guide for studying a system’s flexibility is a three-axis frame model of products, systems and processes that helps us to cover all the relationships and interfaces between them.

Fig. 1 Model to analyze the impact of changes of products (self production)

Based on systems, we will consider that flexibility can be evaluated through two quantitative aspects (feasibility and impact in throughput) and two qualitative ones (adaptability and scalability):

We consider subsystems or modules as the basic working cells (i.e. a picking station, a palletizer, an AGV…) that can be arranged into systems on which branch processes take place, being the warehouse a combination of systems. 3

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 Strict feasibility. Referred to the physical limits and maximum capacities of the system, it is related to the question: Is the system able to decant/pick/store a new item?  Impact in throughput due to changes in items or orders. It is related to the question: How a new item or order profile will condition the throughput?  Scalability. It is the possibility to increase or decrease the capacities of the system in the short term according shifting needs.  Adaptability: it means the easy re-configuration of the modules or elements of the system –which impact on scalability also. Pure element adaptation is closely related to match tool parameters and item characteristics, as for example could happen in a variable grip handling device.

4 Influence of Item Characteristics on Throughput Changes in items’ characteristics may limit the path or ‘branch’ of the process that products can follow. Weight, dimensions, fragility or surface affect item handling and may lead to operative decisions; each handling-related parameter has a specific contribution in the total time of the activity, affecting the throughput. Besides, items in automated systems are generally moved on re-usable containers or pallets, called transport elements, whose design will depend on item’s dimensions, weight, fragility or rigidity. Certainly, the nature of items imposes various conditions on the handling in basic processes and on the transport element definition. Within this frame, warehouse operations can be classified according to two categories of basic activities: manipulation and transportation processes. Decanting, picking or sorting are examples of manipulation processes, and imply the direct handling of products by operators or machines leading to changes in the packing entities. The relationship studied here is that between item (units, packs or cartons) and handling process. Manipulation can also mean the transference of entities between source and target transport elements, studying the relationship that links them (pallets, dollies, totes or cartons) with items’ characteristics. On the other hand, transportation means transference of transport elements within sub-systems, where the grip transport element – system should be studied. Any process in a warehouse can be then de-composed in a sequence of manipulation and transportation processes. In manipulation processes, changes in strict feasibility can be measured evaluating if the item may be handled with the grip item-handling unit (automatic or manual), and also if the item fits into the source and target transport elements, while throughput could be measured as number of units processed in a time period. This will condition the number of transport elements that are inducted into the transportation system. A fictitious item representative of the whole order can be defined (profile item), which is equivalent to assume that only one type of item is managed in the order. With the average processing time per item, a total 467


processing time per order can be obtained, and having capacity constraints (i.e: total or maximum processing time per day) the throughput can be calculated. Then providing a measurement of the impact of variations in item/order characteristics on manipulation process’ throughput is feasible, and can be propagated downstream to transportation subsystems with a simple evaluation, reaching to a measure for the whole system.

5 Designing for Flexibility: a Framework Proposal A flexibility-oriented design of systems starts in the evaluation of the possible changes that the warehouse may suffer from the standpoint of items and orders. Derived from the description of interactions between warehouse’s entities shown in Fig. 1, we may think in propagating product’s changes impact on processes and systems: traveling along the figure counter-clockwise it is possible to make a preselection of systems, while a second round reviewing the interactions systemproduct, product-process and process-system will lead us to know the impact of product changes on throughput, and give us the basis to carry out what-if analysis with different change scenarios. Fig. 2 depicts the steps proposed in our design for flexibility framework.

Fig. 2 Complete evaluation process. Linked by letters and colors to the first and second round on the three-axis model (self production)

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(Step A) Order profile / item characteristics. The type of items to be managed, the order profile and the number of orders per time period have to be clarified:  To develop a list of item characteristics and evaluate them in order to find limitative properties that may branch the activity in different processes, as well as to identify those ones that may impact on handling. Dimensions and weight are ranged from minimum to maximum levels in order to pre-select suitable systems and evaluate strict feasibility once we select the handling resources.  To have an average throughput as a design objective. Here a ‘representative or fictitious item’ with average dimensions and weight, plus variation ranges on them is required to simplify calculations. (Step B) Process branches. Deciding what items are handled automatically in some or all parts of the flow, and what are to be derived to manual processes is required. This deep impact decision will condition the flows in the warehouse, but will also narrow the range of products inducted in the automatic system, thus reducing variability. (Step C) Sub-systems selection. Once we know what is expected to be handled in the warehouse, the systems can be chosen from commercial catalogs and the identification of manipulation and transportation modules is done. (Step D) Transport element definition. Selected systems will limit the dimension and type of transport element to be used. With this and the requirements imposed by items’ characteristics, the transport element should be defined. Besides, it has to be looked for the suitability of the transport element for further processes (i.e. the container may require to be stackable, to admit separators or to allow ergonomic manual handling). (Step E) Manipulation model. The throughput calculation can be done on the already identified manipulation processes, requiring a previous estimation or measurement of the time impact of each item characteristic on this specific handling process. The limitation in throughput for the process must be known. (Step F) Transportation model. Transportation needs can be expressed as number of transport elements to be moved per time period, and are derived from the results of manipulation model. Applying this with the aid of a net flow model, bottlenecks can be identified. (Step A’) Order profile / item characteristics. What-if analysis. With reference values for the ‘order type’ and ‘item type’ already calculated, scenarios of variation can be forecasted. Changes can be intended in volume or in the average representative item (as a result of changes in the order profile), and may mean a shift in the average manipulation time. (Step A’’) Measure impact in throughput. The last step is to evaluate the throughput again for every scenario generated in the previous point, comparing the results with the reference ones. The impact on throughput and possible shifts in bottlenecks can be calculated, leading to possible re-design decisions.

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6 Conclusions and Further Research The general aim of this research work was to set a methodology to include flexibility within the (re) design process of automated warehouses, and has been deployed after reviewing academic literature and developing a framework to understand the meaning and sources of flexibility in warehousing. The drivers that led us to address the flexibility issue were the interactions system-product-process in a warehouse. We have concluded that flexibility in warehouses is the capacity to absorb external changes in products and orders with little or none internal reconfiguration and moderate impact in throughput. Flexibility is evaluable through four dimensions: strict feasibility, impact in throughput, adaptability and scalability. The first two ones are deeply dependent on item and order characteristics and are closely related to the transport elements to be used. Changes in manipulation times due to changes in characteristics of the items are propagated downstream on the process and changes the number of circulation transport elements, thus affecting the throughput. Based on all this, a procedure of eight steps has been proposed to include and evaluate flexibility in warehouse design or re-design process. New questions arise after this work opening complementary or new research lines. Tools are needed to decide when to split the process into manual branches and when to consolidate manual and automatic paths, looking for an impact in throughput for the whole warehouse. To include item rotation or class categories in the study could also help to split class categories in different ‘parallel’ systems or aggregation groups in order to improve flexibility. Adaptability and scalability haven’t been addresses in this work, and could be assessed or benchmarked after a wide comparative analysis of warehousing integrators’ portfolio and published references of real installations.

7 References Bartholdi, J. J. and S. T. Hackman (2008): Warehouse & distribution science. URL http://www2.isye.gatech.edu/~jjb/wh/book/editions/wh-sci-0.95.pdf, 2011. Brockmann, T. and P. Godin (1997): Flexibility for the Future in Warehouse Design. IIE Solutions, 29 (7), pp. 22-25. Christopher, M. and H. Peck (2004): Building the resilient supply chain. International Journal of Logistics Management, The, 15 (2), pp. 1-14. Eldemir F., R. J. Graves and C. J. Malmborg (2004): Conceptualizing automated palletizing systems. International Journal of Production Research, Vol 42, pp. 5119-5132. Lederer, A. L., D. A. Mirchandani. and K. Sims (2001): The search for strategic advantage from the World Wide Web. International Journal of Electronic Commerce, 5, pp. 117-134. Malmborg, C. J. and K. Al-Tassan (2000): An integrated performance model for orderpicking systems with randomized storage. Applied Mathematical Modelling, 24 (2), pp. 95-111.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Manzini, R. (2005): Design and control of a flexible order-picking system (FOPS) a new integrated approach to the implementation of an expert system. Journal of Manufacturing Technology Management, 16 (1), pp. 18-35. Naish, S. and P. Baker (2004): Materials Handling Automation - when is it justified? Richardson, H.L. (1998): Design warehouses for flexibility. Transportation & Distribution. Rouwenhorst, B., B. Reuter, V. Stockrahm, G. Van Houtum, R. Mantel and W. Zijm (2000): Warehouse design and control: Framework and literature review. European Journal of Operational Research, 122 (3), pp. 515-533. Wong, M. M. (2007): On-line reconfiguration to enhance the routing flexibility of complex automated material handling operations. Robotics and Computer-Integrated Manufacturing, 23 (3), pp. 294-304. Yu, M. and R. De Koster (2008): Performance approximation and design of pick-and-pass order picking systems. IIE Transactions, 40 (11), pp. 1054-1069.

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Supplier Evaluation and Selection: a Review of the Literature since 2007 Moliné JI, Coves AM 1 Abstract Supplier selection is currently a subject of great importance to companies. Numerous articles have been published recently, recommending different methods and/or procedures for evaluating and selecting the suppliers with whom the purchasing company will work. The present article reviews a total of 39 articles dealing with this subject, published between 2007 and the present day, in magazines indexed by Journal Citation Reports (in ISI Web of Knowledge). They will be analyzed in order to determine: (i) procedures used in determining criteria, (ii) identification and structure of the criteria under consideration, (iii) methods used to evaluate and select the suppliers and (iv) aims in the selection of suppliers.

Keywords: Supplier Selection, Supplier Criteria

1 Introduction Supplier selection is one of the strategic elements in managing purchases, as the ability of a company to satisfy its clients, as well as its own continuity, depends to a large extent on its suppliers. Purchases have a direct and important impact on profits, as the acquired products and services (purchases), have a significant influence on the cost structure of manufacturing companies, ranging from 42% to 79%. On the other hand, there is a larger framework which defines the general policies of organizations with respect to their relationships with suppliers, some examples being the establishment of partnership deals or global supply chain management.

1

Anna Maria Coves Moreno ( e-mail: [email protected]) Department of Management, Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya, Av. Diagonal 647, 08028 Barcelona, Spain * The authors gratefully acknowledge the partial support of grant DPI2010-15614 (Ministerio de Economia y Competitividad, Spain).

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Supplier selection is basically determined by four decisions, which are: (1) Having the appropriate procedure for determining the criteria and establishing their structure and ranking. (2) Identifying the criteria with which the suppliers will be evaluated. (3) Selecting the most suitable suppliers from those available. (4) Obtaining a list of suppliers, the Suppliers Panel, with whom orders will be placed. This process involves different types of criteria (strategic, tactical, and operational) which are cohesive, as they originated in corporate strategy and are in consonance with it. The described situation has motivated the present article, which reviews a total of 39 articles dealing with this subject, published between 2007 and the present day, in magazines indexed by Journal Citation Reports (in ISI Web of Knowledge). They all deal with the subject of supplier evaluation and selection. This article is organized in such a way that the following section includes an analysis of the principal aspects and, finally, Section 3 shows the conclusions which can be drawn from this review of the latest developments.

2 Analysis of the Latest Developments (since 2007) The most recent theories on supplier selection are organized according to the 4 decisions mentioned in the introduction, in a way that Section (2.1) analyzes the procedures for determining the criteria, and Section (2.2) studies the criteria used for supplier selection. Section (2.3) describes the methods used to evaluate and select the suppliers, while section (2.4) analyzes the aims of the different works on the subject of supplier selection.

2.1 Procedures for Determining Criteria The criteria used for evaluating and selecting suppliers depend on the procedures used for determining them. In this context it can be seen that the most frequently used source is consultation with experts (19 articles, 57.5%), either as a unique source (15 articles, 45.4%) or reinforced by a review of the available literature (4 articles, 12.1%). A detailed analysis shows that some articles described the methodology used, whereas others do not specify how the information was obtained. The experts may either be employees of the purchasing company or others who are familiar with the industry. The second most used source is the review of literature; 6 (18.2%) articles are used as a unique source as well as the previously mentioned case of 4 (12.1%) in

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conjunction with the experts. Not one article describes how the review was carried out. There is just one article (Ho et al, 2011) which describes a specific method, the QFD (Quality Function Deployment) which translates shareholders’ needs into criteria for supplier selection. There are 7 articles (21.21%) that do not specify the procedure used.

2.2 Identifying the Criteria for Obtaining the Panel The panel of suppliers is made up of those suppliers who have best satisfied the criteria of the purchasing company. These criteria can be grouped and ranked according to families. Analysis of the articles shows how each author opts for different ways of structuring them, only coinciding in one case. The present study uses the families proposed by Erdem and Göçen (2012), "Assets and Infrastructure, Costs, Logistics and Quality"; these authors propose an exhaustive classification obtained from reviewing the literature and interviewing experts. The criteria can also be grouped according to their typology: strategic, tactical and operational. Table 1 classifies the criteria of the articles according to their family and typology, taking each criterion as distinct (not counting the number of times it is repeated in different articles). Table 2 includes the repeats of each criterion, the number of times it is cited in the different articles. Table 1 Classification Family vs. Typology using distinct criteria

Family

Typology Strategic

Operational

Tactical

Total general

Assets and infrastructure

78

10

18

106

56.4%

Cost

7

20

4

31

16.5%

Logistics

1

9

7

17

9.0%

Quality

12

19

3

34

18.1%

Total general

98

58

32

188

100%

Table 2 Classification Family vs. Typology counting all repetitions

Family

Typology Strategic

Operational

Tactical

Total general


124

12

50

186

48.9%

Cost

12

37

23

72

18.9%

Logistics

1

13

35

49

12.9%

Quality

21

28

24

73

19.2%

Total general

158

90

132

380

100%

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Tables 1 and 2 show that a total of 380 criteria were mentioned, of which 188 are distinct. Detailed analysis of the distinct criteria shows a very disparate level of detail, some criteria being very generic (e.g. technique) and others which are more specific (e.g. the number of Rejected items at entry quality level). Regarding Typology, the most common are strategic criteria (98 criteria, 52.13%), although if the total number of articles citing them is taken into account the number drops (158 criteria, 41.58%). There are 32 criteria (17%) of a tactical nature, representing 34.74% of citations. Finally, there are 58 operational criteria (30.85%) which make up 23.68% of all citations. To determine the level of criteria standardization, the ratio between the number of citations and the number of distinct criteria is determined, resulting in: "Assets and Infrastructure" (1.75), "Cost" (2.32), "Logistics" (2.88) and Quality (2.15). The family with the highest number of criteria is "Assets and Infrastructure" with 1.75 citations per criterion. This is due to the fact that 75 of the criteria have only one citation; this family reflects the specific cases of the company concerned, leading to fewer repeated criteria. The other three families have fewer distinct criteria and higher levels of repetition, which indicates that their criteria are used by different authors; there is more consensus and a certain standardization. Table 3 shows the most mentioned criteria, a total of 11, which have 5 or more repeats, and which show a high degree of concentration, as the 11 criteria (5.85%) have a total of 123 citations (32.36%). Table 3 Relation of criteria with most citations Criteria

Total

Family

Delivery performance

21

Logistics

Price

20

Cost

Quality performance

19

Quality

Production capacity

16


General demand

10


Financial stability

8


Communication openness

7


Location

7


Transportation

5

Cost

Design capability

5


Quality management practices and systems

5

Quality

There are 156 criteria (82.97% of the total) that have two or more citations, representing 49.47% of the criteria of all the articles.

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2.3 Methods of Evaluating and Selecting Suppliers The methods used to evaluate and select suppliers are very diverse, and Table 4 includes a correlation of all those found in the analyzed articles and the total number of times each one has been used. Analysis of Table 4 shows that there is a great variety of methods, finding 25 different methods in a total of 35 articles. The principal ones are: Analytic Hierarchy Process (AHP) + mathematical programming (4 articles) and those based solely on mathematical programming (5 articles). A detailed study of those that include mathematical programming shows how the authors opted for different procedures and so, as each one is practically unique; there are 34 different methods and only one repetition. It can also be seen that 17 of the articles (48.6%) use the AHP or its variations (ANP, Fuzzy AHP, Fuzzy ANP). Table 4 Methods/procedures used to evaluate and select suppliers Methods/Procedures

Total

AHP (Analytic Hierarchy Process)

1

AHP + Mathematical Programming

4

AHP + CFPR(Consistent Fuzzy Preference Relations)

1

ANP (Analytic Network Process)

1

ANP + Mathematical Programming

3

ANP + TOPSIS+ Mathematical Programming

1

FAHP

2

FAHP + Mathematical Programming

1

Fuzzy AHP + Fuzzy TOPSIS + DEA

1

FANP

1

FANP + Mathematical Programming

1

DEA (Data Envelopment Analysis)

1

DEA + Decision Trees (DT) + Neural Network (NN)

1

Discret Choice Analysis (DCA)

1

Fuzzy logic

1

Grey ralational analysis (GRA)

1

Influence diagram + Fuzzy logic

1

MultiAlternative proposal

1

NN

1

Mathematical Programming

5

Stochastic Dynamic Programming (SDP)

1

Stochastic programming model (SP)

1

Weighted additive fuzzy programming

1

Supplier evaluation system (utilitza PROMETHEE)

1

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 4 (continued) Methods/procedures used to evaluate and select suppliers Methods/Procedures

Total

Vague sets theory

1

2.4 Objectives in Selecting Suppliers The selection of suppliers, in general, has the aim of determining a number N of suppliers and forming a panel of suppliers. An analysis of the current situation shows that the articles suggest different methods: Articles which recommend a ranking of suppliers (23 articles), normally in descending order according to their weight. In general the values of their weight show the degree to which each supplier satisfies the client’s needs. Their value is composed of the relative weight of the criteria for the client and the degree to which each supplier satisfies each criterion. Articles that classify the suppliers in binary fashion (3 articles), only including those who are suitable in the panel. The result of the selection is as follows: supplier selected/ not selected (Aksoy and Öztürk, 2011), supplier efficient /inefficient (Zeydan et al, 2011). Articles that propose different solutions to the anterior: 3.1. Articles that select suppliers without creating a panel (8 articles); directly assigning orders to the cloud of suppliers (Mendoza and Ventura, 2012), or obtaining a ranking which is not based on weight or binary classification; one example is the classification of suppliers according to their partnership consideration (Araz and Ozkarahan, 2007). 3.2. Two articles that analyze other aspects arising from the selection process: a comparison of the weight of criteria in different countries (Van der Rhee, Verma and Plaschka, 2009) and the analysis to determine whether the relationship with suppliers should be long or short term (Li, Murat and Huang, 2009).

3 Conclusions Purchasing management is strategic and supplier selection one of the most decisive processes. In this paper, a review of current thinking in selecting suppliers demonstrates the inexistence of a general model for determining the panel of suppliers, while showing a great diversity in the methods used for creating the panel.

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Each proposal is almost unique, with those articles that use the AHP or its variations standing out. There is no standardization in the criteria themselves nor in the ways of classifying or ranking them. In general, the criteria are determined in two ways: consultation with experts and reviewing the literature, and a detailed analysis shows the wide variety of procedures used. Therefore it can be stated that there is a lack of standards for determining and classifying criteria, which currently depends on the decision-maker’s experience. Almost all the articles deal with different industrial sectors (automobiles, electronics, …), and only one was found which dealt with the service sector (Feng, Fan and Li, 2011), presenting a method of decision making, in the case of an airline company, to solve the problem of supplier selection in subcontracting services. Future research works may include: (i) expand the scope of the review focusing on criteria and validate the lack of standards detected: (ii) implement the stages of supplier selection in the area of services.

4 References Aissaoui N, Haouari M, & Hassini E (2007) Supplier selection and order lot sizing modeling : A review. Computers & Operations Research 34 (12), 3516-3540 Aksoy A, & Öztürk N (2011) Supplier selection and performance evaluation in just-in-time production environments. Expert Systems with Applications 38 (5), 6351-6359 Amin SH, Razmi J, & Zhang G (2011) Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming. Expert Systems with Applications 38 (1), 334-342 Araz C, & Ozkarahan I (2007) Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics 106 (2), 585-606. Ben-David A, Gelbard R, & Milstein I (2012) Supplier ranking by multi-alternative proposal analysis for agile projects. International Journal of Project Management 30 (6), 723-730 Burke GJ, Carrillo JE, & Vakharia AJ (2007) Single versus multiple supplier sourcing strategies. European Journal of Operational Research 182 (1), 95-112 Chen YH, & Chao RJ (2012) Supplier selection using fuzzy preference relations. Expert Systems with Applications 39 (3), 3233-3240 Erdem AS, & Göçen, E (2012) Development of a decision support system for supplier evaluation and order allocation. Expert Systems with Applications 39 (5), 4927-4937 Feng B, Fan ZP, & Li Y (2011) A decision method for supplier selection in multi-service outsourcing. International Journal of Production Economics 132 (2), 240-250 Ferreira L, & Borenstein D (2012) A fuzzy-Bayesian model for supplier selection. Expert Systems with Applications 39 (9), 7834-7844 Gencer C, & Gürpinar D (2007) Analytic network process in supplier selection: A case study in an electronic firm. Applied Mathematical Modelling 31 (11), 2475-2486 Golmohammadi D, & Mellat-Parast M (2012) Developing a grey-based decision-making model for supplier selection. International Journal of Production Economics 137 (2), 191-200.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Ho W, Dey PK, & Lockström M (2011) Strategic sourcing: a combined QFD and AHP approach in manufacturing. Supply Chain Management: An International Journal 16 (6), 446-461 Ho W, Xu X, & Dey KD (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. European Journal of Operational Research 202 (1), 1624. Ho W, Xu X, & Dey KD (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. European Journal of Operational Research 202 (1), 1624. Huang SH, Keskar H (2007) Comprehensive and configurable metrics for supplier selection. International Journal of Production Economics 105 (2), 510-523 Kilincci O, & Onal SA (2011) Fuzzy AHP approach for supplier selection in a washing machine company. Expert Systems with Applications 38 (8), 9656-9664 Kirytopoulos K, Leopoulos V, Mavrotas G, & Voulgaridou D (2010) Multiple sourcing strategies and order allocation: an ANP-Augmecon meta-model. Supply Chain Management- an International Journal 15 (4), 263-276 Kokangul A, & Susuz Z (2009) Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount. Applied mathematical modelling 33 (3), 1417-1429 Lee AHI (2009) A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks. Expert Systems with applications 36 (2), 2879-2893. Li, L., & Zabinsky, Z.B. (2011). Incorporating uncertainty into a supplier selection problem. International Journal of Production Economics 134 (2), 344-356 Li S, Murat A, & Huang W (2009) Selection of contract suppliers under price and demand uncertainty in a dynamic market. European Journal of Operational Research 198 (3), 830-847 Lin RH (2009) An integrated FANP-MOLP for supplier evaluation and order allocation. Applied Mathematical Modelling 33 (6), 2730-2736 Lin CT, Chen CB, & Ting YC (2011) An ERP model for supplier selection in electronics industry. Expert Systems with Applications 38 (3), 1760-1765 Mafakheri F, Breton M, & Ghoniem A (2011) Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach. International Journal of Production economics 132 (1), 52-57 Mansini R, Savelsbergh MWP, & Tocchella B (2012) The supplier selection problem with quantity discounts and truckload shipping. Omega: The International Journal of Management Science 40 (4), 445-455 Mendoza A., & Ventura JA (2012) Analytical models for supplier selection and order quantity allocation. Applied Mathematical Modelling 36 (8), 3826-3835 Ng WL (2008) An efficient and simple model for multiple criteria supplier selection problem. European Journal of Operational Research 186 (3), 1059-1067 Van der Rhee B, Verma R, Plaschka G (2009) Understanding trade-offs in the supplier selection process: The role of flexibility, delivery, and value added services/support. International Journal of Production Economics 120 (1), 30-41 Shaw K, Shankar R, Yadav SS, & Thakur LS (2012) Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Systems with Applications 39 (9), 8182-8192 Toloo M, & Nalchigar S (2011) A new DEA method for supplier selection in presence of both cardinal and ordinal data. Expert Systems with Applications 38 (12), 14726-14731 Ustun O, & Demirtas E A (2008) An integrated multi-objective decision-making process for multi-period lot-sizing with supplier selection. Omega: The international journal of management science 36 (4), 509-521 Vinodh S, Ramiya RA, & Gautham SG (2011) Application of fuzzy analytic network process for supplier selection in a manufacturing organisation. Expert Systems with Applications 38 (1), 272-280

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Wu D (2009) Supplier selection: a hibrid model using DEA, decision tree and neural network. Expert Systems with Applications 36 (5), 9105-9112 Wu W Y, Sukoco BM, Li CY, & Chen SH (2009) An integrated multi-objective decisionmaking process for supplier selection with bundling problem. Expert Systems with Applications 36 (2), 2327-2337 Xia W, Wu Z (2007) Supplier selection with multiple criteria in volume discount environments. Omega: The International Journal of Management Science 35 (5), 494-504 Yücel, A, & Güneri AF (2011) A weighted additive fuzzy programming approach for multicriteria supplier selection. Expert Systems with applications 38 (5), 6281-6286 Zeydan M, Çolpan C, & Çobanoglu C (2011) A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications 38 (3), 2741-2751 Zhang D, Zhang J, Lai KK, & Lu Y (2009) An novel approach to supplier selection based on vague sets group decision. Expert Systems with Applications 36 (5), 9557-9563

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A “Collaborative Me” Crossroad: Individual Beliefs and the Adoption of Corporate Blogs Fernández-Cardador P1, Hernández-García A2, Iglesias-Pradas S3 Abstract Collaboration has become an essential process to improve business performance. Firms need to enhance innovation, and this is where 2.0 collaborative tools are expected to play a key role. Corporate weblogs are one of the main 2.0 tools which have raised more interest among managers, due to their ease of use and potential to bring together employees and partners who have to collaborate in order to achieve a common goal. However, individuals’ reactions to the use of such new systems may differ, which in turn might lead to rejection of corporate blogs. Thus, the objective of this exploratory research is to study the influence of individuals’ beliefs in the adoption of corporate weblogs; more specifically, the factors discussed in this research are self-efficacy, personal outcomes expectations and anxiety. In order to assess predictive ability for the exploratory research model, we have developed a theory grounded model, which has been validated with data from 70 employees from the Information Technology department of a large industrial Spain-based company. Findings from the results show that perceived usefulness is predicted by anxiety and personal outcomes expectation, perceived ease of use is predicted by blog anxiety, and behavioral intention to use corporate blogs is predicted by perceived usefulness.

Keywords: Corporate Blog, Technology Acceptance, Self-efficacy, Personal Outcomes Expectations, Computer Anxiety.

1

Pedro Fernández Cardador (e-mail: [email protected]) Universidad Politécnica de Madrid (PhD Candidate) 2 Ángel Hernández García (e-mail: [email protected], ) Departamento de Ingeniería de Organización, Administración de Empresas y Estadística Universidad Politécnica de Madrid Av. Complutense 30, 28040 Madrid 3

Santiago Iglesias Pradas (e-mail: [email protected]) Departamento de Ingeniería de Organización, Administración de Empresas y Estadística Universidad Politécnica de Madrid Av. Complutense 30, 28040 Madrid

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1 Introduction Collaboration is a fundamental process in knowledge creation and sharing which takes place through interaction among individuals. Collaboration is also one of the main drivers of change in organizations, and especially in knowledge-oriented organizations (Riemer and Frößler, 2007). According to Prahalad and Ramaswamy (2001), there is a strong link between collaboration within a company and firm’s profitability, and this also holds true when considering collaboration with other companies. However, adoption of collaborative technologies is not happening as fast as expected (Palen and Grudin, 2002). There are five major groups of characteristics influencing adoption of collaborative tools; these characteristics are related to the technology, individual, group, task, and context (Brown et al., 2010), respectively. In the mid-seventies, many technology adoption processes were failing due to fear of new technologies (Igbaria and Iivari, 1995) and doubts of employees about their own ability to use a new technology and obtain the expected results in return (Compeau and Higgins, 1995). In organizational contexts, these behaviors are user-specific, as different users have different needs depending on their role (Brown et al., 2010). Collaborative systems in corporate settings have undergone a radical change with the introduction of 2.0 tools, such as wikis and weblogs (Chen et al., 2007). Blogs allow readers and writers to express their opinions, offer different points of view and add new complementary knowledge (Wattal et al., 2009). In the early days of weblogging, their use was limited to personal journals; but later on, blogs began to receive significant attention as useful knowledge sharing tools (Chai and Kim, 2010) due to their potential to facilitate exchange of knowledge among people (Jackson et al., 2007) with a significant cost reduction (Yu et al., 2010). The fact that the beliefs which lead to adoption and rejection of technologies highly depend on intrinsic characteristics of the individual has not been previously addressed in the context of corporate blog adoption. Therefore, the main objective of this exploratory research is to study the influence of individual characteristics – namely, self-efficacy, personal outcomes expectations and anxiety– in the adoption of 2.0 collaborative tools –and, more specifically, in the adoption and use of corporate blogs–. The remainder of this paper is organized as follows: section 2 presents the theoretical framework and research hypotheses; research methodology, procedures and measures will be shown in section 3; section 4 will cover the data analysis technique and empirical results for the study, which will be followed by a discussion of results and implications for theory and practice in section 5.

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2 Theoretical Framework and Research Hypotheses The Technology Acceptance Model (TAM) (Davis, 1989) explains how and why individuals adopt and use a technology –in our case, corporate blogs–. According to Davis, an individual’s behavioral intention towards the use of a new technology is the best predictor of actual use. In TAM, behavioral intention is influenced by two beliefs: perceived usefulness and perceived ease of use; in this study, PU and PEOU refer to the users’ perception of their own performance when using corporate blogs and the degree to which a user believes that using a corporate blog is free of effort (Hsu and Lin, 2008), respectively. Applying TAM relations to the case of corporate blogs, we find that perceived ease of use (H1) and perceived usefulness (H2) positively predict intention to use corporate blogs, and also that perceived ease of use positively predicts perceived usefulness (H3). Anxiety is a generalized emotional distress (Nietzel et al., 1988) experienced by an individual. According to Bandura (1977), anxiety appears when individuals try to carry out behaviors they do not feel competent to perform. There are two kinds of anxiety: trait-based –i.e. personality– anxiety, and anxiety associated to a specific situation; computer anxiety falls into the second category, and may be defined as an irrational “generalized emotional distress experienced by an individual” when using or considering the use of computers (Igbaria and Iivari, 1995, p.592). Based on this concept, we have defined blog anxiety as the anxiety experienced by individuals when they perceive themselves to be underperforming at using corporate blogs. Previous studies found that computer anxiety causes computer use avoidance (Compeau and Higgins, 1995); following this rationale, we posit that blogging anxiety negatively predicts perceived usefulness (H4) and perceived ease of use (H5). Personal outcomes expectations refer to prospective rewards and/or improvements of perception of an individual’s image by other members of the organization (Compeau et al., 1999). This concept is based on the Social Cognitive Theory (Bandura, 1989), which states that an individual will engage in a behavior if he expects some kind of reward after performing it. We have adapted this concept taking into consideration that users may post in corporate blogs when they expect some pleasure –such as enjoyment–, organizational recognition or improvement of their image in return. Previous studies about outcomes expectations are inconclusive; for instance, Papadopoulos et al. (2013) found that people will continue to share information on the internet if they expect praise or rewards and Kankanhalli et al. (2005) found a positive relation between outcomes expectations and intention to use knowledge sharing systems, while Lu and Hsiao (2007) found that this relation was non-significant in the case of blogs. Given this lack of consensus, we will assess the nature of this relation in the case of corporate blogs, and therefore posit that personal outcomes expectations positively predict perceived usefulness (H6) and perceived ease of use (H7).

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Self-efficacy is a human regulatory mechanism which affects individuals’ judgments about their ability to perform a given task (Bandura, 1977). We will adapt this concept to our research context by defining blogging self-efficacy as the self-confidence in one's ability to collaborate using corporate blogs. Blogging self-efficacy emerges thus as a barrier for corporate blog adoption –i.e., if users believe that they are not able to use blogs, they will most likely be reluctant to collaborate with their community via corporate blogs–. Prior research has found that computer self-efficacy may be an antecedent of perceived ease of use (Agarwal and Karahanna, 2000). Moreover, previous studies have found that computer self-efficacy may increase personal outcomes expectations (Compeau and Higgins, 1995) and perceived usefulness (Liu, 2010). Empirical studies have also found a negative correlation between self-efficacy and anxiety (Sam et al., 2005) and other research has established that increasing levels of self-efficacy cause anxiety reduction (Dwyer and Fus, 2002). Taking all this into account, we find that blogging self-efficacy positively predicts perceived ease of use (H8), personal outcomes expectations (H9) and perceived usefulness (H10), and negatively predicts blogging anxiety (H11). Following the hypotheses presented in this section, the complete research model for this study is presented in Figure 1.

Fig. 1 Research Model

3 Research Methodology For this study, we have selected a sample of employees from a Spain-based large industrial company where 2.0 collaborative tools are currently being deployed as part of a plan to establish a new collaborative culture. Data were gathered via online survey during January and February 2013. Ninety employees from the IT department were invited to participate in this study, and 70 valid answers –70 percent from male and 30 percent from female respondents – were collected, for a total response rate of 77.8 percent. The Likert-7 scales used have been validated in prior literature, and were adapted to the context of corporate weblogs: bloganxiety scales were adapted from Heinssen et al. (1987); self-efficacy and person484


al outcomes expectations were taken from Kankanhalli et al. (2005); perceived ease of use and perceived usefulness are based on Davis (1989); scales for intention to use corporate blogs were adapted from Oum and Han (2011).

4 Data Analysis We used a partial least squares (PLS) technique in order to assess the structural model and the software used was SmartPLS 2.0M3 (Ringle et al., 2005). Since this was an exploratory research focused on prediction, PLS was chosen instead of covariance-based structural equation modeling (Hair et al., 2011). Besides, PLS does not need strict assumptions of sample size or measurement scales and allows using smaller sample sets. Item reliability was evaluated by observing the standardized loadings of latent variable indicators –all the indicators were defined as reflective–. Indicators with loadings not exceeding the ideal cutoff level of 0.7 (Nunnally, 1978) were dropped for subsequent analysis. Item reliability results are shown in table 1. A bootstrap resampling procedure was used to test the stability of the estimates, with significance values of p1 𝐷𝑠𝑡𝑙,𝑚 𝐿𝑇𝑙,𝑚 𝐶𝑝𝑐𝑙 , 𝑀𝐼𝑙 , 𝑇𝑃𝑟𝑖,𝑙 , 𝑇𝑆𝑖,𝑙 , 𝐸𝑅𝑖,𝑘 𝑈𝑃𝑖,𝑙 ,

𝑙 ∈ 𝑈𝑏, 𝑚 ∈ 𝑈𝑏 𝑙 ∈ 𝑈𝑏, 𝑚 ∈ 𝑈𝑏 𝑙 ∈ 𝑃𝑙 𝑙 ∈ 𝑈𝑏 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑃𝑙 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑃𝑙 𝑖 ∈ 𝑅𝑡, 𝑘 ∈ 𝐸𝑛 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑈𝑏

𝐷𝑃𝑖,𝑡,𝑙 , 𝑖 ∈ 𝑅𝑡 ∪ 𝑁𝑟, 𝑡 ∈ 𝑇𝑃 , 𝑙 ∈ 𝐶𝑙 𝑅𝐸𝑖,𝑡,𝑙 , 𝑖 ∈ 𝐸𝑛, 𝑡 ∈ 𝑇𝑃 , 𝑙 ∈ 𝐶𝑙 𝐼𝑃𝑖,𝑙,0 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑃𝑙 𝐿𝑙𝑃𝑖,𝑡,𝑙 , 𝑖 ∈ 𝑅𝑡 ∪ 𝑁𝑟, 𝑡 ∈ 𝑇𝑃, 𝑙 ∈ 𝑈𝑏 𝐶𝑃𝑖,𝑙 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑃𝑙 𝐶𝑆𝑖,𝑙 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑃𝑙 𝐶𝐼𝑖,𝑙 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑈𝑏

Planning periods Distance between l and m points Transport lead time to move products from l to m Processing capacity of l plant (in time units) Inventory capacity in location l (in product units) Processing time for a product i in plant l Set up time for a production of one lot of i product Returnable bottles k that are required for i product Association of a product with a specific location. It is a one when i product can be in the l location and cero in other wise External demand of i product, by the l client in t period

𝐶𝐷𝑖,𝑙 𝑖 ∈ 𝑃𝑑, 𝑙 ∈ 𝑈𝑏 𝐶𝑇𝑖 𝑖 ∈ 𝑃𝑑 𝐶𝐸𝑖 𝑖 ∈ 𝐸𝑛 𝑉𝑀𝑖,𝑙 𝑖 ∈ 𝑅𝑡 ⋃𝑁𝑟, ∀ 𝑙 ∈ 𝑈𝑏 𝐶𝑏𝑙 𝑙 ∈ 𝑈𝑏 𝑀 = ∑ 𝑖 ∈ 𝑅𝑡 𝐷𝑃𝑖,𝑡,𝑙

i returned bottles to the l client in t period Initial inventory of i product in l plant Programmed arrivals of i product to the l location in t period Unitary cost of produce an i product in l plant. Set up cost of produce a lot of i product in l plant Holding cost of an i product in the l location for one period. Deficit cost of a i product Unitary transport cost of i product by distance unit Cost of a i bottle Average of sales or dispatch of i product in l facility Coverture days of inventory in l facility Big value

𝑉𝑀𝑇𝑙,𝑚

Minimal volume transported between l and m

∪𝑁𝑟, 𝑙 ∈ 𝑃𝑙, 𝑡 ∈ 𝑇𝑃

𝑙 ∈ 𝑃𝑙, 𝑚 ∈ 𝐶𝑙

Decision variables about production volume, inventory levels, material flows, procurement and deficits are the following: 𝑃𝑖,𝑙,𝑡 𝑆𝑖,𝑙,𝑡 𝐼𝑃𝑖,𝑙,𝑡 𝐷𝑓𝑖,𝑙,𝑡 𝑇𝑟𝑃𝑖,𝑙,𝑚,𝑡 𝐸𝑛𝐶𝑖,𝑙,𝑡 𝑦1𝑙,𝑚,𝑡 , 𝑦2𝑙,𝑚,𝑡 𝑦3𝑙,𝑚,𝑡

Quantity of i product, made in l plant, in t period Binary variable to represent setup presence. Quantity of i product, stored in l installation, in t period Deficit quantity of i product, in l installation, in t period Quantity of i product, transported from l to m, in t period Quantity of i bottles, bought l in plant, in t period Continuous variables to represent discontinues constraints Binary variable used to represent discontinues constraints

Purposed model:

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Objective function, presented in equation 1, is total cost minimization, which results as sum of production, set up, inventory or deficit, forward and reverse transports and new bottles costs, respectively. The model, which integrates reverse logistics with production decisions, has constraints of capacity production, capacity storage of products and product flows among installations. There are two kinds of capacity constraints: in equation 2, the total time consumption for both production and setup is lower than capacity of each plant; and, in equation 3, total space of storage should be lower than available one; Setup presence is modeled with equation 4. In it we use big M number and a binary variable to represent the setup existence when there is a production volume. Flow product constraints were modeled with the 5 to 9 equations; those consider the flows among different levels of the supply chain and their respective transport lead time. Equation 5 represents flows between plants and their respective next level in the supply chain (see in figure 1); the sum of inventory on hand and production minus transported products to other installations is equal to final inventory in each period. Equations 6, 7 and 8 represent the intermediate levels of supply chain, for DCs, store controllers and distributors; and equation 9 shows the flows to final customers. In those flow continuity is guaranteed as the sum of inventory on hand at the start of period, previously programmed arrivals, arrivals of transported products from anterior supply chain levels, minus products dispatched to posterior supply chain levels (or demand) is equal to inventory or deficit at the final of t period. Reverse flow constraints are presented in equations 10 to 14. Equation 10 represents the flow of collected bottles between the customer and the previous level of the chain, so: sum of inventory on hand at start of a period, bottles received by the customer minus dispatched bottles to anterior levels is equal to final inventory; equations 11, 12 and 13 represent the intermediate levels of supply chain flows and equation 14 represents flows to the production plants. In those, sum of inventory on hand at start, previously shipped bottles, bottles that arrives from posterior levels of the supply chain, minus bottles dispatched to anterior levels is equal to final inventory; equation 14 includes the procurement of new bottles and their use in production system. Equation 15 associates bottles and finished products, it let to establish bottle consumption in the production process; Equation 16 is used to guarantee a safety inventory level, which depends of average sales. Equations 17 and 18 equations represent a discontinuous space for the flows between plants and a specific customers; flows between plants and customers should be bigger than a minimal parameter or cero and; equation 19 is used to give the value cero to forbidden flows. Type of variables constraints are in equations 20 to 22. It is possible to relax some of integer variables constraints to reduce calculating time.

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4 Conclusions and Further Research The model was tested in two instances composed by three plants, plant 1 and plant 2, which produce returnable bottled beverages and non-returnable bottled beverages and plant 3, which produces bottled water, in the first level; a DC used for non-returnable bottled products and water; two store controllers; two distributors and six customers. Moreover, six products were considered: products 1 and 2 as returnable bottled soda, 3 is a non-returnable bottled soda, product 4 is bottled water, products 5 and 6 are empty bottles for products 1 and 2, respectively It was possible to solve the aggregated planning problem for a supply chains with returns modeled; model that was, written and tested in MathProg language, shows global consistence with beverage bottled industry behavior, like was evidenced after testing it. The model let to formulate production, distribution and procurement (distribution of finished goods and collection of empty bottles), that minimize total cost. It is possible to include some different objectives in the future. The further research includes the integration of production planning with distribution in a more detailed manner, in the operational level. It is important to support making daily complex decisions like include heterogeneous fleet of vehicles, time windows for pickup and delivery and other situations. Other considerations can be the evaluation of the allocation of geographic areas to the different Supply Chain members, and the evaluation of product distribution and collect bottles using alternative transports. All of alternatives purposed have the objective to achieve global minimal. It is important to observe that, as a consequence of the real size of the system, it is required to evaluate strategies to solve them in a reasonable time.

3 References Andrew Makhorin. (2013). GNU Linear Programming Kit, Modeling Language GNU MathProg. Moscow, Russia: Department for Applied Informatics, Moscow Aviation Institute. Recuperado a partir de http://www.gnu.org/software/glpk/ Luiz M. M. Bettoni. (2010). GUSEK (GLPK Under Scite Extended Kit). Recuperado a partir de http://gusek.sourceforge.net/gusek.html#4 Paksoy, T., Bektaş, T., & Özceylan, E. (2011). Operational and environmental performance measures in a multi-product closed-loop supply chain. Transportation Research Part E: Logistics and Transportation Review, 47(4), 532-546. doi:10.1016/j.tre.2010.12.001 Pochet, Y. (2006). Production planning by mixed integer programming. New York ; Berlin: Springer. Safaei, A. S., Moattar Husseini, S. M., Z.-Farahani, R., Jolai, F., & Ghodsypour, S. H. (2010). Integrated multi-site production-distribution planning in supply chain by hybrid modelling. International Journal of Production Research, 48(14), 4043-4069.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Zhou, X., & Xu, J. (2009). A class of integrated logistics network model under random fuzzy environment and its application to Chinese beer company. International Journal of Uncertainty, Fuzziness & Knowledge-Based Systems, 17(6), 807-831.

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Neural Network Application for Risk Factors Estimation in Manufacturing Accidents. Carrillo JA1, Guadix J2, Grosso R3, Onieva L4 Abstract In occupational safety, when a neural network is trained, it is possible to predict the outcome given a combination of risk factors. Risk assessment is probably the most important issue in occupational safety. Risk assessment facilitates the design and prioritization of effective prevention measures. Neural network were applied for predicting the severity of accidents, which is an important to assess risks. Data sets were obtained from the official accident notifications in the manufacturing sector of Andalusia in 2011. The results confirm that neural networks are useful in risk factor estimation. Association analysis was used to identify the most important risk factors within the predicting variables. Diagnostic array analyses show that for preventive purposes it is better to use a reduced data set with a casecontrol approach in order to improve the specificity and the sensitivity.

Keywords: Neural Networks, Occupational Accidents, Risk Factors, Sensitivity Analysis, Manufacturing Sector

1Jesús Antonio Carrillo Castrillo ( email: [email protected]) Dpto. de Organización Industrial y Gestión de Empresas II. ETSI. Universidad de Sevilla. Camino de los Descubrimientos, s/n. Isla de la Cartuja, 41092, Seville, Spain. 2

José Guadix Martín ( email: [email protected]) Dpto. de Organización Industrial y Gestión de Empresas II. ETSI. Universidad de Sevilla. Camino de los Descubrimientos, s/n. Isla de la Cartuja, 41092, Seville, Spain. 3

Rafael Grosso de la Vega ( e-mail: [email protected]) Dpto. de Organización Industrial y Gestión de Empresas II. ETSI. Universidad de Sevilla. Camino de los Descubrimientos, s/n. Isla de la Cartuja, 41092, Seville, Spain.

4

Luis Onieva Giménez ( email: [email protected]) Dpto. de Organización Industrial y Gestión de Empresas II. ETSI. Universidad de Sevilla. Camino de los Descubrimientos, s/n. Isla de la Cartuja, 41092, Seville, Spain

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1 Introduction Occupational safety is a complex issue. The analysis of accidents deals with multiple causes and circumstances. In most cases, the accident occurrence implies multiple failures in the preventive and protective barriers (Reason 2000). Models of accident causation seek to explain the contribution of each risk factor. Most of research has been focused on determining causal relationships expressed as injury rates, relative risk, odds ratios or quantitative risk estimation. However, because of the socio-technical nature of accident causation, most of those models have little predictive ability. From a public policy perspective, the objective is to identify risk factors at the macro level. For Public Administrations the main concern is identifying intervention areas. At the same time, safety practitioners need an initial estimation for the risk assessment. Expected severity and likelihood of accidents based on the registered accidents in small and medium companies is not feasible due to the low rate of occurrence, and quantitative risk analysis is an expensive and time consuming alternative (Aneziris et al. 2010). Data mining is an interdisciplinary subfield of computer science focusing on the discovery of patterns in large data sets. Data sets of accidents are an excellent candidate to test if data mining techniques can provide meaningful information. Many data mining techniques are available, such as logistic regression, classification trees, chi-squared automatic interaction detection, among others (Bevilacqua et al. 2010). One of the most powerful tools for mining of complex data is using neural networks. In fact, when comparing the predictive ability of the different data mining techniques for risk analysis, neural networks show better results (Wang and Elhag 2007). Previous studies have used neural networks for different purposes such as for classification of industrial jobs in terms of the risk of low back disorders (Zuruda et al. 1997), for the prediction of occupational injury risk (Bevilacqua et al. 2010) or for prediction of the severity in traffic accidents (Delen et al. 2006). In occupational safety, when a neural network is trained, the outcome of a combination of risk factors can be predicted. Risk assessment may be considered the most important issue in occupational safety, used to facilitate the design and prioritization of effective prevention measures. Previous studies in the manufacturing sector of Andalusia (Spain) have shown that a number of individual worker characteristics can affect likelihood of occupational safety injuries (Carrillo et al. 2012) and in case of injury these characteristics also affect the severity of injuries (Carrillo and Onieva 2012). Prediction of the expected severity of accidents associated with certain exposure variables is a quantitative tool that identifies risk factors at the macro level. At the company level, depending on the prevention measures adopted, that initial estimation at the macro level may need to be modified according to the real work684


ing conditions. However, from a public policy point of view, the initial estimation of risk factors for the severity of accidents at the macro level is useful for designing effective intervention programs.

2 Data and Methods

2.1 Accident Data The Data used is from the accident notification database. Accident notification is mandatory for every accident with at least one day of absence from work. Data is coded according to the European Statistics on Accidents at Work Methodology – ESAW (ESAW). In every accident notification there are two separate types of variables from the prevention point of view: the variables of exposure (before the accident); and the variables of result (after the accident). Given the objective of this paper, to use the data to predict the possible accidents and their severity, we will only use exposure variables to train the neural network. Those exposure variables are presented in Table 1. Exposure variables are those not related to the accident occurrence or results. Because in the data set there is a very high proportion of slight accidents, an alternative data set was prepared using a case-control approach. In that approach, a sample of slight accidents is randomly selected. Therefore in the second data set there are a similar number of examples with slight and non-slight severity

2.2 Use of Neural Network for Severity Prediction The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes. Artificial neural network algorithms attempt to achieve good predictive ability with a low generalization error. During supervised error-back propagation training, input patterns are presented sequentially to the system along with the correct response. The network learns by comparing the targeted correct response with the actual response. This process is continued until all examples from the training set are learned within an acceptable error. Then the network is ready to operate in a feed-forward manner, attempting to classify accurately situations not encountered in training. In order to validate the usefulness of the network, examples with real output results are used. In modern software that process is integrated.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 Exposure (predicting) variables in the accident notification dataset: Categories and their distribution Variable

Categories

Abbreviation Number of examples

Sex

Male

S1

19.442

Female

S2

2.181

Spanish

N1

20.559

Foreign

N2

1.064

Young (less 25 years)

A1

7.804

Normal (from 25 to 54 years)

A2

9.116

Senior (more than 54 years)

A3

4.703

Non-manual

J1

621

Qualified manual

J2

16.513

Non-qualified manual

J3

4.489

E1

4.832

Medium (from 4 to 12 months)

E2

4.695

High (more than 12 months)

E3

12.096

Permanent

P1

11.656

Temporary

P2

9.967

Micro (less than 10 workers)

C1

4.508

Small (from 10 to 49 workers)

C2

8.385

Medium (from 50 to 249 workers)

C3

6.367

Big (more than 249 workers)

C4

2.363

Usual

WT1

20.987

Unusual

WT2

636

P1

18.868

Non-industrial

P2

2.755

Production

W1

15.636

Construction

W2

575

Agricultural

W3

71

Services

W4

300

Maintenance, auxiliary

W5

3.852

Transport

W6

451

Other

W9

738

Operating machines

A1

1.902

Working with hand-held tools

A2

4.061

Driving

A3

369

Handling objects

A4

7.276

Carrying by hand

A5

2.786

Movements

A6

4.550

Other

A9

679

Nationality Age

Job

Experience in company Low (less than 4 months)

Contract Company size

Workstation

Working Environment Industrial Work in process

Physical activity

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Finally, a separate set of real examples are used for querying. These are for testing the accuracy of the predictions of the trained network.

2.3 Neural Network Design and Learning Process Development The tool used in this paper allows the selection of networks with one, two or three hidden layers. Once the network architecture is set, the learning process can start. There are several controls for learning what needs to be set. As we want to avoid over fitting, the learning stops when the average validating error increases (Asensio-Cuesta et al. 2010). Other criteria for stopping are when average error is less than 0.01 or when 100% of the validating examples are within the 50% of the desired outputs.

2.4 Evaluation of the Predictive Ability of a Neural Network The main evaluation parameter for the predicting purpose of the neural network is the number of examples correctly classified. For that purpose, the best way of expressing the results is to use a diagnostic array (see Table 2). Table 2 Diagnostic array1 Real examples

Observed examples

True

True

False

True positive (TP)

False positive (FP)

False False Negative (FN) Results for a diagnostic array: Sensitivity: TP/(TP+FN) Specificity: TN/(TN+FP) Positive prediction: TP/(TP+FP) Negative prediction: TN/(TN+FN) Efficiency: (TP+TN)/(TP+FP+FN+TN)

True negative (TN)

1

In relation to the analysis of the risk factors, there are two important parameters for each variable: importance and sensitivity. Importance shows the sum of the absolute weights of the connections from the input node to all the nodes in the first hidden layer. Sensitivity indicates how much an output changes when the inputs are changed. The inputs are all set to the median values and then each in turn is increased from the lowest value to the highest value. The change in the output is measured as each input is increased from lowest to highest to establish the sensitivity to change. 687


3 Results

3.1 Neural Network Analysis Based on the Full Data Set The first analysis looks at associations between variables. This analysis offers a data mining initial pattern of the strength of the relationship between each pair of variables (see Table 3). In terms of risk assessment, variables that have strong association with the Severity outcome variable should be considered risk factors. For the full data set, the Severity output variable only has association with one predicting variable: Workstation. For the case-control data set, there is also association with Nationality. Table 3 Association rules Variable1

Variable2

Strength Full data set

Strength Case-control data set

Severity

Workstation

7.9

2.1

Severity

Nationality

--

1.6

3.2 Neural Network Analysis Based on the Full Data Set Two models were developed for the full data set, one with one hidden layer and the other with two hidden layers. Both of them include the eleven variables of exposure that are available. Errors and results are presented in Table 4 and diagnostic array in Table 5. Table 4 Neural networks based on the full data set Heading

Validating error

Validating OK Cycles

Hidden layers

Hidden Nodes

Model 1

0.28%

99.6%

1.000

1

6

Model 2

0.25%

99.7%

1.000

2

6+8

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 5 Diagnostic array for query examples of the neural networks based on the full data set Real outcome Predicted outcome Model 1 hidden layer Slight Severe Model 2 hidden layers Slight Severe

Slight

Severe

4983

14

0

3

4986

14

0

0

3.3 Neural Network Analysis Based on a Case-control Data Set Two models were developed for the case-control data set, one with one hidden layer and the other with two hidden layers. Both of them include the eleven variables of exposure available. Errors and results are presented in Table 6 and diagnostic array in Table 7. Table 6 Neural networks based on the case-control data set Heading

Validating error

Validating OK Cycles

Hidden layers

Hidden Nodes

Model 1

0.00%

86.2%

2.400

1

9

Model 2

0.93%

86.2%

2.560

2

9+6

Table 7 Diagnostic array for query examples of the neural networks based on the case-control data set Real outcome Predicted outcome Model 1 hidden layer Slight Severe Model 2 hidden layers Slight Severe

Slight

Severe

13

2

4

11

14

3

3

10

4 Discussion The neural networks were built with the variables that are available. Other risk factors such as the level of training, protection measures implemented or risk level of the task are not available. As previous researchers have proposed (Jacinto et al. 2009) the notification system in Europe should include other relevant data.

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The use of these neural networks to assess the expected severity of accidents for a set of exposure variables is a very useful practice and can provide safety practitioners with an initial estimation of the severity of the accidents for a group of tasks in the manufacturing sector. The results of the neural networks based on the two data sets are very different. In terms of efficiency, the full data set is higher, whereas in terms of specificity the case-control is more precise. From de preventive point of view, what really matters to safety practitioners understands the possible risk factors of severity, and for that purpose the case-control approach is more useful (Sorock and Courtney 1997). These neural networks can be easily applied by safety practitioners. Given the levels of the variables in a specific job based on the real data from the enterprise, it is possible to use trained neural networks based on the accidents notified to predict the severity of accidents. Ultimately, that initial estimation should be complemented with the analysis of the prevention measures and the working conditions in the risk assessment process in order to assess the risk of severe accidents.

5 References Aneziris O, Papazoglou I, Doudakmani O (2010). Assessment of occupational risks in an aluminum processing industry. Int J Ind Ergon 40(3): 321-329. Asensio-Cuesta S, Diego-Mas JA, Alcaide-Marzal J (2010). Applying generalised feedforward neural networks to classifying industrial jobs in terms of risk of low back disorders. Int J Ind Ergon 40(6): 629-635. Bevilacqua M, Ciaparica FE, Giacchetta G (2010). Data mining for occupational injury risk: A case study. Int J Reliab Qual Saf Eng 17(4): 351-380. Carrillo JA, Gómez MA, Onieva L (2012). Safety at work and worker profile: analysis of the manufacturing sector in Andalusia in 2008, in: Occupational Safety and Hygiene – SHO 2012. Arezes et al. Portuguese Society of Occupational Safety and Hygiene, Guimaraes: 116120. Carrillo JA, Onieva L (2012). Severity Factors of Accidents: Analysis of the Manufacturing Sector in Andalusia, in: Occupational Safety and Hygiene – SHO 2012. Arezes et al. Portuguese Society of Occupational Safety and Hygiene, Guimaraes: 111-115 Delen D, Sharda R, Bessonov M (2006). Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks. Accid Analys Prev 38(3): 434444. Jacinto C, Canoa M, Guedes Soares C (2009). Workplace and organizational factors in accident analysis within the Food Industry. Saf Sci 47(5): 626-635. Reason J (2000). Human errors: models and management. Br Med J 320: 768-770. Sorock, GS, Courtney, TK (1997). Advancing analytic epidemiologic studies of occupational injuries. Saf Sci 25(1-3): 29-43. Wang Y-M, Elhag THS (2007). A comparison of neural network, evidential reasoning and multiple regression analysis in modelling bridge risks. Expert Syst Appl 32:336348. Zuruda J, Karwowski W, Marras WS (1997). A neural network-based system for classification of industrial jobs with respect to risk of low back disorders due to workplace design. App Ergon 28(1):49-58.

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EN-04 Quality and Product Management

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Information Capability in Basque Country Quality Award Winners Zárraga-Rodríguez M1, Álvarez MJ2 Abstract Given the global environment that companies have to compete in nowadays, changes are so frequent that companies have to adopt a proactive attitude by trying to anticipate those changes. Using quality information while making decisions has become a critical factor for success, and nobody disputes the importance of having this quality information, which comes from the efficient use and management of information. Companies that have such quality information will have a competitive advantage and improve their results. Under the RBV theory, this efficient use and management of information could be considered a capability of a company. The aim of this paper is to explore the degree to which certain companies have developed this information capability. We focused the study on companies committed to Total Quality Management models because, due to the nature of these information intensive models, such companies can be expected to have developed information capability. The findings confirm this fact, although there are still opportunities for improvement.

Keywords: RBV, Information Capability, Information Practices, EFQM

1 Introduction Nowadays companies compete in a changeable word. It is essential that organizations be aware of trends in order to be ready for new situations and, even better, to anticipate them. In this scenario, having reliable and complete information is a key factor in making the right decisions. 1Marta

Zárraga Rodríguez ( e-mail: [email protected]) ISSA-School of Management Assistants, Universidad de Navarra. Cuesta de Aldapeta nº 49, 20009 San Sebastián.

2M.

Jesús Álvarez TECNUN, Universidad de Navarra. Pº Manuel Lardizabal, 13. 20018 San Sebastian.

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In order to obtain this quality information, the efficient use and management of information is critical, and its presence can be evidenced through a set of observable practices. In this study we present a list of information-related practices based on a literature review. Then we explore whether there are practices common to companies committed to TQM, which is considered an information intensive management system.

2 Framework and Objectives of the Study Companies need information when performing almost every activity, and it is a necessary input when making decisions at the operational, tactical and strategic level (Tee et al., 2006; Lin et al., 2007; Gorla et al., 2000; Wang, 2012). Information is a strategic company resource, just as human and financial resources are, but it is not always managed with the same degree of awareness and structure (Tee et al., 2006). Information can be seen as just a resource or as a capability. To the extent that the efficient use and management of information provides a competitive advantage to the company, the efficient use and management of information can be seen as a capability under the Resource Based View (RBV) organizational theory. The RBV organizational theory states that the key to the strategic success of a company lies not only in the environment but also in the resources the organization has and in the strategic use the company makes of them; that is, in its organizational capabilities. Resources alone don’t create value. A capability is a source of competitive advantage for the company that allows the generation of value and differentiation through the combined use of a series of resources (Peppard & Ward, 2004; Ashurst et al., 2008). We consider, therefore, that a company has information capability when the use and management of information is so efficient that it is a source of competitive advantage for the company. It is difficult to observe capabilities, but we can detect practices that evidence their presence. According to Ashurst et al. (2008), practices are more concrete and observable than capabilities, and they are described as a set of socially defined ways of doing things in order to achieve an outcome. To the extent that a practice is defined in terms of its outcomes, it is easier to demonstrate the success of the practice. The question becomes: what practices would be related to information capability as we have defined it?

694


2.1 Information Practices When defining information practices, we take as a reference the work by Marchand et al. (2000). They point out several information practices that are pooled into three major groups: practices related with the management of the information life cycle, practices related to the integration of information technology into day-to-day business, and practices where behaviours and values assumed by employees in relation to the use and management of information are shown. We also take into account proposals by other authors (Chou et al, 2007, Choo et al, 2006, Sabherwal & Chan, 2001, Carmichael et al. 2011, Coltman et al., 2010, Hwang, 2011, among others), and as a result we obtained a list of information practices that serve as evidence of information capability development (Table 1). We have assigned a code to each practice proposed, and we also show the expected outcomes of each practice in the table. Table 1 Information practices (* Key to outcome “Code”, ILCM: information life cycle management practice outcomes, ITI: information technology integration practice outcomes, AIBVC: assumed information behaviours and values convey practice outcomes ) Practice

Collect the information

Sense the information

Outcomes

Code*

Compilation of the information needed by stakeholders

ILCM1a

Compilation of information to collect from the environment and the inner workings

ILCM1b

Process for competitive and technology surveillance

ILCM2a

Process to anticipate problems with suppliers and partners

ILCM2b

Organize the information

Process to ensure that the information is available ILCM3

Process the information

Process to transform data into useful information

ILCM4

Maintain the information

Process to have updated databases

ILCM5

Disseminate the information

Process that ensure the distribution and exchange of information

ILCM6

Employ information technology to support daily operations

Daily operations supported by IT

ITI1

Management of business processes automated and integrated using IT

ITI2a

People management supported by IT

ITI2b

Interaction and relationships with stakeholders strengthened with IT

ITI2c

Employ information technology for business process support.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) Information practices (* Key to outcome “Code”, ILCM: information life cycle management practice outcomes, ITI: information technology integration practice outcomes, AIBVC: assumed information behaviours and values convey practice outcomes) Practice

Outcomes

Code*

Employ information technology for innovation support

Development and exchange of new ideas supported by IT

ITI3

Employ information technology for management support

Monitoring and analysis of internal or external business aspects supported by IT

ITI4

Anticipation of possible future scenarios supported by IT

ITI5a

Competitive and technology surveillance supported by IT

ITI5b

Exchange of information supported by IT

ITI6a

Document location automation supported by IT

ITI6b

Prevent manipulating or hiding information

Absence of handling information for personal gain

AIBVC1

Establish formal and reliable sources of information

Embedded formal and reliable sources of information used by organization’s members

AIBVC2

Transmit information about the performance of the company to all employees

Information about the performance of the company communicated to all employees

AIBVC3

Exchange of sensitive and non-sensitive information collaboratively among team components and between areas

AIBVC4a

Exchange of sensitive and non-sensitive information in a collaborative way with outside

AIBVC4b

Trust in each other

Failures discussions in an open and constructive manner and without fear of repercussions unfair

AIBVC5

Have concern with obtaining and applying new information

Quickly respond to changes and innovation promoted

AIBVC6

Employ information technology for strategy support Employ information technology for information sharing support

Exchange of sensitive and non-sensitive information collaboratively

The objective of this exploratory study is to know whether or not these practices are common practices in companies. We will focus on companies committed to Total Quality Management (TQM) because TQM is an information intensive management system (Matta et al., 1998). In this way, for instance, Fok et al. (2001) explored the relationships between TQM and information systems; they state that in order to implement quality systems successfully, an effective information system could be expected to be in place at the company. Thus it seems reasonable to expect that companies that have obtained quality awards have also 696


promoted information capability development and that information practices are actually common practices in these companies.

3 Research Methodology Our empirical study was carried out in the Basque Country, and participants were selected according to their commitment to quality management. This region in the north of Spain is the European region with the highest density of EFQM awards (Heras-Saizarbitoria et al., 2012). The data were collected via questionnaire. Items were presented as statements and respondents had to indicate their agreement on scale of 1 (strongly disagree) to 10 (strongly agree). The statements aim to measure the outcomes of the practices because this allows the success or the presence of the practices to be demonstrated. Statements were developed from a literature review and the instrument was tested by faculty members, senior managers and Euskalit members in order to make sure the items’ meanings were clear and that the questionnaire was easy to answer. (Euskalit is the Basque Foundation for Excellence, a private non-profit organization founded in 1992 by the Department of Industry and Energy of the Basque Government, which supports the policy of promoting the quality of the Basque Government). The final instrument contained three main sections: outputs of practices related to the management of the information life cycle (that is, the ILCM group), outputs of practices related to the integration of information technology in day-to-day business (the ITI group), and outputs of practices related to behaviours and values assumed by employees and displayed when using information (the AIBVC group). In the ILCM section, there were 8 statements related to 6 information practices, in the ITI section there were 10 statements related to another 6 information practices, and in the AIBVC section 7 statements were developed in relation to 6 additional information practices. The questionnaire was administered via a web page, which participants accessed with a link. The participants were contacted by Euskalit. The link to the questionnaire was sent to 292 companies that had received a quality award and 43 of them responded, which is a response rate of 15 per cent. The respondents were managers, who reported their agreement with each statement. The Basque Government provides quality awards according to the points obtained by the companies during external evaluation, which employs the scoring system used by the European Model of Excellence.

697


4 Results and Discussion Table 2 presents a summary of the scores given to each statement by the respondents, separated by section. All the means are between 6 and 8.5, which implies that a high level of information practices is commonly held. ̅) and deviation (σ) of the questionnaire scores Table 2 Quantitative results: mean (𝒙 ILCM1a

ILCM1b

ILCM2a

ILCM2b

ILCM3

ILCM4

ILCM5

ILCM6

x̅

8,05

7,42

6,47

7,00

7,49

7,40

7,42

7,56

σ

1,23

1,59

2,00

1,91

1,45

1,50

1,58

1,39

ITI1

ITI2a

ITI2ba

ITI2c

ITI3

ITI4

ITI5a

ITI5b

ITI6a

ITI6b

x̅

8,23

7,98

7,72

7,47

7,30

8,23

7,49

6,37

7,84

7,74

σ

1,07

1,22

1,49

1,71

1,49

1,00

1,50

1,84

1,19

1,35

AIBVC1

AIBVC2

AIBVC3

AIBVC4a

AIBVC4b

AIBVC5

AIBVC6

x̅

8,35

8,26

8,47

7,63

6,58

7,07

7,60

σ

1,54

1,20

1,47

1,48

1,88

1,74

1,40

Figures 1, 2 and 3 also deal with the results pooled into three groups, showing the level of agreement between the respondents and the presence of practice outcomes. Figure 1 displays the perceived level of practices associated with the management of the information life cycle (ILCM). Notice that the outcomes related to the practice defined as sense the information (ILCM2a and ILCM2b) are the ones with the lowest scores in this group. Interestingly, these organizations do not perceive the existence of competitive and technological surveillance processes when they are understood to be a key element in setting strategy. On the other hand, one of the outcomes related to the practice defined as collect the information has the highest score (ILMC1a), revealing that these kinds of organizations seems to be aware of the information that employees, customers, suppliers and other stakeholders need and they gather it systematically.

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Fig. 1 Mean scores for management of the information life cycle practice outcomes (ILCM)

Fig. 2 Mean scores for integration of information technology in day-to-day business practice outcomes (ITI)

Figure 2 displays the perceived level of practices related to the integration of information technology in day-to-day business. It can be observed that according to the scores these companies don’t seem to use information technologies (TICs) as support for competitive and technology surveillance (ITI5b), which is in accordance with the result pointed out in Figure 1. Moreover, higher scores correspond to the use of TICs to support daily operations, improving individual productivity and the use of TICs to facilitate process monitoring and indicator analysis. The use of TICs is, in general, an increasingly widespread practice in organizations and, in the case of the organizations that are committed to total quality and thus, must monitor the processes having an information system that is supported by new technologies is very helpful. Figure 3 displays the perceived level of practices that convey behaviours and values assumed by employees in relation to information use. According to the results shown in Figure 3, the free exchange of sensitive information in a collaborative way with people outside the organization (customers, partners, suppliers, society at large) is the set of practices with the lowest score (AIBVC4b). On the other hand, the higher scores obtained by the AIBVC1, AIBVC2 and AIBVC3 outcomes emphasize that these organizations value people sharing sensitive information rather than manipulating or hiding it, that they have formal and reliable sources of information that their members use and that information about the performance of the company is revealed to all employees in order to influence and direct individual performance and consequently the company’s performance.

699


Fig. 3 Mean scores for behaviours and values assumed by employees in relation with information use convey practice’s outcomes (AIBVC)

5 Conclusions As a general conclusion, we see that the companies analysed seem to have developed information capability to the extent that many information practices are perceived as common practices; this was to be expected since those companies were committed to Total Quality Management and have even won a quality award. Correctly applying the EFQM model involves establishing processes that must be under control by using the right indicators. The monitoring of the whole performance of the quality system would be allowed by using the appropriate indicators that have to be produced and updated. An information system designed by taking information capability into account would be the most suitable. The study has allowed areas of improvement to be identified by pointing out practices that, if they were commonly implemented, would improve the use and management of information and make it more efficient, which would be reflected in a company’s results. As for research limitations, the first one is that the questionnaires were answered by managers, which could have introduced a bias. Given that information flows throughout the company and involves everyone’s work, it would be better to know the perception of all the employees. The second limitation is the small size of the sample.

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6 References Ashurst C., Doherty N.F. & Peppard J. (2008) Improving the impact of IT development projects: the benefits realization capability model, European Journal of Information Systems, 17: 352370 Carmichael F., Palacios-Marques D. & Gil-Pechuan I. (2011) How to create information management capabilities through web 2.0, The Service Industries Journal, 31(10);1613-1625 Choo C.W., Furness C., Paquette S., van den Berg H., Detlor B., Bergeron P. & Heaton L. (2006) Working with information: information management and culture in a professional services organization, Journal of Information Science, 32(6):491-510 Chou T., Chan P., Cheng Y. & Tsai C. (2007) A path model linking organizational Knowledge attributes, information processing capabilities, and perceived usability, Information and Management, 44(4):408-417 Coltman T., Devinney T.M. & Midgley D.F. (2010) Customer Relationship Management and Firm Performance, Journal of Information Technology. This journal article is available at Research Online: http://ro.uow.edu.au/commpapers/768 Fok L.Y., Fok W.M. & Hatman S.J. (2001) Exploring the relationships between total quality management and information system development, Information & Management, 38: 355-371 Gorla N., Somers, T.M. & Wong B. (2010) Organizational impact of system quality, information quality, and service quality, Journal of Strategic Information Systems, 19:207-228 Heras-Saizarbitoria, I., Marimon, F. & Casadesús, M. (2012) An empirical study of the relationships within the categories of the EFQM model, Total Quality Management & Business Excellence, 23(5-6):523-540 Hwang Y. (2011) Measuring information behaviour performance inside a company: a case study, Information Research, 16(2), paper 480. [Available at http://InformationR.net/ir/162/paper480.html] Lin S., Gao J., Koronios A. & Chanana V. (2007) Developing a data quality framework for asset management in engineering organizations, International Journal of Information Quality, 1(1):100-126 Marchand D.A., Kettinger W.J. & Rollins J.D. (2000) Information Orientation: People, Technology and the Bottom Line, Sloan Management Review, 41(4):69-80 Matta K., Chen H.G. & Tama J. (1998) The information requirements of total quality management, Total quality Management and Business Excellence, 9(6):445-461 Peppard J. & Ward J. (2004) Beyond strategic information systems: towards an IS capability, Journal of Strategic Information Systems, 13:167-194 Sabherwal R. & Chan Y.E. (2001) Alignment between Business and IS Strategies: a Study of Prospectors, Analyzers, and Defenders, Information System Research, 12(1):11-33 Tee S.W., Bowen P.L., Doyle P. & Rohde F.H. (2007) Factors influencing organizations to improve data quality in their information systems, Accounting and Finance, 47:335-355 Wang W.T. (2012) Evaluating organisational performance during crises: A multi-dimensional framework, Total Quality Management and Business Excellence, 23(5-6):673-688

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Market Oriented New Product Development Process: a Case Study Nunes M1, Afonso P2 Abstract For many industries, the development of new products is the most important factor in sustaining the success once achieved. The emphasis on development of new products has spurred researchers from strategic management, engineering, marketing and other disciplines to study the process of new product development. In recent years, new product development (NPD) process became more strategic and market oriented. Market orientation is moving from the traditional market-driven to the new driving-market approach. Such approach asks for a different leadership of the NPD process, higher coordination amongst departments (marketing, sales, accounting and engineering areas) that may share common concerns, objectives and tools during the NPD process. While these changes often pose conflicting demands on the firm, there is a growing body of evidence that the firm may employ strategies to successfully meet their objectives. The conceptual framework presented in this article was tested through an exploratory case study developed in a manufacturer of refrigerators and other refrigeration equipment for domestic, commercial and professional use. Some findings were obtained from the analysis of the data. Essentially, market-driven and driving-market approaches are different in terms of customer and competitor orientation as well as inter-functional coordination.

Keywords: New product development, Market orientation, Case study

1Manuel

Lopes Nunes ( e-mail: [email protected]) Department of Production and Systems. School of Engineering. University of Minho. Campus de Azurém, 4800-058 Guimarães, Portugal. 2Paulo

Lima Pereira Afonso ( e-mail: [email protected]) Department of Production and Systems. School of Engineering. University of Minho. Campus de Azurém, 4800-058 Guimarães, Portugal.

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1 Introduction The role of the marketing function has evolved from only performing tactical marketing tasks to infusing a marketing capability into the organization’s core business processes (Jaakkola et al., 2009). Extensive research shows that the infused marketing function is an essential and natural part in the firms’ new product development (NPD) today (Lewis, 2001; Narver et al., 2004; Ellis, 2006). Some scholars hold the view that marketing function plays a positive role in NPD. Firms that are better at the market orientation-related activities have better innovation processes and greater success with NPD (e.g. Jaworski and Kohli, 2000; Song and Montoya-Weiss, 2001; Baker and Sinkula, 2005). This could be referred to as the market orientation’s influence on NPD in a firm. Simultaneously, some scholars defined NPD as the transformation of a market opportunity into a product as a result of the coupling of market assumptions with technological possibilities (Krishnan and Ulrich, 2001). Based on this, NPD becomes a complex and multifunctional process, including concurrent marketing, engineering, cross-functional working, advanced tools, early involvement etc. (Baker and James, 2005). The general perspectives of NPD are often stated to be R&D, marketing, and manufacturing (Kohn, 2006). Although market orientation and NPD has attracted considerable attention in the marketing literature, several important questions require further examination. Firstly, apart from the previous understanding of market orientation, some new concepts emerging in recent years, there is still no clear definition of market orientation and the existing statement of these concepts are abstract, therefore it is ambiguous how market orientation is carried out in NPD in a firm. Secondly, majority of prior research merely studies the relation between market orientation and NPD through quantitative research, such as negative or positive, direct or indirect relation. However, there is limited research on how market orientation affects NPD. Accordingly, this research is devoted to helping fill these two gaps, in other words, based on the previous research, authors will figure out how market orientation is carried out in NPD, besides, how market orientation affects NPD will also be explored.

2 Market Orientation Market orientation was first defined in literature as an organization-level culture comprising values and beliefs about putting the customer first in business planning (Kohli and Jaworski, 1990). Additionally, Some authors also emphasized that market orientation is the set of beliefs that puts the customer's interest (or understand the latent needs of customers) first (Deshpand. et al., 1993; Narver et al., 2004), while not excluding those of all other stakeholders such as owners, manag703


ers, and employees, in order to develop a long-term profitable enterprise (Deshpand. et al., 1993). Since then, market orientation has been studied both as a cultural phenomenon, and a set of behaviours and actives relating to (1) organizationwide market intelligence (covers both customers and competitors) generation through decision support systems, marketing information systems and marketing research efforts, (2) market intelligence dissemination within the firm, and (3) action-oriented responsiveness to the information (Gatignon and Xuereb, 1997; Deshpande, 1999). During the development of a market orientation, some scholars put the emphasis on certain perspective around cultural and behavioural approaches, e.g. they view the market orientation from a market information processing perspective. Hunt and Morgan (1995, p.11) define market orientation as: “(1) the systematic gathering of information on customers and competitors, both present and potential, (2) the systematic analysis of the information for the purpose of developing market knowledge, and (3) the systematic use of such knowledge to guide strategy recognition, understanding, creation, selection, implementation, and modification”. Meanwhile, in a recent study, some researchers stated market orientation as the process of obtaining information from the marketplace (customers, competitors, supply chain partners, and environmental trends), analysing and evaluating of market information, and using the information throughout the organization (take response of the information) (Jaakkola et al., 2009; Song et al., 2009). During the development of a market orientation, some scholars put the emphasis on certain perspective around cultural and behavioural approaches, e.g. they view the market orientation from a market information processing perspective. Hunt and Morgan (1995, p.11) define market orientation as: “(1) the systematic gathering of information on customers and competitors, both present and potential, (2) the systematic analysis of the information for the purpose of developing market knowledge, and (3) the systematic use of such knowledge to guide strategy recognition, understanding, creation, selection, implementation, and modification”. Meanwhile, in a recent study, some researchers stated market orientation as the process of obtaining information from the marketplace (customers, competitors, supply chain partners, and environmental trends), analysing and evaluating of market information, and using the information throughout the organization (take response of the information) (Jaakkola et al., 2009; Song et al., 2009). Nevertheless, to counter criticism that market orientation (conceptualized as being market-driven) was too reactive, both Jaworski et al. (2000) and Beverland et al. (2006) identified two forms of market orientation - market-driven and driving-market approaches. They proposed that firms that are truly market-oriented combine both approaches (Ibid). When utilizing a market-driven approach, businesses adopt a reactive stance and focus on trying to learn, understand and respond to stakeholder (customer, competitor, owners, managers and employees) perceptions and behaviour (Jaworski et al., 2000). Backman et al. (2007) stated that market-driven concept is aimed towards a certain customer group or business oppor704


tunity. In contrast, a driving-market approach involves proactive strategies that aim to change the structure of the marketplace or the rules of the game (Jaworski et al., 2000). Driving-market involves leading customers rather than evolving the offer in response to customers' on-going requests (Beverland et al., 2006). A company must have the imagination to envision markets that do not yet exist and the ability to stake them out ahead of the competition (Hamel and Prahalad, 1994). Organizations using a driving-market strategy in NPD do not only strive to meet customer needs but also search for products that pioneer new markets. Marketdriven approach would focus on evolutionary product changes driven by feedback from business buyers and end-consumers (Beverland et al., 2006). The strategy, market-driven and driving-market would both include a competitor focus, deriving ideas from the marketplace, and gaining access to distribution channels (Beverland et al., 2006). Besides, according to Kumar et al. (2000), a firm whose success has been based on radical business innovation indicates that such firms are better described as driving-market. While market-driven processes are excellent in generating incremental innovation, they rarely produce the type of radical innovation that underlies market-driving firms. Driving-market strategy entails high risk, but also offers a firm the potential to revolutionize an industry and reap vast rewards (Kumar et al., 2000). People may confuse about technology push and driving-market. It is necessary to clarify these two definitions and compare the differences between them. Technology push is a term used to describe a part of a business strategy of a firm. A technology push implies that a new invention is pushed through R&D, production and sales functions onto the market without proper consideration of whether or not it satisfies a user need (Mavondo et al., 2005). In the technology push view; technologists or scientists carry out research in their laboratories in order to create new knowledge. This new knowledge forms the basis for new products, processes or services that are then “handed over” to the rest of the organization to produce, sell and distribute. Technological advances push what goes into the marketplace (Whittington et al., 2007). Compared with the definition of driving-market, it can be seen that, driving-market focuses not only on searching for products that pioneer new markets, but also striving to meet customer preference. An innovation based upon market pull has been developed by the R&D function in response to an identified market need (Mavondo et al., 2005). Compared with the statement of driving-market and market-driven above, it can be seen that market-driven and driving-market are both market pull since they both promote the NPD in response to the market needs, either current or latent.

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3 How Market Orientation Influences NPD As Lafferty and Hult (2001) state, market orientation embraces four areas, when it comes to the research question, these four areas can be seen as four areas of how market orientation is carried out in NPD. Combining with NPD theories, these four areas will be reviewed with the connection of NPD. Meanwhile, as reviewed before, market orientation contains two approaches, market-driven and drivingmarket. Therefore, they share the same four areas with market orientation. Accordingly, in this part, market orientation’s effect on NPD related with four areas will be reviewed from market-driven and driving-market approaches.

3.1 Identifying Customers’ Needs Narver and Slater (1990) stated that the customer orientation element requires a sufficient understanding of the customer in order to create products or services of superior value for them. Recent work suggests that customers have a crucial role to play in understanding how and why innovation works. Close contact with customers and effective communications of their needs leads to a better understanding of the value of product features (Akgun et al., 2006). Besides, firms’ orientation towards customers is likely to influence how they respond to changes in the marketplace, in particular, the extent to which firms develop and introduce new products (Lewis, 2001). In market-driven approach, firms respond to environmental changes as they arise, but do not attempt to force change back into the environment (Narver et al., 2000). Even in those instances where latent needs are uncovered by the firm, there is still no active attempt to create or change behaviours among the customers (Narver et al., 2000). This kind of firms would not step outside the immediate voice of the customer and attempt to shape consumer preferences or modify them (Jaworski et al., 2000). For driving-market approach, market orientation includes development of capabilities in market sensing and customer linking (Day, 1994), which led to a deeper insight into customer’s both expressed and latent needs. Kohli and Jaworski (1990) also indicate that effective market intelligence involves not just current needs but also future ones. Driving-market approach requires the company has deep insight into the needs, lifestyles, and aspirations of today and tomorrow’s customers will (Hamel and Prahalad, 1994). Furthermore, firms using driving-market approach tend to change the rules of the “games”, or create new customers/ markets (Hamel and Prahalad, 1994).

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3.2 Collecting Information A firm’s capability of generating, disseminating and exploiting market information strongly influences NPD and its outcomes (Han et al. 1998; Langerak et al., 2007). Market-driven approach to NPD emphasizes close relationships with entities both internal and external to the organization in order to get information about customers’ needs and wants, competitors and changes in the market. Thus, a market-driven product development management emphasizes the significance of creating and exploiting market knowledge in designing and developing superior products (Srivastava et al., 1999; Kohli and Jaworski 1990). What’s more, market information processing capabilities and generative learning also permit to quickly identify and respond to changing customer needs (Baker and Sinkula, 2005). In order to develop the new product and make the NPD succeed, the organization needs to understand the strengths and weaknesses of its competitors, monitoring competitors' actions and investigate competitors’ supply chain partners (Laffery and Hult, 2001). For driving-market approach, as Jaworski et al. (2000) claim, this approach shares the similar perspectives with market-driven, but contains more from other sides. They stress the external activities, arguing that a firm using driving-market approach can reshape the value chain through eliminating players (deconstruction), adding players (construction) or by changing their functions (reconstruction) (Ibid). Firms using market-driving approach may also shape the behaviour of key factors such as customers or competitors by educating them or influencing their incentives and preferences (Ibid). For instance, Sarasvathy (2001) points out firms using driving-market approach may set up alliances and cooperate with their competitors.

3.3 Inter-functional Coordination Inter-functional coordination is the coordinated use of firm resources to create superior value for target customers (Narver and Slater, 1990). This coordinated integration draws on the information generated and through the coordinated use of firm resources, disseminates the information throughout the organization (Laffery and Hult, 2001). Moye and Langfred (2004) stated that sharing information among different departments might not only reduce different conflicts such as task conflict and relationship conflict but also create a common understanding. Moreover, argument shows that marketing and manufacturing strategies and design inputs should be closely integrated throughout the NPD effort (Narver and Slater, 1990). The technical community either did not understand the customers’ underlying needs or missed the appropriate price/performance target. Meanwhile, as many companies are becoming more market-oriented, their world-class competitors are 707


using advanced technology to create new businesses that few marketers could have imagined (Hamel and Prahalad, 1994). Neither technology nor marketing can be the sole departure point for creating new competitive space (Ibid). Consistent with Narver and Slater’s (1998) arguments that market orientation goes beyond being customer led, a firm’s competitor orientation and inter-functional coordination are positively associated with its NPD creativity (Wei and Wang, 2010). Creative new ideas and innovations usually come from interactions among people (Leenders et al., 2003). Therefore, technology and marketing need to be well coordinated within a firm. To blur organizational and career boundaries by ensuring that both communities had a large base of shared experiences. The result was potent mixture of market and technical imagination (Hamel and Prahalad, 1994). Integration leads to greater product design quality, where design quality is a holistic concept comprised of both product performance and conformance attributes (Swink and Song, 2007). The inter-functional coordination embedded in the market-oriented culture (Narver and Slater, 1990) also provides a unifying focus of creating superior value for customers (Baker and Sinkula, 2005) with a comparative impetus with competitors’ activities, and helps to achieve a holistic approach to NPD practices, thus improving new product performance (Langerak et al., 2007). The emphasis of inter-functional coordination differs for market-driven and driving-market approach. As to the former, Kohli and Jaworski (1990) stress the preference for market driven that it makes the marketing department take the responsibility of all departments in the organization. As the later, early manufacturing inputs can squelch creative ideas (Swink and Song, 2007), technology department plays much more important role in driving-market, successful market driving firms have developed a unique internal business system that offers customers a leap in the value proposition in terms of, for example, new price points or a superior service level (Kumar et al., 2000).

4 A Conceptual Framework of How Market Orientation is carried out in NPD In this part, based on the previous literature, a new conceptual framework of how market orientation is carried out in NPD (see Figure 1) is built up. This model will be used in the empirical part of the article. Following the model, authors will explicitly elaborate how the model is formulated and the interaction of different parts.

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Fig. 1 The conceptual framework of how market orientation is carried out in NPD

Lafferty and Hult (2001, p. 100) stated that four general areas constitute the basic foundation of market orientation which are (1) an emphasis on customers; (2) the importance of shared knowledge (information); (3) inter-functional coordination of marketing activities and relationships; and (4) being responsive to market activities by taking the appropriate action. First area is the emphasis on customers. As reviewed above, the cultural and behavioral approaches are the main streams in market orientation. Meanwhile, as Mavondo and Farrell (2000) noted, the cultural and behavioural approaches share the notion that the consumer is central in the manifestation of market orientation. Second area is the importance of shared knowledge (information). The information here contains customers, competitors, supply chain partners, and environmental trends information (Jaakkola et al., 2009; Song et al., 2009). Third area is the inter-functional coordination of marketing activities and relationships. Forth area is being responsive to market activities by taking the appropriate action. Narver and Slater (1990) considered that the inter-functional coordination is essential for market orientation. Gatignon and Xuereb (1997) and Deshpande (1999) put the emphasis on the action-oriented responsiveness to the information. The authors have the consensus opinion with Jaworski et al. (2000) that market orientation (conceptualized as being market-driven) was too reactive. Market orientation should contain two forms: market-driven and driving-market approaches (Ibid). These two approaches share the same four areas, but the content contained in each area is different. As mentioned above, market-driven and driving-market are different approaches to firms. That is to say, to answer the question, “how market orientation is carried out in NPD”, it is very important for a firm to choose one of them (either market-driven or driving market approach) before developing one specific new product. After choosing, the firm may follow the four general areas to implement NPD. The sequence of these four areas is related to the NPD process in which market orientation is carried out. Authors formulate a chainlinked process with feedback loops to describe the sequence and interaction of these four areas. The reason of adding feedback loops into the process is that when it comes to the taking action area, if the firms found that the information is insuffi709


cient, they could go back to the first area identifying customers’ needs. In order to help with in responding to how market orientation affects NPD, the authors formulated one tool (see Table 1). Table 1 Four areas’ effect on NPD related with driving market-driven and driving-market approaches Two approaches Four areas

Market-driven

Driving-market

Identifying

Emphasizes the feedback from customers and the response to customers’ current needs (Narver et al., 2000).

Emphasizes a deeper insight into both the expressed and latent needs of customers (Narver et al., 2000), and gives rise to new customers (Hamel and Prahalad, 1994).

Information based on the understanding of the strengths and weaknesses of firms’ competitors, and information from monitoring competitors' actions and investigating competitors’ supply-chain partners (Laffery and Hult, 2001).

Requires further information by shaping the behaviour of competitors (e.g. firms set the alliances, and cooperate with competitors) (Sarasvathy, 2001), and by changing the structure of industry (Jaworski et al., 2000).

Makes the market department take the responsibility for all departments in the organization (Kohli and Jaworski, 1990).

Technology department plays a much more important role (Kumar et al., 2000). Early manufacturing inputs could stifle creative ideas (Swink and Song, 2007).

customers’ needs

Collecting information

Inter-functional coordination

Taking action

All departments need to be responsive, such as designing, producing, promoting and distributing products (Kohli and Jaworski, 1990).

As stated above, market orientation contains two approaches, market-driven and driving- market. They share the four areas of market orientation. Nevertheless, the content of each area under two approaches is different. Therefore, when it comes to market orientation’s effect on NPD, each area’s effect on NPD should be explicitly stated under market-driven and driving-market approaches. Meanwhile, the each content in the table is concluded from the previous study. At the following discussion, authors will compare with the empirical data and further complete the contents of the table. In this study, the unit of analysis is the product.

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5 Case Study

5.1 Research Method This study is trying to figure out how marketing orientation is carried out in NPD and how marketing orientation affects NPD. Specifically, the indication of this research is to dig deeper into the relationship between market orientation and NPD. While a quantitative research is primarily aimed at providing statistical knowledge, enabling predictions, a qualitative research emphasizes a broader range of perspectives on complex interrelationships within a more limited number of empirical entities (Yin, 1994). Therefore, this study draws on a qualitative research. Considering the one single company of this study, Freeze Industry SA, it is pertinent to speak of a case study. Case study is an approach that helps in exploring a contemporary phenomenon in its real life context (Yin, 1994). Multi-case studies facilitate a deeper understanding of soft variables and key relationships and are believed to be particularly valid for uncovering business-marketing practices (Eisenhardt, 1989). However, multi-case studies are often facing a problem of dealing with the huge sum of the data, and decrease the possibility of having a deeper insight into the company (Yin, 1994). Connected with the topic, one case is a proper method to proceed since the limited time and the difficulty of collecting data. More importantly, one single case can strengthen the depth of the study and meet the objective of this paper. The selection of case is an important aspect when authors are developing theory (Eisenhardt, 1989). The case company was selected following a purposive sampling logic. Firstly, Freeze Industry SA is a small and medium enterprise that has its own marketing department and NPD department. Moreover, Freeze Industry SA used to develop new products based on market demand and its own innovative capability. Secondly, the CEO of the company is quite kind and generous. He is willing to do the research with authors, which will improve the reliability of empirical data. Thirdly, authors had the successful cooperation with Freeze Industry SA before. The project that related to Freeze Industry SA European market helped authors understand Freeze Industry SA and triggered authors’ interest to do further research with Freeze Industry SA. Finally, since Freeze Industry SA locates close to authors’ university, it is quite convenient to make the interview and get more complementary information, if needed. Data for this paper were obtained through two sources: primary and secondary data. Semi-structured interview, which offers the interviewee freedom and flexibility in answering question, was chosen to collect primary data (Bryman and Bell, 2007). According to Yin (1994), interviews will be the primary way, and it is one of the most important sources for a case study. Therefore, authors developed an interview guide based on the theoretical framework. The data was mainly obtained 711


from the interviewees with the Sales responsible, Marketing manager, I&D responsible and other managers. During the interview, authors share the work, one focuses on asking the question, recording and making the questions easier for interviewees, the other one pays attention to the body language and eye contact of the interviewees, making short notes as well as making sure that all questions are covered (Bryman and Bell, 2007). Besides, as the secondary data, the authors collected data from the firm’s official website, as well as from the news and reports about the company. After the interview, authors listen to the record several times and transcribe all the data onto thirteen pages, then authors break down the data, examine, compare, evaluate, conceptualize and categorize data, and discussed with each other, and then the data is compiled into four pages of text. Accordingly, authors analyse the empirical data combined with the literature. It is necessary to establish and assess the quality of research. Reliability and validity are the appropriate criteria for qualitative research (Bryman and Bell, 2007). To ensure high reliability and validity, the interview guide was simplified so that the interviewee can understand easily. Meanwhile, the interview guide was formulated according to the theoretical review and conceptual framework, and it is corresponding with the research question. Moreover, the company was willing to do the research with authors, which ensures the data that authors get can be highly reliable. In order to improve the reliability of data, authors transcribed and find the coherence of the data. In addition, the paper was returned to the company for examination. Consequently, the reliability and validity in this study can be considered as acceptable.

5.2 Company Description Freeze Industry SA is a Portuguese family company dedicated to the manufacture of refrigerators and other refrigeration equipment for domestic, commercial and professional use. Freeze Industry SA was started in 2008 and resulted from two firms with twenty years of experience which were leaders in their respective markets. Freeze Industry SA fulfils all of the demands included in the ISO 9001:2008 Standard for quality, and OSHAS 18001 for work safety, highlighting a high commitment to product and service quality as well as the well-being of all collaborators. This company aims to consolidate its leadership in the Portuguese market and distinguishing itself as one of the principal manufacturers of refrigeration products at European and World levels. Freeze Industry intends to be a reference in the refrigeration sector, through the recognition of its technical and service provision capacity. Technically, production flexibility and reduced delivery time are strong points in the service provided by the firm.

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The company’s strategy is focused on emerging markets, especially Africa, through the creation of conditions for direct distribution to their clients. It also focuses on commercial and professional refrigeration and the ever-increasing projection of its brand, Freeze, in the markets where it is present; particularly, in their main markets which are Africa, Europe and the Arab world. To support this strategy, new and modern facilities (namely a new production plant) were constructed in the North of Portugal. Recently, Freeze Industry SA concluded an investment of 22.6 million Euros to expand the production capacity. This expansion will allow the group to increase exportations, reinforce sales of its own brand and launch new brands in the market. This investment is part of an operational restructuring of Freeze Industry SA, which involved the closing of two factories, whose activity was transferred to the new facility. The two companies produced 150 thousand units per year and this new facility will produce between 640 to 650 thousand units per year.

5.3 Products The company produces chest freezers, combined refrigerators/freezers, refrigerators and upright freezers. Among others, the main products of this company are the following: chest and upright freezers, refrigerators, wine coolers and other cooling. The design of new products and a constant strategic market analysis are fundamental to support Freeze’s strategy. The company offers products recognised for their excellent value for money and technical service in the all markets were they are present in. This implies an intense effort in the development of solutions that are adapted to their clients’ needs and with performance characteristics that should fit the diverse and demanding clients around the world. On the other hand, beyond the common refrigerators and freezers, the company develops, produces and commercializes more sophisticated products such as wine coolers, refrigeration units for the pharmaceutical industry and commercial and professional refrigeration systems. Recently, the company is focus on chest freezers of high-energy efficiency. These new products should be recognized by their high-energy efficiency associated with design. For example, minimalist but sturdy lines influenced by the current tendencies are under development. All these are very innovative products developed to provide a vast array of solutions anticipating market demand.

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6 Analysis of Findings In this company, the Strategic Marketing Manager is responsible for the market analysis, competitor analysis, brand management and communication. According to him Freeze Industry SA is a company dedicated to the manufacture of refrigeration appliances for domestic, commercial and professional use with “a very large range of products like vertical refrigerators, chest freezers, upright freezers, ice cream chest freezers and wine coolers. We have product files of all categories”. In the case of Freeze Industry, their efforts to design a new innovative product of high-energy efficiency (an A+++ product) show how different the marketdriven and driving-market approaches are different. These differences are summarized in Table 2 and they can be expressed in the abovementioned three domains: customer orientation, competitor orientation and inter-functional coordination. Table 2: Findings summary

Identifying customers’ needs

Collecting information

Market-driven

Driving-market

(The traditional approach)

(The new A+++ product)

- Led by clients

- Led by Marketing department/CEO

- Through the eyes of clients and business partners

- Through direct data from consumers and from market studies - Technologically and strategically aligned

- Led by Sales department

- Led by Marketing department

- Using common suppliers and common clients to obtain information about competitors

- New sources of information are needed

- Using free available data - Led by I&D department Inter-functional coordination

- Reduced and late internal inter-functionality - Reduced clients’ and suppliers’ contribution

- Through a benchmarking exercise of the competitors - Leadership is not clear and it may be shared but I&D department remains central - The NPD process turns more complex with more and earlier contributions

6.1 Customer Orientation The company has a geographic segmentation with its main markets in Africa, Europe and Arab World. The firm segments its products-markets in these terms because these markets have needs that are completely different. Traditionally, Freeze Industry follows a market-driven approach. According to the Sales manager “pro714


duction system is very flexible permitting several product combinations” and they “are able to adapt easily their products to market needs”. Thus, their NPD has been essentially reactive and pushed by their clients’ suggestions and by client’s perceptions of customers’ needs. The firm makes some incremental improvements in their products - “usually the company reacts to the market” (C&D Responsible). Their clients have also suggested new product lines. For instance, “the client asked for a new line of products with 60 cm doors and we developed an entire line of these products” (C&D Responsible). Other examples can be given (e.g. a special line of small freezers). Nevertheless, the new product (an A+++ freezer) intends to anticipate market needs, clients requests and competitors solutions and it is pushed in a different manner. Firstly, this a new product aligned with strategic and technological objectives and the CEO putted it in the NPD agenda. Thus it is pushed by the inside of the company, the marketing department assumes the leadership in terms of costumer analysis and intends to collect direct data and to use information from market studies. It is a completely different approach.

6.2 Competitor Orientation Freeze Industry SA makes a regular estimation of competitors’ costs and product attributes through reverse engineering. Furthermore, they analyse competitors’ activities according to mutual suppliers and mutual customer’s information. Competitors’ strategies, technologies and market approaches recognized as cost-effective are analysed, particularly “competitors strategies and product technologies” (Strategic Manager). Strategic Manager stated that they “have a sales and marketing department with that responsibility. […] We purchase competitor new products to study their structure and technology. […] We have competitor monitorization in world shows and exhibitions”. According to the Strategic Manager, they consider this competitor information when making product/service decisions “very important for […] decisions [in terms of] costs and product structure. However, the driving-market orientation asks for a different approach, internally pushed and conducted. New sources of information are needed and consultants’ advice may be important. The company recognizes that they must collect information directly from their clients and that there is necessary a benchmarking exercise of the direct competitors. On the other hand they consider important to collect information on European and national programs for energy efficiency. The marketing department now conducts all this process.

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6.3 Interfunctional Coordination Finally, inter-functional coordination has been led by the I&D department because the NPD process is centred on the I&D department. Clients contribute in the beginning of the process with their suggestions and the “voice of the customer” and receive feedback just in the end of the NPD process (after product industrialization). Just a very few number of suppliers may contribute to the NPD (and those are usually moulding and materials suppliers). The other departments of the company collaborate in the end of the NPD process (after product development). Purchasing and production are asked to participate just in the product industrialization stage, before the first production series. Assuming a driving-market perspective, the leadership of the process is not clear and it may be shared. Nevertheless, the role of I&D department remains central. The NPD process turns more complex with more and earlier external and internal contributions, i.e. from suppliers and from the other departments. The CEO approval is very important and he should validate the initial production cost estimative. A target costing could be followed to deal with this augmented complexity but it is not a possibility in this case.

7 Conclusion Regarding how market orientation is carried out in NPD, the analysis shows that when the firm develops the new product, it follows four steps after choosing the market-driven or driving-market approach. These four steps are identifying customers’ needs, collecting the information, inter-functional coordination and taking action. These four steps move on sequentially. How market orientation affects NPD in the enterprise is explored from these steps towards two approaches. Under each step, the specific content in marketdriven product and driving-market product is different. For example, for the first step, identifying customers’ needs, the market-driven product requires the firm responding to customers’ feedback and monitoring customers’ current needs. While for the driving-market product, it needs the firm’s deeper insight into not only customers’ current needs, but also customers’ latent needs in order to create new customers. A number of managerial implications arise from the findings either NPD is market-driven or driving-market. Let this product follow the market trend or create new needs for customers are two options. After the company has chosen one of the two approaches, the way of how to perform market orientation needs to be considered, specifically, from identifying customers’ needs, collecting information, inter-functional coordination and taking action aspects. For market-driven product, the company puts the emphasis on meeting customers’ current needs, 716


monitoring competitors' actions. While for driving-market product, it requires the firm has a view of the future, to explore and create new needs of customers, to change the rule of the market, to invest much more on technology and when taking action, new distribution channel might need to be changed because of the totally new product. What’s more, for both market-driven product and drivingmarket product, information should be collected in a wide range (such as customers, competitors, the other industries, and different policies in the market) and well diffused among different departments in the whole organization, people in different departments should be well communicated in order to obtain the maximum cooperation. Future researchers might enlarge the research range of market orientation and NPD based on this research. They could do the research on comparison of market orientation and NPD in different firms. Each firm may have different characters of market orientation when they develop new products, do these characters relate with the industries’ features, or do they only depend on the product’s features? Are there some common characters of companies from one country, do they have similar market orientation performance in NPD? Therefore, one direction for future research could be conducted under a multi-industry or multi-culture background.

8 References Akgun, A.E., Lynn, G.S. and Cengiz, Y., 2006. Learning process in new product development teams and effects on product success: A socio-cognitive perspective. Industrial Marketing Management, 35 (2), pp. 210-224. Backman, M., Brjesson, S. and Setterberg, S., 2007. Working with concepts in the fuzzy front end: exploring the context for innovation for different types of concepts at Volvo Cars. R&D Management, 37, pp. 17-28. Baker, W.E. and James M.S., 2005. Market Orientation and the New Product Paradox. Journal of Product Innovation Management, 22, pp. 483-502. Beverland, M.B., Ewing, M.T. and Matanda, M.J., 2006. Driving-market or market-driven? A case study analysis of the new product development practices of Chinese business-tobusiness firms. Industrial Marketing Management, 35, pp. 383– 393. Bryman, A. and Bell, E., 2007. Business Research Methods. 2nd ed., Oxford University Press. Day, G.S., 1994. The capabilities of market driven organizations. Journal of Marketing, 58, pp. 37−52. Deshpande, R., 1999. Developing a market orientation. Thousand Oaks, CA: Sage Publications. Inc. Deshpand, R., Farley, J.U. and Webster, F., 1993. Corporate culture, customer orientation, and innovativeness in Japanese firms: a quadrad analysis. Journal of Marketing, 57, pp. 23-37. Ellis, P.D., 2006. Market Orientation and Performance: A Meta-Analysis and Cross-National Comparisons. Journal of Management Studies, 43 (5), pp. 1089–1107. Eisenhardt, K.M., 1989. Building Theories from Case Study Research. The Academy of Management Review, 14 (4), pp. 532-550.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Gatignon, H. and Xuereb, J.M., 1997. Strategic orientation of the firm and new product performance. Journal of Marketing Research, 36, pp. 77-90. Hamel, G. and Prahalad, C.K., 1994. Competing for the Future, Boston: Harvard Business School Press. Han, J.K., Kim, N., and Srivastava, R.K., 1998. Market orientation and organizational performance: Is innovation a missing link? Journal of Marketing Research, 62, pp. 30−45. Homburg, C., Grozdanovic, M., and Klarmann, M., 2007. Responsiveness to customers and competitors: The role of affective and cognitive organizational systems. Journal of Marketing, 71 (3), pp. 18−38. Hunt, S.D. and Morgan, R.M., 1995. The comparative advantage theory of competition. Journal of Marketing, 59, pp.1-15. Jaakkola, M., Santala, M. and Vassinen, A., 2009. Market orientation and business performance: the mediating effect of core business processes. International Marketing Trends Congress, January 16-17, pp. 1-22. Jaworski, B., Kohli, A. K., and Sahay, A., 2000. Market-driven versus driving markets. Journal of the Academy of Marketing Science, 28 (1), pp. 45−54. Kohli, A.K. and Jaworski, B.J., 1990. Market orientation: The construct, research propositions, and managerial implications. Journal of Marketing, Vol. 54 (2), pp. 1-18. Kohn, K. (2006). Managing the balance of perspectives in the early phase of NPD: A case study from the automotive industry. European Journal of Innovation Management, 9 (1), pp. 44-60. Krishnan, V. and Ulrich, K.T., 2001. Product development decisions: a review of the literature. Management Science, 47 (1), pp.1-21. Kumar, N., Scheer, L. and Kotler, P., 2000. From Market Driven to Market Driving. European Management Journal, 18 (2), pp. 129- 141. Lafferty, B.A. and Hult, G.T.M., 2001. A synthesis of contemporary market orientation perspectives. European Journal of Marketing, 35, pp. 92-109. Langerak, F., Hultink, E.J. and Robben, H.S.J., 2007. The mediating role of new product development in the link between market orientation and organizational performance. Journal of Strategic Marketing, 15, pp. 281 – 305. Leenders, R.T.A.J., Engelen, J.M.L. and Kratzer, J., 2003. Virtuality, Communication, and New Product Team Creativity: A Social Network Perspective. Journal of Engineering and Technology Management, 20, pp. 69-92. Lewis, M.A., 2001. Success, Failure and Organizational Competence: A Case Study of The New Product Development Process. Journal of Engineering Technology Management, 18, pp. 185–206. Mavondo, F.T. and Farrell, M.A., 2000. Measuring market orientation: Are there differences between business marketers and consumer marketers? Australian Journal of Management, 25, pp. 223-244. Mavondo, F.T., Chimhanzi, J. and Stewart, J., 2005. Learning orientation and market orientation, relationship with innovation, human resource practices and performance. European Journal of Marketing, 39, pp. 1235-1263. Moye, N.A. and Langfred, C.W. (2004). Information sharing and group conflict: Going beyond decision making to understand the effects of information sharing on group performance. International Journal of Conflict Management, 15 (4), pp. 381−410. Narver, J.C., Slater, S.F. and Maclachlan, D.L., 2004. Responsive and proactive market orientation and new-product success. Journal of Product Innovation Management, 21, pp. 331-347. Narver, J., Slater, N. and MacLachlan, D., 2000. Total Market Orientation, Business Performance, and Innovation. MSI Working Paper, pp. 100-116, Marketing Science Institute. Narver, J.C. and Slater, S.F., 1990. The effect of a market orientation on business profitability. Journal of Marketing, 54, pp. 20-35.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Narver, J.C. and Slater, S.F., 1998. Additional thoughts on the measurement of market orientation: a comment on Deshpande and Farley. Journal of Market Focused Management, 2, pp. 233-236. Song, M., Benedetto, C.A.D. and Parry, M.E., 2009. The impact of formal processes for market information acquisition and utilization on the performance of Chinese new ventures. International Journal of Research in Marketing, 26, pp. 314–323. Song, M. and Montoya-Weiss, M., 2001. The effect of perceived technological uncertainty on Japanese new product development. Academy of Management Journal, 44 (2), pp. 61–80. Srivastava, R., Shervani, T. and Fahey, L., 1999. Marketing, business processes, and shareholder value: An organizationally embedded view of marketing activities and the discipline of marketing. Journal of Marketing, 63, pp. 168-179. Swink, M. and Song, M., 2007. Effects of marketing-manufacturing integration on new product development time and competitive advantage. Journal of Operations Management, 25, pp. 203–217. Wei, Y.H. and Wang, Q., 2010. Making sense of a market information system for superior performance: The roles of organizational responsiveness and innovation strategy. Industrial Marketing Management, 40 (2) pp. 267-277. Yin, R.K., 1994. Case Study Research – Design and Methods. 2nd ed., Sage Publications.

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The Logical Framework Approach and Worker Commitment Paipa-Galeano L1, Jaca C2, Viles E3, Mateo R4, Santos J5 Abstract The main objective of this paper is to present the logical framework approach (LFA) as a tool that prepares companies and workers to implement continuous improvement programs. This methodology encourages worker participation in different steps in order to reach consensus in the organization. In addition, the application of LFA improves the capabilities of workers in areas such as participatory analysis, problem analysis and objectives analysis. These capabilities are necessary in any continuous improvement program. The paper also presents the results of applying LFA in two different companies.

Keywords: Participation, LFA, Improvement, Organizational Behaviour

1 Introduction Many companies believe that continuous improvement programs will enable them to survive in today’s climate by improving their performance and results (Prado1Luis Paipa-Galeano ( e-mail:[email protected]) University of La Sabana, Chía, Cundinamarca, Colombia. 2Carmen

Jaca ( e-mail: [email protected]) Department of Industrial Management, School of Industrial Engineers, TECNUN, Universidad de Navarra, Paseo Manuel Llardizábal, 13, 20018,San Sebastian, Spain. 3Elisabeth Viles ( e-mail: [email protected]) Department of Industrial Management, School of Industrial Engineers, TECNUN, Universidad de Navarra, Paseo Manuel Llardizábal, 13, 20018,San Sebastian, Spain. 4Ricardo Mateo ( e-mail: [email protected]) School of Economics and Business Administration, University of Navarra, Pamplona, Spain. 5Javier

Santos ( e-mail: [email protected]) Department of Industrial Management, School of Industrial Engineers, TECNUN, Universidad de Navarra, Paseo Manuel Llardizábal, 13, 20018,San Sebastian, Spain.

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Prado, 2009). Most current systems are based on the principles of the Toyota Production System, where one of the core principles is to facilitate the participation of workers and promote their autonomy (Hirano, 1989; Delbridge, Lowe, Oliver, 2000; Liker, 2004). In recent years, many authors have suggested that the key to the different methodologies and tools originated in Japan is that they are based on the participation and commitment of employees through training and behavioural change (Suárez-Barraza, Ramis-Pujol, Heras, 2010; Dahlgaard-Park, 2011). However, it was found that the application of improvement tools in the West focuses on operative aspects, leaving aside the aspects that have to do with change management and people (Ho, 1998; Douglas, 2002; Magaña-Campos and Aspinwall, 2003; Gapp, Fisher, Kobayashi, 2008; Kobayashi, Fisher, Gapp, 2008). Organizations commonly implement continuous improvement systems from top to bottom, where worker motivation and participation is usually considered to result from those improvement programs. However, it is necessary to have a strategy to support behavioural change in people (Jaca et al., 2012). In fact, getting employees to be involved in and committed to Western companies is an unresolved matter. According to the prestigious consulting firm Gallup, about 70% of U.S. workers are not committed to their work or are "actively disengaged" from their work, meaning they are emotionally disconnected from their workplaces and are less likely to be productive (Gallup, 2011). As a result, most of the workers' potential is wasted and with it, the opportunity to improve business results. These are the core principles of the continuous improvement methodologies: the autonomy of individuals and their participation in improvement through their own opinions and ideas. The objective of this paper is to present a tool used in donor organizations as a way to increase the involvement and motivation of employees in continuous improvement processes. Using this tool, which is called the logical framework approach, the organization focuses first on the analysis of environmental comfort and the development of the habits of the participants, and then improves processes and operations.

2 Environmental Comfort as Motivational Factor Over the past 35 years there has been a profusion of theories linking the workplace with levels of job satisfaction and worker motivation and stress (Björklund, 2001; Vischer, 2007). Several studies have shown that aspects such as spatial organization, architectural details and environmental conditions (order, cleanliness, ambient conditions and resources, spatial organization, architectonic details, and view or visual access from the work area), are associated with motivation, stress, per-

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formance and even social interaction at work (Burke, 1988; Sullivan and Bhagat, 1992; Leong and Furnham, 1996; Fairbrother and Warn, 203). As a result, some authors have coined the term environmental comfort, which links the psychological aspects of workers’ environmental likes and dislikes with concrete outcome measures, such as improved task performance, and with organizational productivity through workspace support for work-related tasks. Environmental comfort includes three categories: physical, functional and psychological comfort. Together these categories make the work environment stimulate workers so they will perform better as they carry out their tasks (Vischer, 2007). In recent decades, several studies have attempted to explain the factors that affect the success or failure of organizational change. Kristin Piderit (Piderit, 2000), for example, proposes a new way of understanding employee response to changes. The author maintains the idea that any change process needs both top-down and bottom-up work. Meanwhile, Hodgson (Hodgson, 2007) proposes that the development of an organization or a change in its strategy involves, even partially, the development of habits that are agreed upon by employees. The same author also stresses that the psychological mechanism of forming habits is something much more specific than what is commonly denoted as "organizational culture". Thus, he suggests the importance of focusing on processes of habit development as a way to address organizational changes more successfully. In order to establish a starting point for sustainable continuous improvements, it is necessary to first focus on identifying the needs and interests of individuals with regard to the workplace (environmental comfort) and then focus on improving processes and operations. To facilitate this process, we present a methodology, the logical framework approach, which is useful for promoting logical thinking and checking internal logic. The method also encourages people to consider what their expectations are, while also improving communication between people who are involved in the change (Aune, 2000).

3 The Logical Framework Approach Methodology The logical framework approach (LFA) is a widespread methodology, particularly in donor-assisted projects in developing countries (Aune, 2000; Dale, 2003). This methodology proposes a procedure for the planning of a development project. The different steps used by the LFA promote the participation of the different parties involved, based on the identification of problems in order to reach the proposed solutions. Thus, the methodology encourages participants to identify different visions regarding their particular interests, directives and resources that can be in favour of or against a proposal for a solution. Employees are then able to consider at the same time how the problems are perceived and the expected solution or re-

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sults. It is therefore ideal to create a shared vision from all stakeholders via consensus building (NORAD, 1999). This methodology has been adapted in order to encourage participation and consensus, as mentioned above. For this purpose, the steps have been tailored to focus on identifying and solving problems and concerns related to environmental comfort. Basically the adapted methodology applies steps adapted from LFA, following the sequence suggested by the methodology, which are the following (see Fig. 1):  Participatory analysis: Environmental comfort is analysed by the different people involved (workers, staff, supervisors, mid-level managers and directors, among others), according to Vischer’s model.  Problem analysis: This consists of identifying the cause-effect relationships between the major problems found in the participation analysis step, thorough the use of a ‘problem tree’. The objective of this phase is to be able to reach the root of the problems.  Objectives analysis: In the objectives analysis the problem tree is transformed into a tree of objectives (future solutions of the problems) and analysed. So, the group is able to identify the future desired situations in each of the comfort categories and identify the means-ends relationships that allow the desired situation to be reached.  Alternatives analysis: The purpose is to identify possible alternative options, assess their feasibility and agree upon the future desired solution. This is an exercise in creativity and idea generation.  Project planning: This consists of preparing and presenting the activities, resources and costs necessary to develop the proposal(s) for solving the problems. All the information is condensed into a single Logical Framework Matrix or LFM

Fig. 1 The Logical framework approach methodology, adapted from NORAD, 1999

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4 Application of the Logical Framework Approach in Two Different Companies The LFA was applied as part of an improvement program in two different companies as a first step toward making people aware of order and cleanliness in their workplaces. The characteristics of both companies are shown in Table 1 below. Table 1 Characteristics of the companies Company Activity

Location

Turnover

Nº employees

Participants

A

Manufacturing

Spain

15M €

120

24

B

Food and agriculture

Colombia

10M €

70

70

The application of LFA allowed us to analyse situations of discomfort that were not critical but that could be demotivating factors for employees. Such circumstances can act as a mental barrier for workers, creating a negative attitude towards organizational changes, sometimes even unconsciously. The LFA methodology brought to light these discomfort issues, and thus the employees were heard and valued by their managers. In turn, the workers’ attitude relaxed and they displayed a more positive attitude toward listening. In both situations, the application of LFA led to improvements related to environmental comfort, as evidenced in Tables 2 and 3, which includes some of the proposed improvements from the implementation of the Logical Framework Approach. The methodology not only encouraged employees to analyse the improvement opportunities, but also to propose and participate in the implementation of those improvements. Table 2 Example of improvements resulting from the application of LFA in Company A Area

Improvements proposed by employees

Maintenance

Improvements related to cleaning: Improved coolant leaks, cleaning program establishment and renovation of certain elements Repairs proposed: cranes, damaged glass in machines, heating system in plant Review of preventive maintenance guidelines: cranes, breakdowns reports

Machines

Improvements related to order: Painting of floor space, relocation of current materials, establishment of loading and unloading area Ergonomic study

Health and Safety

Management of safety: Safety audits, improve the use of PPE, create incidents collection system, reactivate the committee to study incidents and accidents, be educated about occupational risks Elements of prevention: Install emergency lighting, create per position plan, close engine cowling

Training

Create a competency management system, create a system of incentives for improvement proposals, create interdisciplinary teams for improvement

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 2 (continued) Example of improvements resulting from the application of LFA in Company A Area


Communication

Create shift sheet, train people in assertiveness and social skills, implement boards with production planning

Housekeeping

Put spacers in lockers, perform housekeeping study in shifts, distribute lockers

Table 3 Example of improvements resulting from the application of LFA in Company B Area


Logistics

Pre-order programming, programme conveyors at different times, systematic order platform Google map for location of farms

Processes

Create and communicate manual for office functions, worker training by function, define organizational chart Define processes and participants with systematic template, modify maintenance emergency procedures

Area


Human

Professional Development Plan, worker performance evaluation plan

Resources

Open lines of credit supporting vehicle replacement, promote social activities Social area for visitors

Corporate image

Promote the dissemination of corporate image with employees via incentives Establish routine exterior maintenance

Maintenance

Improved parts store, control maintenance plans, maintenance training

Health and Safety

Periodic training in risk prevention

As the above tables show, the proposed improvements will not only impact matters directly related to the environmental comfort of workers. This methodology has led to proposals and actions related to the productivity and performance in both companies.

5 Conclusions The application of logical framework approach combined with Vischer’s comfort model is designed to promote the participation of people by attending first to their needs and then to the overall improvement of the process. We argue that the employee's attitude is influenced by his perception of his work, and this perception acts as an input for personal participation and motivation. The proposed methodology is based on organizational change management, which is founded on continuous improvement tools, and organizational behaviour principles, which is pro725


posed as a way of addressing improvement in an organization. Once the employees have had the opportunity to analyse and improve the aspects related to their comfort, the program focuses on improving processes and operations. The following benefits are expected from applying LFA: a) Putting the organization on the path of continuous improvement b) Increased employee morale by improving environmental comfort in its three dimensions: physical, functional and psychological. c) Reduction of absenteeism and staff turnover by improving environmental comfort in all three dimensions. d) Increased involvement in the organization by engaging employees in the identification and resolution of problems from building consensus and a shared vision. e) An increase in productivity through the development of training programs oriented toward changing people's behaviour. The application of this methodology in both companies shows that LFA is a useful tool for fostering the commitment of workers by aligning their needs and complaints with those of the company where they work.

6 References Aune JB (2000) Logical Framework Approach and PRA - mutually exclusive or complementary tools for project planning?. Development in Practice, 10(5), 687-90. Björklund C (2001) Work Motivation - Studies of its Determinants and Outcomes, Stockholm School of Economics. Burke RJ (1988) Sources of managerial and professional stress in large organisations. Causes, Coping and Consequences of Stress at Work. C. L. Cooper and R. Payne. Chichester: John Wiley & Sons. Dahlgaard-Park SM (2011) The quality movement: where are you going?. Total Quality Management, 22(5), 493-516. Dale R (2003) The logical framework: An easy escape, a straitjacket, or a useful planning tool?. Development in Practice, 13(1), 57-70. Delbridge R, Lowe J, Oliver N (2000) Shopfloor responsibilities under lean teamworking. Human Relations, 53(11), 1459-79. Douglas, A. (2002) Improving manufacturing performance, Quality Congress. ASQ's Annual Quality Congress Proceedings, (56), 725-32 Fairbrother K, Warn J (2003) Workplace dimensions, stress and job satisfaction. Journal of Managerial Psychology, 18(1), 8-21. Gallup (2011) Majority of American Workers Not Engaged in Their Jobs. Available at: http://www.gallup.com/poll/150383/majority-american-workers-not-engaged-jobs.aspx%60 Accessed on 12/12. 2012. Gapp R, Fisher R, Kobayashi K (2008) Implementing 5S within a Japanese context: an integrated management system. Management Decision, 46(4), 565-579. Hirano H (1989) JIT Factory Revolution. Cambridge: Productivity Press. Ho SKM (1998) 5-S practice: a new tool for industrial management. Industrial Management & Data Systems, 98(2), 55-62.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Hodgson GM (2007) Institutions and Individuals: interaction and evolution. Organizational studies, 28(1), 95-116. Jaca C, Santos J, Errasti A, Viles E (2012) Lean thinking with improvement teams in retail distribution. Total Quality Management & Business Excellence, 23(4), 449-465. Kobayashi K, Fisher R, Gapp R (2008) Business improvement strategy or useful tool? Analysis of the application of the 5S concept in Japan, the UK and the US . Total Quality Management & Business Excellence, 19(3), 245-262. Leong CS, Furnham A (1996) The moderating effect of organizational commitment on the occupational stress outcome relationship . Human Relations 49(10): 1345-1363. (1996)., 49(10), 1345-1363. Liker JK (2004) The Toyota Way: 14 Management Principles from the World's Greatest Manufacturer. New York: McGraw-Hill. Magaña-Campos J, Aspinwall E (2003) Comparative study of Western and Japanese improvement systems, 4(4). NORAD (1999) The Logical Framework Approach (LFA): handbook for objectives-oriented planning: NORAD: Norwegian Agency for Development Cooperation. Piderit SK (2000) Rethinking resistance and recognizing ambivalence: a multidimensional view of attitudes toward an organizational change. Academic of management Review, 25(4), 783794. Prado-Prado JC (2009) Continuous improvement in the supply chain. Total Quality Management & Business Excellence, 20(3), 301-309. Suárez-Barraza MF, Ramis-Pujol J, Heras MA (2010) Reflecting upon Management Systems: Content analysis and synthesis, 1(2), 64-86. Sullivan SE, Bhagat RS (1992) Organizational stress, job-satisfaction and job-performance Where do we go from here? Journal of Management, 18(2), 353-374. Vischer JC (2007) The effects of the physical environment on job performance: towards a theoretical model of workspace stress. Stress and Health, 23(3), 175-184.

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How to Choose the Best Order when Implanting HIWP in Operations Area Marin-Garcia JA1, Perello-Marin MªR, Canos-Daros L, Valero-Herrero M Abstract The aim of this paper is to provide a general methodology to help choosing the set of practices in the field of HR management in the area of operations (practices known as High involvement work practices) that will lead to the desired mix of operational performance according to the previous state of the organization (i.e. the practices it has already implanted). The results presented come from data of the third tear suppliers in the Spanish automotive industry.

Keywords: High-Involvement Work Practices, Evolution, Management innovation.

1 Introduction In a world where global competitiveness is one of the main keys to organizations’ success; where innovation, flexibility, responsibility and cooperation become particularly relevant to ensure organizational success, or even mere survival, the importance of human capital, as a source of competitive advantage, is gathering especial significance. It is becoming increasingly frequent, the introduction of new management practices to the organization, seeking to enhance performance, as a form of Management Innovation (MI) (Perello-Marin et al. 2013; Paauwe and Boselie 2005). This is so because such practices are usually difficult to replicate exactly from one company to another, provided they are well rooted in the daily work in the organi1Juan

A. Marin-Garcia ( e-mail: [email protected]) ROGLE-Departamento de Organización de Empresas. Universitat Politécnica de Valencia. Camino de Vera s/n. 46022 Valencia.Spain. * This paper has been partially supported by the project "CORSARI MAGIC DPI2010-18243" by the Ministerio de Ciencia e Innovación del Gobierno de España within the Program de "Proyectos de Investigación Fundamental No Orientada" and project TIN2008-06872-C0402/TIN

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zation, or in other words, they are part of their own identity (Thang et al. 2007) (Mol and Birkinshaw 2009). If we look at other resources as a source of competitive advantage, different HR, we can state that they are becoming more accessible and easy to copy, and therefore, ephemeral sources of competitive advantage, which does not happen with complex social systems {. This paper deals with Human Resource Practices (HRM practices) geared towards improving organizational effectiveness and hence better performance outcomes, as opposite to traditional HR practices. Selection and implementation of those programs and practices have been extensively studied by the body of research called “strategic human resource management” (SHRM). Within these papers, myriad of programs and practices in HRM to be implanted for the firms to increase its performance can be found; most of them from the perspective of individual practices or on the other way around, as a whole system of practices (without a clear identification of its composition). The pioneer studies appear twenty years ago. There is quite a lot of literature, since then to date, dealing with the relationship between HRM practices and improving organizational performance. Some of the paper have focused on aspects such as market value, financial performance , profitability, operational measures of performance or productivity, social climate and culture or turnover. We have found that an increasing body of work contains the argument that the use of certain practices (including comprehensive employee recruitment and selection procedures, incentive compensation and performance management systems, and extensive employee involvement and training) can improve the knowledge, skills, and abilities of a firm’s current and potential employees, increase their motivation, reduce shirking, and enhance retention of quality employees while encouraging nonperformers to leave the firm. These practices can be referred differently in the academic literature as for instance, “high-performance work practices”, “high-involvement work practices”, “high commitment practices” or “innovative human resource practices or best practices”, depending on the author. Each term has little nuances that distinguish each other, but most of the authors agree with the fact that when business capabilities are combined with employees motivation, the resulting organization value is not a sum of its parts, but a multiplication (Ordiz Fuertes 2002; Combs et al. 2006; Guest et al. 2004). In this paper, we study, as the engine of evolution and change, the introduction of tools and practices that are new to a particular organization and intended to enhance its performance and success. We specially focus on practices at the operational level that firms implant to enhance performance and hence change from one form of organization to another.There are many studies already published dealing with the adoption of practices and tools at this level that make organization to evolve from forms as for instance ‘ancient manufacture system’ to other more efficient as ‘mass producer’, ‘flexible manufacturing’ or ‘lean producer’ (Akdere 2009; Albors and Hervás 2006; Anand and Kodali 2008; Collaine et al. 2002; Doolen and Hacker 2005; Herron and Braiden 2006; Hipple 2005; Marin-Garcia 729


et al. 2011; Mol and Birkinshaw 2009; Pavnaskar et al. 2003).Scholars and practitioners, alike, affirm that when organizations implant certain tools and practices looking for a competitive advantage, not always achieve success on it. Moreover, some practices succeed in one organization but fail in another, although they were similar organization in comparable environments (Baxter and Hirschhauser 2004; Bayo-Moriones et al. 2008; Corso et al. 2007; Doolen and Hacker 2005; GarciaSabater et al. 2011). But, when analyzing the reason of success or failure in implementation of tools and practices, we have found that there is no consensus by scholars. The aim of this paper is to provide a general method to help choosing the set of practices that will lead to the desired mix of operational performance according to the previous state of the organization (i.e. the practices it has already implanted). We thus try to shed some light to the decision making process when implanting HIWP by presenting a tool that can helps us to choose the order in with practices are to be implanted. In doing so, we have used data from the third tear suppliers in the Spanish automotive industry. We specially focus on High Involvement Work Practices (HIWP). We do not try to explain the cause of success or failure on the selection of HRM practices, but introduce a methodology to help in the decision making process to choose an additional practices to be implanted according to the pre-defined success criteria of the organization.

2 HIWP as Human Resources Practices in Area of Operations Within the field of human resource management, selection and implementation of programs and practices have been widely studied. The pioneer studies appear twenty years ago. There is quite a lot of literature, since then to date, dealing with the relationship between HRM practices and improving organizational performance in different sectors. In this work, we have gone through the literature of human resource management and related to improve organizational performance by enhancing employee commitment and motivation, looking for the most commonly used HR practices. We have focused only in high involvement practices, high commitment practices, or innovative HR practices, that lead to better performance, but not in traditional Human Resources practices. A previous examination of the literature concluded by a series of interviews with managers involved in the third tier automotive industry identified on one hand the most common HIWP in terms of increasing organizational and operational performance (see table 1), and on the other hand, six dimensions of the operational performance in those organizations: Quality, Cost-efficiency, reliable-delivery, absenteeism, voluntary turnover and productivity.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 HRM Practices Category

Practice

Empowerment

PART1. Suggestion system: A program that elicits individual employee suggestions on improving work or the work environment PART2. Survey feedback: Use of employee attitude survey results, not simply as an employee opinion poll (in motivation, satisfaction, training needs and expectations), but rather as part of a larger problem solving process in which survey data are used to encourage, structure, and measure the effectiveness of employee participation PART3. Job enrichment or redesign: Design of work that is intended to increase worker performance and job satisfaction by increasing skill variety, autonomy, significance and identity of the task, and performance feedback PART4. Quality circles: Structured type of employee participation groups in which groups of volunteers from a particular work area meet regularly to identify and suggest improvements to work-related problems. The goals of QCs are improved quality and productivity, there are no direct rewards for circle activity, group problem solving training is provided, and the groups’ only power is to suggest changes to management. PART5. Employee participation groups other than quality circles: Any employee participation groups, such as task teams or employee work councils, which do not fall within the definitions of either self-managing work teams or quality circles. Usually these groups are formed by personnel from different departments or even different level. Its mission is also to make suggestions for improvement but with a broader scope. PART6. Mini-business units: Relatively small, self-contained organizational unit (perhaps smaller than the plant level) that produces its own product of service and operates in a decentralized, partly autonomous fashion as a small business. PART7. SeIf-managing work teams: Also termed autonomous work groups, semi-autonomous work groups, self-regulating work teams, or simply work teams. The work group (in some cases, acting without a supervisor) is responsible for a whole product or service, and makes decisions about task assignments and work methods. The team may be responsible for its own support services such as maintenance, purchasing, and quality control and may perform certain personnel functions such as hiring and firing team members and determining pay increases.

Reward

Comp1. Individual bonus based on skills and/or knowledge: employees have a base salary plus an additional amount based on the amount of jobs he or she can develop, or on his or her level of training. Comp2. Share of profits of the organization: employees receive a certain amount of money as a function of the profits of the organization. Comp3. Share of profits based on suggestions made (Gainsharing, Scanlon…): The employee or employees perceive abonus proportional to the savings achieved by improvements in productivity, quality or cost reduction. Comp 4. Individual Bonus based on individual goals: employees perceived an extra amount in their salary for achieving certain short-term objectives or goals.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 1 (continued) HRM Practices Category

Practice Comp5. Group bonus based on achievement of goals. Comp6. Non-monetary awards related to performance: congratulations, employee of the year, company awards… Comp7. Participation in the capital of the company: the employee perceives as a part of the reward a certain amount of shares of the company’s capital. Comp8. Flexible remuneration: the employee decides how to perceive the extra salary. The most common alternatives are: in cash, through training, travels, social benefits, extra vacations… Employees do not decide the amount, but they have full autonomy on how to receive it. Comp9. Job security: company policies or clauses in contracts intended to avoid layoffs.

Communication

Comm1. Regularly share information with employees.

Training

Train1. Training in decision making/ problem solving in groups skills. Train2. Training in leadership, business administration and team management skills. Train3. Training in statistical analysis and quality. Train4. Training for other areas or jobs within the company.

3 Methodology We designed a questionnaire containing two different parts. The first one concerned the potential interaction between each pair of practices (HIWP). Manager and academics experts in the sector were asked to fill in the cells a number from -5 to +5 that expresses whether two practices are in strong conflict, or are strongly synergetic. In essence, the first part of the questionnaire filled in a 21 x 21 matrix expressing the supposed synergy or conflict between each pair of practices (see figure 1)

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HIWP Part1 Part2 Part3 Part4 Part5 Part7 Part8 Rem2 Rem3 Rem4 Rem5 Rem6 Rem7 Rem8 Rem9 Rem10 COM Form1

Part 2

Part 3

Part 4

Part 5

Part 7

Part 8

1 0 1 1 -2 4 -2 0 0 3 -3 -5 1 0 3 2 2 5

1 1 0 1 4 4 0 0 0 0 0 0 0 0 1 2 0

1 3 2 3 3 5 0 2 4 2 0 0 1 3 2 1

1 -5 2 -1 1 0 5 -3 2 5 1 2 3 2 5

1 4 3 1 0 3 -4 1 5 0 1 0 3 5

1 5 4 3 5 -2 3 1 2 3 4 5 4

1 5 1 5 -5 3 3 1 2 4 3 5

1 0 3 0 0 0 0 0 0 0 1

1 0 0 0 1 3 2 0 4 0

1 -2 0 1 1 1 1 5 5

1 2 -4 -2 2 0 0 0

1 -3 0 2 1 1 1

1 0 0 1 0 5

1 5 5 5 0

1 0 0 0

1 1 0

1 2

1

0 2 1

0 0 0

1 0 1

3 5 1

2 3 2

4 2 4

5 5 5

0 1 5

1 0 0

1 3 2

0 2 0

2 2 1

1 3 3

4 0 0

0 0 0

0 0 0

4 0 0

2 5 1

Form 2, 3, 5

Form4 Form7

Re m2

Re m3

Re m4

Re m5

Re m6

Re m7

Re m8

Re m9

Re m1 0

Part 1

CO M

For m1

For m 2, 3, 5

1 3 0

For m4

1 0

For m7

1

Fig. 1 Response of the focus group for the Pair Interaction matrix

Quality 8

CostEfficiency 10

Reliable delivery 8

Absenteism 5

Voluntary turnover 5

Productivity 10

Part2 Part3

0 10

0 2

0 5

8 9

10 6

3 3

Part4 Part5 Part7

8 8 10

10 10 3

10 10 10

7 7 10

5 5 3

10 10 7

Part8 Rem2 Rem3

10 7 0

5 6 2

8 0 0

10 0 1

5 0 1

7 3 2

Rem4

10

10

10

8

5

10

Rem5

2

2

0

7

3

10

Rem6 Rem7 Rem8 Rem9 Rem10 COM

6 5 0 0 1 1

3 5 0 0 1 1

5 4 0 0 0 0

8 2 7 0 0 2

4 3 10 3 6 2

8 3 2 0 0 0

Form1

4

8

3

0

0

9

Form 2, 3, 5 Form4

0 5

0 3

0 3

2 0

4 0

3 1

Form7

1

3

1

0

2

3

Practice Part1

Fig. 2 Ratings of the different HIWP in terms of expected contribution to different dimensions of performance

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The second part of the questionnaire concerned the emergent properties that they produce, which affects the competitive performance of the organization. These were the effects on quality of production, the costs, the ability to deliver reliably, involve employees to decrease absenteeism, reduce turnover and increase productivity. These performance factors clearly constitute the ‘selection criteria’ of the decision of implanting one practice or another. The pair interactions constitute the internal synergies and conflicts that affect the trade offs involved in using particular practices. The 21 possible practices were rated in the second part of the questionnaire according to their expected capacity to perform well in terms of each success criteria factor as seen in figure 2. We can represent the required dimension of performance by using a weight sum of the six performance factors. Using an evolutionary based computer model developed by Peter Allen (Allen 2001) we have made several simulations in order to find the best bundle of practice to achieve certain success factor. Initially, the agents in the model have no knowledge of the effectiveness of the different practices, nor whether they are in conflict or synergy with others. The simulations therefore proceed by an agent trying some, essentially random sequence of innovation by attempting the introduction of a new practice. Each practice is supposed to have a cost in implementation and so following the introduction of a practice if the performance does not increase more than the cost of its introduction then it is considered a failure and its withdrawn. In this way, agents attempt to introduce successive practices in random sequences, and some, by luck, increase the performance of the organization faster than others. The performance is measured by a weighted sum of the six criteria mentioned above. The model proceeds by calculating it for the bundle of practices initially present and adds a random practice. If the gain in performance is less than the cost of the implementation, then the practice is removed again. In this way, overall performance increases in steps given by matrices of performance, depending on the particular sequence that occurs. Repeated runs with different random number seeds have ensure that the results are robust. High performance is obtained by only including practices that provide the right kind of performance and also are synergetic.

4 Results and Conclusions In figure 3 we show the results of the practices maximizing successively the different dimensions of performance. We can identify which bundles fit better for each success factor, and also that the order in choosing the practice to be implant and the ones have been implanted before is relevant to the final results. This implies that it is important to try out practices sufficiently fast, and also that luck will still play a role in who is successful. 734


Fig. 3 Different practices retained for the different dimensions of performance

5 References Akdere M (2009) The Role of Knowledge Management in Quality Management Practices: Achieving Performance Excellence in Organizations. Advances In Developing Human Resources 11: 349-361. Albors J, Hervás JL (2006) CI practice in Spain: its role as a strategic tool for the firm. Empirical evidence from the CINet survey analysis. International Journal of Technology Management 35: 380-396. Allen PM (2001) A Complex Systems Approach to Learning in Adaptive Networks. International Journal of Innovation Management 5: 149. Anand G, Kodali R (2008) Selection of lean manufacturing systems using the PROMETHEE. Journal of modelling in management 3: 40-70. Baxter LF, Hirschhauser C (2004) Reification and representation in the implementation of quality improvement programmes. International Journal of Operations & Production Management 24: 207. Bayo-Moriones A, Bello-Pintado A, Merino-Diaz-De-Cerio J (2008) The role of organizational context and infrastructure practices in JIT implementation. International Journal of Operations & Production Management 28: 1042-1066. Collaine A, Lutz P, Lesage JJ (2002) A method for assessing the impact of product development on the company. International Journal of Production Research 40: 3311-3336. Combs J, Liu Y, Hall A, Ketchen D (2006) How much do high-performance work practices matter? A meta-analysis of their effects on organizational performance. Personnel Psychology 59: 501-528. Corso M, Giacobbe A, Martini A, Pellegrini L (2007) Tools and abilities for continuous improvement: what are the drivers of performance. International Journal of Technology Management 37: 348-365. Doolen TL, Hacker ME (2005) A Review of Lean Assessment in Organizations: An Exploratory Study of Lean Practices by Electronics Manufacturers. International Journal of Manufacturing Systems 24: 55-67. Garcia-Sabater JJ, Marin-Garcia JA, Perello-Marin MR (2011) Is implementation of continuous improvement possible? An evolutionary model of enablers and inhibitors. Human Factors and Ergonomics in Manufacturing In Press. Guest D, Conway N, Dewe P (2004) Using sequential tree analysis to search for 'bundles' of HR practices. Human Resource Management Journal 14: 79-96. Herron C, Braiden PM (2006) A methodology for developing sustainable quantifiable productivity improvement in manufacturing companies. International Journal of Production Economics 104: 143-153.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Hipple J (2005) The Integration of TRIZ with Other Ideation Tools and Processes as well as with Psychological Assessment Tools. Creativity & Innovation Management 14: 22-33. Marin-Garcia JA, Miralles Insa C, Garcia-Sabater JJ, Perello-Marin MR (2011) Alternative tools to mass production and human performance indicators in sheltered work centers of Valencian community (Spain). Journal of Industrial Engineering and Management 4: 467-480. Mol MJ, Birkinshaw J (2009) The sources of management innovation: When firms introduce new management practices. Journal of Business Research 62: 1269-1280. Ordiz Fuertes M (2002) Prácticas de alto rendimiento en recursos humanos. Concepto y factores que motivan su adopcion. Cuadernos de economia y direccion de empresa 12: 247-265. Paauwe J, Boselie P (2005) 'Best practices... in spite of performance': just a matter of imitation? International Journal of Human Resource Management 16: 987-1003. Pavnaskar SJ, Gershenson JK, Jambekar AB (2003) Classification scheme for lean manufacturing tools. International Journal of Production Research 41: 3075. Perello-Marin MR, Marin-Garcia J A, Marcos-Cuevas J (2013) Can we study management innovation from the lens of complexity? Path dependence approach. Management Decision In press. Thang LC, Rowley C, Quang T, Warner M (2007) To what extent can management practices be transferred between countries?: The case of human resource management in Vietnam. Journal of World Business 42: 113-127.

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EN-05 Knowledge and Project Management


Competitive Intelligence Practices in Microenterprises and SMEs from the Industrial Sector: the Case of Basque Country Aldasoro J C1, Cantonnet M L2, Cilleruelo E3 Abstract We are finding ourselves in an increasingly competitive business environment that is characterised by a shortening of life cycles for products and technologies and the globalisation of markets. Within this context, continuous innovation and knowledge have become the most important strategy and resource for the survival of organisations. The aim of this article is to show the results obtained from a survey we have carried out on competitive intelligence practices in microenterprises and SMEs from the industrial sector in the Basque Country. The results clearly show that competitive intelligence is a practice that is gaining importance among these types of enterprise.

Keywords: Competitive Intelligence, SME, Microenterprise, Industrial Sector

1 An Increasingly Changing and Competitive Environment: the New Economy Technical advances have made the continual entry onto the market of new products possible, which in turn has meant that the life cycle of these products has shortened, thus making previous ones obsolete very quickly (Escorsa P. and Valls 1 Juan Carlos Aldasoro Alustiza ( e-mail: [email protected]) Management Dpt. Polytechnical College of San Sebastian. University of Basque Country UPV/EHU. Plaza de Europa, 1; 20018 Donostia-San Sebastián. Spain. 2 María Luisa Cantonnet Jordi. ( e-mail: [email protected]). Management Dpt. Polytechnical College of San Sebastian. University of Basque Country UPV/EHU. Plaza de Europa, 1; 20018 Donostia-San Sebastián. Spain. 3

Ernesto Cilleruelo Carrasco. ( e-mail: [email protected]). Management Dpt. Faculty of Engineering of Bilbao. University of Basque Country UPV/EHU. c/ Alameda Urquijo s/n, 48013 Bilbao. Spain

739


P., 1997). In view of this situation, which is characterised by continuous innovation and products entering the market to compete, firms can be surprised at any time by the appearance of new products, new technologies, new competitors or changes in customer tastes that may threaten their smooth running (Escorsa P., 2003). The mass dissemination of information and communication technologies has led to a new situation that is referred to as the New Economy, which leaves industrial society behind. This New Economy is characterised by the globalisation of markets, a greater supply of products than demand, increasingly demanding customers and continuous innovation as a source of competitive advantage (Escorsa R. and Maspons R, 2001). Within this genuinely competitive and open new context, enterprises that opt for an optimization strategy in management and production, a reduction in costs and an increase in quality are not necessarily more competitive, as both products and technologies can be quickly imitated. Consequently, continuous re-invention of the business model becomes a requirement in order to achieve competitiveness. The milieu has become turbulent and complex – permanent innovation is now the main source of competitive advantage. Thus, the ability to identify new markets and new requirements that need to be met becomes a more important competitive advantage than company size, available resources or the history of the organisation (Gómez A. and Calvo J.L.; 2010). Some authors think competitive intelligence (hereinafter referred to as CI) helps strategists understand those forces that influence the business environment and thus make it possible to develop suitable plans so as to successfully compete (McGonagle and Vella, 2002). The most common benefit (Bose, R., 2008) provided by CI is the ability to design information profiles that help the enterprise identify competitors’ strengths, weaknesses, strategies, objectives, market positioning and behavioural patterns. Such information profiles require data in for firms to identify, classify and keep up with competitors. The organisation may establish comparative aspects such as strengths and weaknesses in relation to its competitors using these profiles.

2 Competitive Intelligence and its Implementation in Organisations There are many definitions of the concept of competitive intelligence, and it may be described as "the use of the entire organisation and its networks to develop useable resources originating from within the milieu (customers, competitors, legislators, technology) that help the enterprise develop and sustain a competitive advantage. This process is applied systematically and ethically in planning, the

740


gathering of information, analysis, communication and management" (Calof 2008). Different studies of an empirical nature show that most enterprises in Spain do not carry out competitive intelligence activities systematically, as the results reflect the fact that three quarters of them view the competitive environment either informally or sporadically (Postigo J., 2001). A study carried out by Cetisme (a consortium comprising several public administrative bodies and private companies) in 2003 shows that a large number of European and Spanish enterprises have the necessary guidelines at their disposal to gather strategic information, yet fail to do so systematically. SMEs have greater difficulties in defining CI programmes and, the smaller the enterprise, the more its CI activity will be limited. Many SMEs resort to buying products from competitors and try to obtain information from the sales team. The Internet is the source used most by small-sized firms (Tena J. y Comai A., 2005). There has not so far been information available regarding the number of firms that carry out competitive intelligence activities systematically in Spain. Different studies fail to describe the magnitude of CI practice in detail (Postigo 2001; Cetisme 2003; Tena and Comai 2003), and show that Spanish enterprises are currently in the initiation phase of innovation activity (Tena J. and Comai A., 2004).

3 Design of the Study into the Carrying out of Competitive Intelligence Practices in Industrial Microenterprises and SMEs in the Basque Country A survey was designed with a view to ascertaining the different types or practices used to implement competitive intelligence activities, and also the main reasons given for carrying them out. Furthermore, an attempt was made to ascertain which organisational and external factors would contribute towards deciding as to their implementation and what checks and balances or impediments there would be that might delay or prevent this. Competitive intelligence is understood as referring to a range of analytical techniques and treatment of information that can be applied in order to obtain conclusions that might give value added to decision-making on a tactical and/or strategic level within the organisation. Table 1 Study population Study population:

425 organisations

Selection criteria:

- Beneficiaries of grants for innovation over the past 4 years - Belonging to the industrial sector - Microenterprises and SMEs

Geographic area:

The Basque Country (Spain)

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The microenterprise and SME classification criterion used by the European Commission was applied in order to classify firms according to the size variable, as established in Recommendation 2003/361/CE (Official Daily L 124, dated 2005-2003), whereby microenterprises are deemed to be those that have up to 10 employees and SMEs between 11 and 249 employees. As for the sector, firms needed to belong to activities deemed to be industrial according to NACE-09 code (National Standard Classification of Industrial Activities), such as the extractive industry, manufacturing industry, electrical energy and gas supply, water supply, clean-up/drainage activities, management of residue and decontamination, and the building trade. Table 2: Features of the questionnaire and way of administering it Type of questionnaire:

Structured, dichotomous scale-type and nominal questions

Sections:

Company features and specific milieu Planning of CI activities in the company CI activities carried out Distribution of CI results Assessment and performance of CI activities

Way in which it is administered:

Self-administered

Field work:

From May to October 2012

Channel used for sending it:

Email (personal and/or corporate)

The questionnaire brought together 124 items or questions, in whose sections an attempt was made to obtain information about company features (size, main activity, market on which they focus and position on the market), and also their specific milieu (intensity of competition on the market, market share). In the Planning section, the aim was to ascertain whether the activities carried out are planned by some managerial body, whether the enterprise has established a formal procedure and whether there is staff specialising in intelligence-based activities. In the Activities section, an attempt was made to establish what type of information the enterprise seeks, the sources of information, the type of analysis and treatment of information, and the techniques used to do so. In the Distribution section, the aim was to find out to which company body the information was sent once the information had been analysed and in which format. Lastly, in the Assessment and Performance section, the questionnaire tried to ascertain whether the intelligencebased activities carried out have helped improve the organisation and whether their effectiveness and efficiency are assessed. The questionnaires received were treated in accordance with the criterion that the survey needed to have 100% of questions from all sections completed, with those that had not met this requirement therefore being rejected. 742


3 Results Obtained The enterprises taking part in the research work give the following reasons for carrying out competitive intelligence activities:

Reasons given by enterprises for carrying out competitive intelligence activities. Percentages.

To keep up with trends in the industrial sector

93

To develop new products

78

To lend support to the strategic planning process

72

To identify new consumer needs

70

To lend support to the tactics implemented

56

To develop new technologies

54

To develop new marketing strategies and tactics

43

To obtain feedback about the strategies implemented

41

0

20

40

60

80

100

Fig. 1 Reasons given by enterprises for carrying out competitive intelligence activities

Figure 1 shows that most enterprises stress the fact that the main reason for carrying out competitive intelligence activities is to be enable them to keep up with trends in the industrial sector (93%), followed by being able to develop new products (78%) and lending support to the strategic planning process (72% of enterprises). In addition, the most used sources of information are mainly news in the press and magazines attached to the sector, Internet search engines, visits to trade fairs and competitions and company websites. The sources of information that prove 743


most difficult to access or use, such as data bases of patents and scientific journals, are used by less than 50& of the enterprises consulted, as shown in the following table. Table 3 Sources of information used by enterprises Sources of information used:

Percentages

News in the press and magazines attached to the sector

96

Internet search engines

96

Visits to trade fairs and competitions

93

Company websites and/or news groups

89

Official bulletins

52

Data bases of patents

48

Purchase and analysis of competitors’ products

46

Data bases from scientific journals

33

Complaints and claims filed via Consumer Protection Offices

9

The results in terms of activities are reflected in the figure 2. In figure 2 it can be seen that the analytical activities used in over 50% of cases were: research into competitor technology and market research in 65% of cases, a study of competitors’ profile in 59% of cases and a SWOT analysis in 57% of cases. The least used techniques (less than 20%) were war games or simulation, analysis of employee profile in competing firms and analysis of Porter’s Five Forces.

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ACompetitive intelligence activities carried out by industrial microenterprises and SMEs in the Basque Country. Percentages.

The enterprise researched into competitor technology

65

The enterprise carried out market research

65

The enterprise carried out a survey of its competitors’ profile

59

The enterprise carried out a SWOT analysis

57

A benchmarking survey was carried out

39

The enterprise carried out an economic and financial analysis of competitors

37

Visits were made to competitors’ workplaces

30

A survey was carried out of social, political and regulatory trends (PEST analysis)

26

The enterprise carried out an analysis using Porter’s 5 Forces model

20

Information was sought about employees from competing firms

11

A war game or simulation was applied

2

0

10

20

30

40

50

60

70

80

90

100

Fig. 2 Competitive intelligence activities carried out by industrial microenterprises and SMEs in the Basque Country

4 Conclusions The results show that enterprises evidence a relatively high degree of interest in obtaining information both from variables that affect both their general and specific milieu. However, the sources of information they use are low-level resources in terms of cost and sophistication, which have certain limitations when analysing 745


the milieu in depth. The gap existing between the information they seek and its subsequent analysis should also be mentioned, as they do not treat the information with the same frequency. Consequently, the conclusion can be drawn that industrial microenterprises and SMEs in the Basque Country can still be found to be in an initial, developing phase with regard to the competitive intelligence system, which is why it can be stated that this coincides with studies carried out by some institutions and authors (Tena J. and Comai A., 2004; Cetisme 2003).

5 References Bose, R. (2008). Competitive intelligence process and tools for intelligence analysis. Industrial Management & Data Systems, vol. 108, nº 4, pp. 510-528). Calof, J.L. (2008). Selling competitive intelligence. Competitive Intelligence Magazine, vol. 11, nº 1, pp. 39-42. CETISME (2003). Inteligencia Económica y Tecnológica: guía para principiantes y profesionales. Innovación, Desarrollo y Transferencia de Tecnología, S.A. Comunidad de Madrid. Escorsa. P., (2003). La región y el fomento a la innovación y la competitividad: experiencias en España y Europa en la construcción de sistemas regionales de innovación. Workshop on Science, Technology and Globalisation. Organización de Estados Iberoamericanos OEI. Escorsa P. y Maspons R.; (2001). De la vigilancia tecnológica a la inteligencia competitiva. Ed. Prentice Hall. Escorsa P. y Valls J. (1997). Tecnología e innovación en la empresa: Dirección y gestión. Ediciones UPC. Gómez A. y Calvo J.L. (2010). La innovación: factor clave del éxito empresarial. RA-MA Editorial. Madrid. McGonagle, J.J. Jr. y Vella, C.M. (2002). A case for competitive intelligence. Information Management Journal, vol. 36, nº 4, pp. 35-40. Postigo J. (2001). La inteligencia competitiva en España: una encuesta sobre su utilización por parte de las empresas exportadoras. El profesional de la información, vol. 10, nº 10, octubre. Tena, J. and A. Comai. (2003). Cómo la inteligencia competitiva apoya a la innovación. Puzzle – Revista Hispana de la Inteligencia Competitiva vol 2, nº 8: 14-18. Tena J. y Comai A. (2004). La Inteligencia Competitiva en las Mejores Prácticas Españolas. EMECOM Consultores S.L. Tena J. y Comai A., (2005). El desarrollo de la inteligencia competitiva en España: un recorrido bibliográfico. Revista Hispana de inteligencia Competitiva. Vol. 4, No. 16.

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Web 2.0 as a Key Tool for Sharing Knowledge in Basque Country SMEs Alvarez Meaza I1, Cilleruelo Carrasco E2, Zamanillo Elguezabal I Abstract Knowledge sharing has become an important variable in knowledge management in enterprises, being the workplace not the best place for flowing employee’s knowledge. That is why, is important to analyze what is the influence of Information and Communication Technologies (ICTs) and its development in the last decade for trying to fill that gap. The bibliographic review illustrates that Web 2.0 is a tool very close to knowledge management and can give us a solution for improving the knowledge sharing. Therefore, this research study analyzes what the current availability of technological tools in Basque Country small and medium-sized enterprises (SMEs) is. More specifically, the use of Web 2.0 tool, in order to evaluate whether the Basque SMEs give importance to knowledge sharing process and what activity sector and size of SME, by number of employees, are using it more intensely.

Keywords: Knowledge Management, Knowledge Sharing, ICT, Web 2.0, SME

1 Introduction Small and medium-sized enterprises (SMEs) are a vital part of any regional economy. In the Basque Country, SMEs are the main source of wealth and employment of its industry, specifically, 99.82% of companies are SMEs. According to EUSTAT (Statistics Institute of Basque Country) data, almost 90% of Basque Country companies have less than five employees. However, the small size of the

1

Izaskun Alvarez Meaza (e-mail: [email protected]) Departamento de Organización de Empresas. Escuela Superior de Ingeniería de Bilbao, C/ Alameda Urquijo s/n, 48013 Bilbao, Spain 2

Ernesto Cilleruelo Carrasco (e-mail: [email protected]) Departamento de Organización de Empresas. Escuela Superior de Ingeniería de Bilbao, C/ Alameda Urquijo s/n, 48013 Bilbao, Spain

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company is not specific from Basque Country, but also is general in European business model (Gobierno Vasco, 2010). European Commission has analyzed EU SME in 2012, and has concluded that, throughout the downturn, SMEs have retained their position as the backbone of the European economy, with some 20.7 million firms accounting for more than 98 per cent of all enterprises, of which the lion’s share (92.2 per cent) are firms with fewer than ten employees. For 2012 it estimated that SMEs accounted for 67 per cent of total employment and 58 per cent of gross value added3 (European Commission, 2012). With this information, management scholars cannot ignore SMEs as a viable and interesting research space (Desouza and Awazu, 2006). Over the past few decades, many parts of the global economy have moved towards a knowledge base, in which wealth creation is associated with the challenge of developing and managing knowledge resource (Coyte et al., 2012). A literature review saw that knowledge management has been studied extensively. Even so, there is a tendency to focus on large business and neglect SMEs (Durst and Edvardsson, 2012). Prior relevant research suggests SMEs are different, not just in size, but in practices around a wide range of management activities, including in the management of knowledge (Hutchison and Quintas, 2008). Thereby, further research is needed to better understand how SMEs manage knowledge resources (Salojärvi et al., 2005, Ricceri et al., 2010). In this context, the advancement and ever-growing of Information and Communication Technologies (ICTs) developed within the past few decades has favoured changes in SME management (Barba et al., 2007) (Cela, 2005). Nowadays, the use of ICTs by European SMEs is driving the way that enterprises run their business and organise e-commerce. The statistical study made bay EUROSTAT concludes that, in 2012, 97% of European SMEs had access to Internet, 77% had a website and one in two enterprises provides staff with portable devices for mobile Internet connection (EUROSTAT, 2012). ICTs play a vital role in the global socio-technological realm through knowledge mobilization, network externalities, alliances and cooperative relationships. The convergence of knowledge management processes and ICTs infrastructure and architecture have been enhanced by the recent advancements in technology ubiquity, semantics and knowledge representation (Mohamed et al., 2010). Particularly, ICTs have a valuable potential for developing SMEs through better integration in business process; also, assisting them to make more efficient decisions to their performance. ICTs have potential to generate changes among SMEs and make them more competitive and innovative (Barba et al., 2007). In this paper, the use of Information and Communication Technologies (ICTs), as a tool for supporting knowledge management process, will be analyzed, with

3

Gross Value Added (GVA) includes depreciation, rewards to labour, capital and entrepreneurial risk. GVA remains when the intermediate costs are deducted from the sales or turnover.

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the purpose of describing the current situation of the use of them, and analyzing the use of Web 2.0 for sharing knowledge in Basque Country SMEs.

2 Knowledge Sharing and Web 2.0 ICTs can enhance knowledge sharing by lowering temporal and spatial barriers between workers. Knowledge sharing has been identified as a phase in the process of knowledge management. At the same time that knowledge sharing is recognize as an important pillar in knowledge management, in practice, it proves to be a significant barrier for effective knowledge management (Hendriks, 1999). Various factors have been identified as impediments for knowledge sharing, like inadequate organizational structures and sharing unfriendly organizational cultures, among others (Davenport and Prusak, 2000) (Tissen et al., 1998). The needed adaption to new scenarios results in a search for new organizational structures and approaches. The management model change into an organization context which promotes the exchange of knowledge by creating the appropriate environment, abandoning the traditional hierarchical structures and giving flexibility to the organizations (Alvarez et al., 2012). The adoption and implementation of ICTs can improve business cooperation, business relationships, quality and diffusion of knowledge. Thus, ICTs are powerful strategic tools for SMEs (Barba et al., 2007). Despite the fact that, other research studies conclude that there is a strong need to create, share and disseminate knowledge within SMEs, this is clearly not related with the availability of ICT infrastructures (Nunes et al., 2006). In particular, when information systems such as intranets, document management systems or groupware applications are introduced to support knowledge sharing, reports show that often the introduction of these systems does not result in significant improvements in knowledge sharing (Hendriks, 1999). Hendriks concludes that ICT is an important instrument to share knowledge, but not the only or most prominent one (Hendriks, 1999).Then, ¿how knowledge can be shared using ICTs?. Internet maturity and development over the last decade, the large number of people that have access to internet through desktop and mobile devices and the evolution of software sector have resulted in what has been called phenomenon Web 2.0 (Levy, 2009). According to Tebbutt, forcing people to encode their knowledge in a formal manner is not easy. When people are socializing, even in a work context, they are much happier to share their thoughts and their experiences. Therefore, he puts the change needed for knowledge management on focusing on people, allowing systems to be focused more into human needs (Tebbutt, 2007). Web 2.0 focuses on people; hence, Web 2.0 is bringing a new trend that should be adopted in knowledge management (Levy, 2009). But, why? Sharing it’s not easy. Perhaps, sharing is something that happens after work time or outside the work749


place. The access to the Internet through mobile devices and the ICTs development towards tools like Web 2.0 have given a potential solution to one of the knowledge management challenges. Levy has analyzed Web 2.0 principles in a knowledge management perspective and has concluded that they are very close to those in knowledge management (Levy, 2009).

3 Empirical Study: the Availability of Technological Tools to Support Knowledge Management in Basque SMEs. Results We will now introduce the methodology that will be used to analyze the availability of technological tools to support knowledge management in Basque SMEs. The studied targeted a group that is composed of 526 SMEs with headquarters in the Basque Country that are associated with any of the following industrial clusters: Machine- Tools, Electrical Appliances, Automotive, Environment, Electronics, Computing and Telecommunications, Energy, Aeronautics and Space, Paper, Audiovisual, Transport and Logistics. The reason why these activities have been selected for this study is that the sectors in which they operate have a high index of industrial production, spend about 60% of expenditure on technological innovation activities and have diversity in terms of their level technology. Moreover, clusters are a key element in competitiveness in the Basque Country and have become the backbone of Basque economic structure, and have allowed to encourage the flow of knowledge and innovation and learning, thanks to the geographical concentration of its enterprises’ activities. Consequently, the company associated with these clusters takes place in an environment where the flow of knowledge is abundant and gives more importance to knowledge management. Table 1 Data sheet for research Object of Study

526 SME associated with clusters

Associated Clusters

Machine- Tools, Electrical Appliances, Automotive, Environment, Electronics, Computing and Telecommunications, Energy, Aeronautics and Space, Paper, Audiovisual, Transport and Logistics

Scope

Basque Country

Data of implementa- June - July 2011 tion Source for elaboration 1. “Measuring Knowledge Management in the Business Sector: First Steps” of questionnaire (OCDE, 2003). 2. “Estudio sobre la Gestión del Conocimiento en España 2004” (Tena and Ongallo, 2004). FUNDECYT y AENOR

750


To collect data, the survey was designed with questions about the availability of technological tools to support knowledge management in order to make an inventory of them. In the questionnaire, there are tools related to internet access, website available, Intranet system, Extranet system, no computerized knowledge supports (documentation centers, archives,...), Workflow/groupware systems, document management systems, computer tools for information search, make use of knowledge sharing applications, like WEB 2.0 and PLM software. The analysis of the results, both quantitative and qualitative, about the availability of different tools to support knowledge management practices, can contribute to understand better the current situation of ICTs in regard to knowledge management practices in different types of companies classified by activity sector and number of employees.

3.1 The Availability of Technological Tools to Support Knowledge Management in Basque SMEs In Table 2, obtained results related to the availability of technological tools to support knowledge management in Basque Country SMEs proposed in this study are represented. Table 2 Percentage of Basque SME that has available technological tools Technological Tools

Available

Access to Internet

100%

Website

95%

Intranet system

73%

Extranet system

50%

No computerized knowledge supports (documentation centers, archives…)

41%

Workflow/Groupware systems

45%

Document management systems

55%

Computer tools for information search

55%

Make use of knowledge sharing applications, like Web 2.0

59%

PLM software

0%

In Figure 1 and Figure 2, achieved results related to the availability of technological tools to support knowledge management in Basque SMEs, by activity sector and by number of employees, are presented.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. 10

5

7,14

5,5

5,82

5 2,67

5 0 Aeronautics and Space

Automotive

Electronics, Comp. And Telcom

Energy

Machine-tools

Others

Fig. 1 The availability of technological tools to support knowledge management in Basque SMEs, by activity sector. 6,67

10

5,43

5,25

5 0 1_9

10_49

50_249

Fig. 2 The availability of technological tools to support knowledge management in Basque SMEs, by number of employees.

3.2 The Availability of WEB 2.0 to Support Knowledge Sharing in Basque SMEs, by Activity Sector and by Number of Employees In Figure 3 and Figure 4, obtained results related to the availability of to support knowledge sharing in Basque Country SMEs proposed in this study are represented. yes

0% 50% 100%

50%

25% 75%

No

33%

50% 100% 50%

67%

0%

Fig. 3 The availability of Web 2.0 to support knowledge sharing in Basque SMEs, by activity sector

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yes

25% 75%

1-9

No

50%

33% 67%

50%

10-49

50-249

Fig. 4 The availability of Web 2.0 to support knowledge sharing in Basque SMEs, by number of employees.

4 Conclusions The technological tools more present in Basque SMEs are: access to the Internet, website, Intranet system and use of Web 2.0 tools. Looking for European statistics about the access to the Internet in SME (97%), it can be concluded that the percentage of Basque SMEs that have access to Internet is higher than the European ones. Furthermore, in general terms, terms Basque SMEs have a large availability of technological tools in order to support knowledge management practices. The Electronics, Computing and Telecommunications sector is the one that has more availability of tools. Therefore, it can be concluded that the availability of technological tools to support knowledge management is linked with technological development of the sector. Moreover, the analysis of availability of tools according to SME size (by number of employees) allows us to confirm the result of other research study related to the use of ICTs in enterprises, claiming that the capacity to have technological tools to support knowledge management is directly proportional to the capacity of technical and human infrastructure of SMEs. Regarding to the use of knowledge sharing applications like Web 2.0, it can be concluded that Basque Country SMEs have promoted the use of new ICT technologies to seek the improvement of knowledge sharing, in order to provide a solution to this important gap in knowledge management process. It is highlighted the fact that Aeronautic and Space sector makes the most use of it. Also, it is observed the fact that SMEs with fewer employees (between 1 and 9) are those that make the most use of it. So, it can be concluded that knowledge sharing doesn’t depend on technical and human infrastructure, but thanks to new ICTs development the solely requirement needed to achieve knowledge sharing is that employees are motivated to do so.

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5 References Alvarez, I., Cilleruelo, E., Zamanillo, I. & Zarrabeitia, E. 2012, "Knowledge management practices in SME. Case study in Basque Country SME" in "Industrial Engineering: Overcoming the Crisis”. Book of Full Papers of the 6th International Conference on Industrial Engineering and Industrial Management, eds. J.C. Prado, J. García, J.A. Comesaña & A.J. Fernández, Universidad de Vigo edn,Vigo, pp. 555-562. Barba, V., Martínez, M.P. & Jiménez, M.I. 2007, "Drivers, benefits and challenges of ICT adoption by small and medium sized enterprises (SMEs): a literature review", Problems and Perspectives in Management, vol. 5, no. 1, pp. 103-114. Cela, J. 2005, "Sociedad del conocimiento y sociedad global de la información: Implantación y desarrollo en España", Documentos de las Ciencias de la Información, vol. 28, pp. 147-158. Coyte, R., Ricceri, F. & Guthrie, J. 2012, "The management of knowledge resources in SMEs: an Australian case study", Journal of Knowledge Management, vol. 16, no. 5, pp. 789-807. Davenport, T.H. & Prusak, L. 2000, Working Knowledge, Harvard Business School Press, Boston. Desouza, K.C. & Awazu, Y. 2006, "Knowledge management at SMEs: five peculiarities", Journal of Knowledge Management, vol. 10, no. 1, pp. 32-43. Durst, S. & Edvardsson, I.R. 2012, "Knowledge management in SMEs: a literature review", Journal of Knowledge Management, vol. 16, no. 6, pp. 879-903. European Commission 2012, EU SMEs in 2012: at the crossroads. Annual Report on small and medium-sized enterprises in the EU, 2011/12, ECORYS edn, Rotterdam. EUROSTAT 2012, ICT usage in enterprises 2012, European Commission, European Union. Gobierno Vasco 2010, Plan de Competitividad Empresarial 2010-2013, Servicio Central de Publicaciones del Gobierno Vasco, Vitoria-Gasteiz. Hendriks, P. 1999, "Why share knowledge?The influence of ICT on the Motivation for Knowledge Sharing", Knowledge and Process Management, vol. 6, no. 2, pp. 91-100. Hutchison, V. & Quintas, P. 2008, "Do SMEs do knowledge management?Or simply manage what they know?", International Small Business Journal, vol. 26, pp. 131-151. Levy, M. 2009, "WEB 2.0 implications on knowledge management", Journal of Knowledge Management, vol. 13, no. 1, pp. 120-134. Mohamed, M., Murray, A. & Mohamed, M. 2010, "The role of information and communication technology (ICT) in mobilization of sustainable development knowledge: a quantitative evaluation", Journal of Knowledge Management, vol. 14, no. 5, pp. 744-758. Nunes, M.B., Annansingh, F., Eaglestone, B. & Wakefield, R. 2006, "Knowledge management issues in knowledge-intensive SMEs", Journal of Documentation, vol. 62, no. 1, pp. 101-119. OCDE 2003, Measuring Knowledge Management in the Business Sector: First Steps, OCDE edn, OCDE, Paris. Ricceri, F., Guthrie, J. & Coyte, R. 2010, The management of knowledge resources within organisational practices:some international best practices illustrations, O'Brien, E.; Clifford, S.; southern, M.; edn, ISI Global, Pennsylvania. Salojärvi, S., Furu, P. & Sveiby, K.E. 2005, "Knowledge management and growth in Finnish SMEs", Journal of Knowledge Management, vol. 9, no. 2, pp. 103-122. Tebbutt, D. 2007, "Breathing new life into KM", Information World Review, , no. Enero. Tena, R. & Ongallo, C. 2004, Estudio sobre la gestión del conocimiento en España, SETSI; FUNDECYT; AENOR edn, FUNDECYT y AENOR, Madrid. Tissen, R., Andriessen, D. & Lekanne, F. 1998, Value-based Knowledge Management: Creating the 21st century company: knowledge intensive, people rich, Logman, Amsterdam.

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Predisposition of Workers to Share Knowledge: an Empirical Study Sáiz L1, Díez J I2, Manzanedo, M A3, Del Olmo, R4 Abstract Our objective is to determine the factors and obstacles that either contribute or complicate knowledge exchange between workers. This research area is new in Spain, as only three references have been found for firms in China and North America. In our approach to this topic, we apply concepts of a sociological, psychological, and motivational nature, which affect knowledge exchange and sharing and allow us to justify the theoretical basis of this study, as well as its purpose and its organizational benefits. A detailed survey was prepared for the empirical research with 21 questions given to a sample of 557 workers from firms in Burgos. Among the positive factors that contribute to knowledge sharing, the results highlight recognition and an appreciation of the worker’s contribution, the work environment and reciprocity. The most important barriers are the poor quality of employment contracts, fellow workers that do not wish to learn, and unfair and disloyal behaviour.

Keywords: Knowledge Management, Knowledge Sharing, Assistance and Barriers to Knowledge Exchange, Employment Contract, Work Environment, Motivation Policies

1Lourdes Sáiz Bárcena ( e-mail: [email protected]) Department of Civil Engineering. Higher Polytechnic School. University of Burgos. C/ Francisco de Vitoria, S/N, 09006 Burgos. 2José

Ignacio Díez Pérez ( e-mail: [email protected]) PhD student. Department of Civil Engineering. Higher Polytechnic School. University of Burgos. C/ Francisco de Vitoria, S/N, 09006 Burgos. 3

Miguel Ángel Manzanedo del Campo ( e-mail: [email protected]) Department of Civil Engineering. Higher Polytechnic School. University of Burgos. C/ Villadiego, S/N, 09001 Burgos.

4

Ricardo del Olmo Martínez ( e-mail: [email protected]) Department of Civil Engineering. Higher Polytechnic School. University of Burgos. C/ Villadiego, S/N, 09001 Burgos.

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1 Introduction Acceptable use of knowledge and its management within the firm is increasingly gaining ground in the promotion of the strong points with which the organization wishes to compete (Ndofor and Levitas, 2004). However, there are workers who are more or less committed to exchange, in accordance with their personality, the context and their motivation, be it intrinsic or extrinsic, that is provided by the firm (van den Hooff and Huysman, 2009) (Martín et al., 2009). The firm is, therefore, committed to knowing about and taking action on all behaviour and attitudes that favour the exchange of knowledge (Chen et al., 2012). Transfer, sharing and management of knowledge within the firm has been considered a process or a function that contributes to the success of the firm, for which purpose general models for exchange have been designed and developed to support this activity (Nonaka and Takeuchi, 1995), (Hedlund, 1994). Nevertheless, there are still people and attitudes within the firm who are contrary to knowledge sharing, which is evident from the barriers to the full application of knowledge management (Connelly et al., 2012). On occasions, such barriers are raised because of the managers and the management style of the firm. Hence, the directors and those responsible for decision taking are key elements, perhaps the most important, so that all employees find their position and share knowledge in the posts where they can best contribute (Yu and Chu, 2007), (Chow and Chan, 2008). In this work, as well as studying the purpose and the elements that influence knowledge exchange between workers, an empirical study is conducted, the novelty of which stands out, which has contrasted the positive factors that are likely to promote knowledge sharing and transfer and the barriers that are likely to prevent such activities. The results and conclusions that are reached will help us progress in this area of research and will provide information to firm directors, so that they take more informed decisions that will enable the effective application of knowledge management.

2 Knowledge Exchange within the Firm Knowledge sharing and exchange in the workplace is a complex task with all too many links and consequences. Its fundamental objective is to transfer knowledge from its generation to the different places in the firm that need it; it therefore affects organizational survival, prosperity and growth, improving its capability to respond and to take action and making it more competitive. Knowledge management, of which this exchange forms part, bases its function on competitive advantage that is gained with the improvement and the quality of the knowledge of people that help to create new knowledge, in a permanent cycle (Erden et al., 2008). Efficient knowledge management means that workers lose their fear of 756


sharing knowledge with other fellow workers (Cabrera and Cabrera, 2002), in an environment where the system or management style provides and favours the trust and the reciprocity needed for workers to perform their knowledge exchange (Renzl, 2008). The exchange of knowledge has beneficial effects for workers, given that learning is quicker, workers learn what is necessary and gain further experience. Even though it may not be completely assured, because there are other factors with an influence, it also has a beneficial effect on the performance of employees (Hsu, 2006). The creation of an environment of trust with acceptable behaviour improves the exchange of knowledge, acting on the personal emotions, minimizing destructive emotional conflict and assisting a work environment based on mutual trust. All of this is supported by distribution of knowledge and information that motivates exchange and mutual learning (Xia and Ya, 2012). Nevertheless, tacit knowledge is the most difficult to capture and to transfer, because it is non-explicit knowledge or because it can be intentionally concealed by the person who holds it. This type of knowledge might imply a point of negotiation or a guarantee to remain in the firm, because of the exclusivity that it represents, which may even be used as a token for exchange (Yuqin et al., 2012). Despite the beneficial effects of the exchange of knowledge, on occasions, workers deliberately hide and even deny the existence of their knowledge (Connelly et al., 2012), or raise seemingly insurmountable barriers that appear in various forms (Lin et al., 2012). In some situations, when the worker does not share knowledge, it is out of a fear of losing the status that the firm has and by which it is valued. In these cases, if the work environment is not conducive to knowledge exchange, the majority of workers will be fearful of doing so (Renzl, 2008). This fear brings to the surface the feeling of being replaceable in the firm, when the exercise of sharing means that the worker loses any exclusive idea of possessing knowledge (Renzl, 2008). In this context, a possible consequence, in the worker’s view, is redundancy, with all of its very significant psychological and social consequences (Raday, 1989), (López, 2007), (Eguchi, 2007). The disastrous economic situation at present means that redundancy is often determined by the shorter employment record of the worker as much as by criteria based on any corresponding compensation for loss of employment (GaldónSánchez and Güell, 2003). It generates an uneasy situation in which the youngest or the most recently incorporated workers are unjustly disadvantaged (Malo and Cueto, 2012) and not those who contribute least knowledge. Together with this, the practice of early retirement may imply the loss of more expert workers, who will be replaced by others at a lower level. This retirement is encouraged for purely pecuniary reasons, as the new workers are on considerably lower salaries, with no consideration of the knowledge that it contributes (Cremer et al., 2009), (Messe, 2011). Incentives and rewards, valuable allies for the correct application of knowledge management, should therefore be offered to alleviate the consequences of these 757


practices in the workplace (Quigley et al., 2007). With an acceptable design, a supportive and beneficial work environment may be created for knowledge exchange and transfer. Organizations may provide various rewards in multiple forms, such as salary increases, bonuses, stable contracts, opportunities for promotion and other types of benefits for the workers (Bock et al., 2005). Bearing in mind cultural, national and other factors linked to where the incentive is created, it has been demonstrated that the organization is, on occasions, more effective in the formation and teaching of its employees, when there is an incentive that rewards that attitude towards learning (Hall, 2001). However, research also exists that proves that the organizational response can have a negative effect on the attitude of the individual towards the exchange of knowledge (Bock et al., 2005).

3 Empirical Study: Methodology, Justification for the Study, Sample and Questionnaire The objective of this study is to survey the views and perceptions of workers towards knowledge exchange and sharing within the firm. In other words, the aim is not only to establish whether workers share knowledge in a natural way in their jobs in the firm, but also to establish which, in their opinion, are the drawbacks and barriers that complicate that exchange. The justification for this study is based on the need to know some of the aspects that affect knowledge exchange, from the work environment, the management style, the personality of the individual and the social and interpersonal relations that are found in the workplace. The sample consists of 557 workers from different firms in the city of Burgos (northwest Spain) and the province of the same name, found in the automobile, services, energy and agricultural and livestock sectors. Further data that are representative of the sample are as follows: workers are contracted by firms with over 10 workers and have, on average, 2 years service, for those within the 18-31 year-old age bracket, 10 years of service for those within the 31-45 year-old age bracket, and 20 years service for those older than 46 years old. An “ad-hoc” questionnaire was designed to gather the data, composed of 21 questions and structured into four sections: a) general data for the identification of the participants; b) predisposition to exchange knowledge; c) human relations and work environment; c) motivation and incentives to encourage exchange. The questions were drafted with the help of two experts, knowledgeable of the reality of these firms and of the challenges and trials that they have faced in the exchange and sharing of their key knowledge. Having completed the questionnaires, performed the data treatment and the analysis of the information that had been gathered, the results and the conclusions helped us to identify barriers to knowledge sharing and incorporated 758


recommendations of interest on how to increase and to improve the exchange of knowledge in the firm. Table 1 Research data sheet Sample population

557 workers

Sectors of economic activity

Automobiles, Services, Energy, Agriculture and Livestock

Field

Burgos and province (Spain)

Date of survey

June - October 2012

Design and Technical Direction

J. I. Díez, L. Sáiz, M. A. Manzanedo

Sources for the preparation of the questionnaire

(Lin et al., 2012), (Connelly et al., 2012), (Bures, 2003)

4 Results and Conclusions This study has summarised its results, in particular, those that refer to situations or aspects that support knowledge sharing within the firm and equally those that prevent it or complicate it. Moreover, it reflects the predisposition of workers to share knowledge and the incentives that encourage behaviour that will support knowledge exchange within the firm. The descriptive results are presented as frequencies and percentages, to facilitate a clear understanding (Table 2). Table 2 Aspects that support and that prevent knowledge sharing Aspects that support sharing

(%)

Aspects that prevent sharing

(%)

Recognition and appreciation

24.5

Unstable contract

17.2

Good work environment

14.2

Fellow workers who do not wish to learn

15.2

Reciprocity

16.1

Disloyal fellow workers

14.6

Stable contract

9.7

Lack of recognition and appreciation

14.5

Remuneration

8.9

Bad work environment

13.3

Labour responsibility

8.4

Bad relation with fellow workers

9.6

Business organization

7.1

Unfairness of salary or in decision-making

7.3

Comunication with management

4.7

Pressure or bullying

4.2

Fair firm

3.3

Badly organized firm

4.1

Job security

3.1

With respect to the predisposition of the worker to share knowledge, the results revealed that 80.3% would be willing to teach others, provided that the people they teach do not appropriate their ideas, and 40.4% would not share it with fellow 759


workers unfairly assessed as better than them. If workers considered themselves poorly valued or underused, which implies a lack of motivation, they would not share their knowledge. Moreover, if the acquisition of such knowledge had implied a significant effort, 29.4% of individuals would not share it. Reciprocity in the transmission of knowledge emerged as an essential element for knowledge exchange, given that 38.8% would not transfer their knowledge if others did not do likewise. The leading incentives for knowledge transfer were, for 72% of interviewees, an organizational structure that promotes and facilitates sharing knowledge and know-how; the existence of a stable contract in 65% of cases; and 34% responded positively to the idea of additional remuneration for passing knowledge on to others. We may deduce from these results that the study has revealed some unknown factors in relation to the exchange and the sharing of knowledge. By means of an empirical study that used primary information (from 557 workers in different firms), we tested the elements and opportunities that supported knowledge transfer in the workplace, as well as its obstacles and limitations. The most prominent aspects are recognition and appreciation of the worker by the firm, up to the point that when this recognition is lacking, a highly demotivating situation is generated, not only for knowledge sharing, but also to be efficient and to contribute value to the function in question. Another relevant element is a work environment oriented towards knowledge sharing, as in situations of conflict, there is a lack of clarity in the assignation of tasks and objectives and little or no consideration of the worker, which is demotivating and provokes passive attitudes with little or no involvement in improvements made to the job. Mutual reciprocity is a further element that favours exchange and notably influences human behaviour, it being a quality that affects, in a significant way, not only the quantity, but also the quality of valuable knowledge exchange. In turn, the poor quality of employment contracts are found among the barriers that, more than any other, complicate knowledge sharing between workers. A direct tie between the quality of the contract and knowledge exchange has been confirmed; fellow workers unwilling to learn or showing unjust and disloyal behaviour represent an added problem given that it is an intentional attempt to render the exchange inoperative, either by the negation to acquire more knowledge or by not using what has been acquired. This study has also served to establish certain factors that influence the predisposition of the worker to share knowledge, which are maintenance of knowledge ownership, fair valuation of the work carried out by everybody, and the fact that others share and interact with their knowledge. The motivating elements or most prominent incentives to achieve efficient exchange reside in an appropriate organizational structure, stable contracts and specific remunerative complements for those who share knowledge.

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5 References Bock GW, Zmud RW, Kim YG et al (2005) Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Quarterly: Management Information Systems 29(1): 87-111. Bures V (2003) Cultural barriers in knowledge sharing. E+M Ekonomics and Management, Liberec 6(special): 57-62. Cabrera Á, Cabrera EF (2002) Knowledge-sharing Dilemmas. Organization Studies 23(5): 687710. Connelly CE, Zweig D, Webster J et al (2012) Knowledge hiding in organizations. Journal of Organizational Behavior 33(1): 64-88. Cremer H, Lozachmeur J-M, Pestieau P (2009) Use and misuse of unemployment benefits for early retirement. European Journal of Political Economy 25(2): 174-185. Chen S-S, Chuang Y-W, Chen P-Y (2012) Behavioral intention formation in knowledge sharing: Examining the roles of KMS quality, KMS self-efficacy, and organizational climate. Knowledge-Based Systems 31(0): 106-118. Chow WS, Chan LS (2008) Social network, social trust and shared goals in organizational knowledge sharing. Information & Management 45(7): 458-465. Eguchi K (2007) Productivity loss and reinstatement as a legal remedy for unjust dismissal. Journal of the Japanese and International Economies 21(1): 78-105. Erden Z, Von Krogh G, Nonaka I (2008) The quality of group tacit knowledge. The Journal of Strategic Information Systems 17(1): 4-18. Galdón-Sánchez JE, Güell M (2003) Dismissal conflicts and unemployment. European Economic Review 47(2): 323-335. Hall H (2001) Input-friendliness: Motivating knowledge sharing across intranets. Journal of Information Science 27(3): 139-146. Hedlund G (1994) A model of knowledge management and the N-form corporation. Strategic Management Journal 15(S2): 73-90. Hsu IC (2006) Enhancing employee tendencies to share knowledge- Case studies of nine companies in Taiwan. International Journal of Information Management 26(4): 326-338. Lin C, Wu J-C, Yen DC (2012) Exploring barriers to knowledge flow at different knowledge management maturity stages. Information & Management 49(1): 10-23. López B. SA (2007) Efectos individuales del despido y la resilencia como facilitador en la búsqueda del empleo. Panorama Socioeconómico. Redalyc 25 (035): 168-172. Malo MÁ, Cueto B (2012) Biografía laboral, ciclo económico y flujos brutos en el mercado de trabajo español. Panorama Social: 1-24. Martín C. N, Martín P. V, Trevilla C. C (2009) Influencia de la motivación intrínseca y extrínseca sobre la transmisión de conocimiento. El caso de una organización sin fines de lucro. CIRIEC-España, Revista de Economía Pública, Social y Cooperativa. Redalyc 66(octubre): 187-211. Messe PJ (2011) Taxation of early retirement windows and delaying retirement: The French experience. Economic Modelling 28(5): 2319-2341. Ndofor HA, Levitas E (2004) Signaling the Strategic Value of Knowledge. Journal of Management 30(5): 685-702. Nonaka I, Takeuchi H (1995) The Knowledge- Creating Company. Oxford University Press, Inc., Oxford. Quigley NR, Tesluk PE, Locke EA et al (2007) A multilevel investigation of the motivational mechanisms underlying knowledge sharing and performance. Organization Science 18(1): 71-88. Raday F (1989) Costs of dismissal: An analysis in community justice and efficiency. International Review of Law and Economics 9(2): 181-207.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Renzl B (2008) Trust in management and knowledge sharing: The mediating effects of fear and knowledge documentation. Omega 36(2): 206-220. Van Den Hooff B, Huysman M (2009) Managing knowledge sharing: Emergent and engineering approaches. Information & Management 46(1): 1-8. Xia L, Ya S (2012) Study on Knowledge Sharing Behavior Engineering. Systems Engineering Procedia 4(0): 468-476. Yu CP, Chu TH (2007) Exploring knowledge contribution from an OCB perspective. Information and Management 44(3): 321-331. Yuqin Z, Guijun W, Zhenqiang B et al (2012) A Game between Enterprise and Employees about the Tacit Knowledge Transfer and Sharing. Physics Procedia 24, Part C(0): 1789-1795.

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User Software and Information Systems in Engineering Project Management Arias J1, Rubio R, Solana J Abstract Project management is important and necessary for every organization, as projects are required either for growing or adapting the organization to the environment, and also because some organizations – especially the project oriented ones – depend on the successful management and execution of projects for other organizations in order to survive. That is why some software tools have been developed to assist the team of the project in the administration of the work to be executed. These software tools include user software and organizational platforms. Although user software cannot be considered as an information system per se, it can be used together with larger systems which can actually be considered information systems which are knowledge sharing structures involving also the human factor. The final aim of an information technology structure supporting such an information system would be to integrate that software with the underlying organizational information system under which all the relevant information related to the resources of the organization is contained.

Keywords: Information Systems, Knowledge Management, Project Management, User Software, & Information Integration Strategies.

1 Information Systems and User Software An information system can technically be defined as a set of interrelated components that collect, process, store and distribute information to support decisionmaking and control in an organization (Laudon & Laudon, 2012). On the other hand, user software might be any kind of information technology based tool that is

1José Manuel Arias Calvo ( e-mail: [email protected]) Grupo de Ingeniería de Organización. Dpto. de Organización, Administración de Empresas y Estadística. Escuela Técnica Superior de Ingenieros de Telecomunicación. Universidad Politécnica de Madrid. Avenida Complutense 30, 28040 Madrid.

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used by any user to carry out typical desktop tasks like writing a document or preparing a presentation. There is, therefore, a substantial difference between the two concepts. While information system platforms may be based on hardware networks of information technologies that involve the use of intranets or Internets, especially for collecting and disseminating information, user software packages are usually supporting the labor of each individual user of that software.

2 Engineering Project Management On the one hand, system design has a “focus on the problem itself, its delimitations, the systemic objectives, the technical aspects of the design and structure of the solution.” On the other hand, project management has a “focus on the management of the problem solving process, the planning and allocation of material, personnel, finance and similar resources, the organization of the flow of information, of the process of forming an opinion and the process of decision” (de Weck & Lyneis, 2011). It is already clear from this definition that project management has a clear tendency towards being supported by management information systems, which may be able to support decision taking and control. This may appear to be clearer in Fig. 1, where decision taking may be used within the project adapting phase in order to establish effective control mechanisms based on the project execution monitoring status to be addressed.

Fig. 1 Project model (de Weck & Lyneis, 2011)

Apart from this feedback loop inside the project, there is a feedback loop between projects, which corresponds to double-loop learning organizational processes. This means that learning organization principles might be applicable when try-

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ing to make different things in the future such that results are better than in previous projects (Argyris & Schon, 1996). In the next sections, the way existing information systems and user software packages can help in the development of engineering projects is discussed, as well as the need for user software packages to transition into management information systems in order to be more effective in the project management function.

3 User Software for Project Management User software involves different software packages like Microsoft Project, Primavera Project Planner, OpenProj, DotProject, etc (Rubio, 2013). A brief description of each of them is provided below. Microsoft Project is one of the tools most used in project management. It is applicable to all types of industries. This tool allows the project manager to program all the project activities, allocate resources and people in charge to each of them, follow up the progress of the project, administer the budget and analyze workloads. It is also possible to find the critical path by means of a Program Evaluation and Report Technique (PERT) analysis and trace Gantt graphs. It applies the concepts described by the Project Management Institute, and it can be said to be structured along the three great concepts of project management: Gantt, PERT and Critical Path Method (CPM). The software also includes the possibility of simultaneously administering several projects, aggregating dependencies among them, and managing shared resources. Primavera Project Planner is a tool that is less extended than the previous one, but also known in the area of project management, and used in all types of industries, although it was first developed for construction engineering projects. Some recommend it as a tool more powerful than Microsoft Project, although less intuitive. For all of this the user is required to have previous knowledge in computing, Gantt charts, critical path, CPM and Work Breakdown Structure (WBS). As in the previous case, it is also necessary to have a clear idea of the different activities that constitute the project as a whole, the resources and the costs associated to these activities. This knowledge allows the user to configure the WBS, so that all the elements to enter the data into the software are available. OpenProj is free software for project management designed as a complete substitute of Microsoft Project able to open project files native of Microsoft Project. OpenProj is run in Java platform, which enables its execution in a variety of different operational systems. Compared to Microsoft Project, OpenProj has a similar user interface and a similar focus for the construction of a project plan: create a list of tasks or WBS, establish the durations, create links and allocate resources. The fields and costs are the same as for Microsoft Project: work, time, material usage and fixed costs. Therefore, a user of Microsoft Project should find it easy to 765


use OpenProj. It controls all the aspects referred to project management: planning and programming, management and allocation of resources, simulation of alternatives in critical processes, etc. DotProject is built by means of open source applications and maintained by a little group of volunteers. It is an application based in web. Free support is provided by volunteers in the community forums and by online documentation. It is a tool with a simple user interface. DotProject is a tool oriented to project management. Therefore, it is oriented to the administration of resources to develop a product whose production requires of a set of activities or tasks carried out in parallel or independently. It enables the management and planning of projects in collaborative environments, the allocation of resources to a single or several projects, and the decomposition into tasks. It also enables the classification and ordering of projects according to their state. Some of the statistics that can be extracted are allocated hours and hours incurred in reality. As it is based in a web platform, it allows the members of a project to participate online.

4 Information Systems for Project Management Information systems for project management involve different software platforms like Planisware 5, Red Mine, Clocking IT, Lighthouse, Springloops, CreativePro Office, No Kahuna, Basecamp, SAP, DOORS, etc (Rubio, 2013). Planisware 5 is an Enterprise Project Portfolio Management solution or Corporate Portfolio Management, which supports the portfolio management of organizational projects. It is a tool designed as a project management information system covering costs control, portfolio management, resources management, time planning and collaborative work. It is conceptually different from the software packages previously commented, as it can be actually understood as a work platform for all the organization more than as user software. Project portfolio management is useful to ensure the projects to implement are in line with the organization strategy. Planisware 5 helps to develop and manage a product portfolio under development in equilibrium with a sustainable number of projects. Red Mine is a tool for project management including a non-conformances tracking system. Other tools included are an activity calendar, Gantt diagrams for the visual representation of the projects timeline, wiki, forum, versions control repository viewer, workflow control based on roles, integration with e-mail, etc. It is free software and open code. This tool is very useful for organizing the information stored in the organization. CreativePro Office offers online management tools and is totally free. It is thought for autonomous and little teams of graphical designers and web developers. With this tool, any project manager might be able to administer his team in an easy and intuitive way. Also, all the team can be aware of the project state. 766


No Kahuna is a simple tool for project management. It enables the creation, distribution and tasks follow-up of all the project members. It is also possible to delegate tasks, alerts and statistics, as well as visualize the advances of each phase, percentages of the project and everything that might be necessary to warrantee that the project will be finished in the required time. It is free until 30 tasks or 3 projects are open. Many people consider Basecamp the best project management system and collaboration platform that exists. Its main functionalities are: task lists, file sharing possibilities, time management, comments, calendar to see the projects to which one belongs, and the last actions of the employees. Basecamp is under payment, but there is a free version and 30 days trial versions. SAP is divided into modules. Each of them carried out a different function but is designed to work with other modules. It is integrated totally so that it is compatible with all the functions of an organization. It also produces specialized modules in different specific sectors. Some of these modules are: financial accounting, controlling packages, project systems – the one of interest for our work, human resources, plant maintenance, quality management, production planning, materials management, and sales. Finally, IBM Rational DOORS is a requirements management application for optimizing communication, cooperation and verification of requirements in the organization and all the supply chain. It is a scalable solution that can help to manage the scope and costs of a project as well as to reach the organizational objectives. The DOORS tool allows the user to capture, search, analyze and manage changes in the information, as well as to show conformity with norms and standards.

5 Conclusions The previous distinction between user software and information systems establishes a first idea of how a project management can be better supported by the use of information technologies. In a first step, user software like Microsoft Project would require the manual acquisition of information regarding the current status of a project in order the compare it with the foreseen evolution. If there are meaningful differences, then the original planning would have to be reworked. The problem here would be how to gather all the information required so that an accurate idea can be provided to us of how the project status is at a given moment in time. This task might be carried out more easily with the support of software tools like the ones described in the last section. Integration with organizational resources offers a more interesting way of dealing with the allocation of resources to a given project, as well as the evolution analysis of the different activities involved 767


in a Gantt chart. This is especially demanding in an organizational environment where there are multiple projects running simultaneously. It is interesting to see that from a system information evolution point of view, the firstly mentioned user software only represents a very primary contribution to an information system, where most of the tasks would have to be carried out manually. On the other hand, information systems like Planisware 5 or IBM Rational DOORS enable the integration of the planning tools with the overall organizational system. Human intervention is always needed in an information system, but in this last case, it is easier to accommodate, for the technology behind already covers much of the work. Therefore, big room for improvement is left for user tools like the well known Microsoft Projector or Primavera Project Planner. It is then proposed from this contribution that future evolutions of these products gradually evolve towards an integrated information system solution like the ones described under the last section. In a greater context, it is clear that a good planning system is necessary to ensure the success of project management in the long run. By means of model simulations like the one in Arias (2012), it can be shown how the influence of information systems is determinant in the future resources consumption of a project. If the information system in place is of high quality, then the planning will be good, and the resources consumption will not increase dramatically during the development phases of the project. The way information systems affect the planning of a project is depicted below.

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Fig. 2 Project dynamics model (Arias, 2012)

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Base System Quality

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Fig. 2 (continued) Project dynamics model (Arias, 2012)

+

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+

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+ - Actual Perceived Productivity 0



6 Limitations The research which has been previously presented constitutes a compared analysis of a discretional number of software applications used in project management. Further work would consist on identifying a set of criteria for establishing a more extensive set of software applications under study. However, the intention of the article is to establish a framework for the performance of additional research.

7 References Argyris C, Schön DA (1996) Organizational Learning II. Addison-Wesley Publishing Company, United States of America. Arias JM (2012) The Influence of Information Systems in the Learning Organization within the Context of Project Management. System Design and Management thesis, Massachusetts Institute of Technology. Laudon KC, Laudon JP (2012) Management Information Systems. Pearson Education, Upper Saddle River. Rubio R (2013) Influencia de los Sistemas de Informacion en la Gestion de Proyectos de Ingeniería. Proyecto Fin de Carrera, Universidad Politécnica de Madrid. De Weck O, Lyneis J (2011) Successfully Designing and Managing Complex Projects. MIT Press.

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Application of Public Private Partnerships to the Spanish Airport System Coello N1, Rodríguez Monroy C2, Calvo F3 Abstract The current deficit situation of the Spanish airport system suggests the need to manage this in a more efficient and profitable way. One of the possible options is through private management and being able to do this through Public Private Partnerships (PPP). This study analyzes the situation of the sector and its economic importance and the different possibilities for introducing private management in a public company, specifying the situation in the case of airports, presenting the advantages and disadvantages of these possibilities, and aiming at results obtained in other places where it has been applied. It is proposed that the ideal model for the introduction of private management would be through PPP models tailored to each airport, but having common characteristics according to the group they belong to. Finally, we observe that not all airports are commercially attractive, so that the PPP concept does not apply to all of them. In some cases even the operability itself is not viable at all, and that should be considered separately in order to avoid creating a private monopoly while trying to enhance competition among them.

Keywords: Airport, Privatization, Efficiency, PPP, Management.

1 Nicolás Coello ( e-mail: [email protected]) Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2, 28006 Madrid. 2

Carlos Rodríguez Monroy ( e-mail: [email protected]) Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2, 28006 Madrid 3

Félix Calvo ( e-mail: [email protected]) Universidad Politécnica de Madrid. c/ José Gutiérrez Abascal, 2, 28006 Madrid

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1 Introduction The purpose of this paper is to analyze more efficient options for managing the Spanish airport system through the PPP approach in order to reach a sustainable economic situation. Given the difficult financial situation faced by many European countries, including Spain, it is almost impossible to imagine that a public airport management company may have a permanent budget deficit situation. An alternative to privatization is the PPP pproach, which can provide economic management benefits without losing control of the ownership of public assets. We begin by studying the situation of the sector and what the PPP concept implies. The bases for these studies are all secondary data taken from research databases and reports from organizations or government agencies. With these data we propose a possible model for the different airports and we warn that some of them will not be possible to operate even under private management. We also warn of the dangers that may appear by taking this action, including the possible creation of a private monopoly.

2 Situation of the Spanish Airport System Currently the Spanish airport system is managed by a public company called Aeropuertos Españoles y Navegación Aérea (AENA) which manages the provision of airport and air navigation services. AENA is responsible for providing air navigation services in Spain and other parts of the world. In this paper, the analysis will focus on the part related to AENA Aeropuertos SA, which manages 47 airports and 2 heliports in Spain. Since the outset we can consider separately air operations and ground operations, given the possibility of having separate management, as it has been shown in the recent separation of Aena Aeropuertos SA, as mentioned in Ley 9/2010 de 14 de Abril. Since the establishment as an independent company Aena Aeropuertos SA has allowed the entry of private capital in its shareholding. In fact, in 2011 it was envisaged an IPO of 49% of the company, which has not been implemented, although it is still in the ideology of the political management the flotation of the company in one or two years, as stated by the Secretary of State for Infrastructure, Transport and Housing, Rafael Catalá in July 2012 (Preferente.com 2012). Given the importance of tourism in Spain, which represents 10.2% of GDP and 11.5% of employment, according to 2010 data provided by the OECD, and according to the Balance of Tourism 2011, conducted by the Instituto de Estudios Turisticos, 80% used as transportation means the plane, and within that group 56.9% have made their displacement in a low-cost carrier, which represents a growing trend. Thus, an efficient airport system is absolutely necessary in Spain, for its heavy reliance on tourism, and the dependence on the low cost airlines. But 773


instead AENA approved an average increase rate of 19%, which represents at the two busiest airports, Madrid Barajas and Barcelona El Prat, a maximum of 50%. In previous years these airports have undergone a deficit, and the company has accumulated a debt for the whole system, of 14,000 million euros, while navigation charges dropped by 7.5% (Galindo 2012). Of all 47 Spanish airports managed by AENA, (AENA 2012b), and according to a report by the Fundación de Estudios de Economía Aplicada (Fedea 2012), only eight are profitable. These airports are: Fuerteventura, Alicante, Ibiza, Palma de Mallorca, Sevilla, Valencia, Lanzarote and Málaga. This report also indicates, that more than half of the airports have another airfield within a radius of 130 kilometers, and in some cases such as Galicia three airports are less than one and a half hours by road, for a population of 2,778,913 inhabitants in 2012. Within the network, there are airports those have no airlines operating in them, such as Ciudad Real and Lleida, or have never operated such as Castellón. To reach this efficiency at airports one of the measures that can be introduced is private management. This can be attained from outsourcing the management of a company, to the complete sale of the infrastructure, and a number of possible intermediate steps. Within this intermediate steps between full public ownership and management, to complete private ownership is the PPP concept.

3 Public Private Partnership (PPP) and Privatization in Transport Infrastructure Focus in Airports There is no clear definition of what constitutes a PPP, as expressed by Carmona (2010), beginning with the controversy for some authors of what “partnership” really means. PPP definitions given by various European bodies such as the European Commission, can be found in the “Green paper on public-private partnerships and community law on public contracts and concessions” that defines PPP as “forms of cooperation between public authorities and the world of business which aim to ensure the funding, construction, renovation, management or maintenance of an infrastructure or the provision of a service”. For another institution as the European Investment Bank, the term PPP covers a wide range of situations. It should be taken as a “generic term for the relationships formed between the private and public sectors bodies often with the aim of introducing private sector, resources and/or expertise in order to help provide and deliver public assets and services”. From the perspective of the latter organization the “key feature of a PPP is that it involves a risk sharing relationship between public and private promoters, based on a shared commitment to achieve a desired public policy outcome”. Therefore as Carmona (2010) notes a factor to determining PPP project is considered a transfer of a sufficient amount of risk to the private partner on a long term basis. 774


In these definitions the primary purposes for which it resorts to such alliances is made evident, and as Graham (2011) points out and specifies in the case of airports, it is based on a synthesis of the research done on the topic, besides being studied in the country that led to partnerships and privatizations which was the UK, with its large privatization in 1987. In the same paper Graham (2011) states that the three main objectives of the PPP approach have been improving efficiency, cover the needs for new investment and improved management and diversification. It also includes a possible advantage if, as for the current political situation in the case of Spain, with strong interference and manipulation, more so in public companies as the case of AENA, we obtain the removal of state control over the company due to the transfer of risk and responsibility to the private sector, and the elimination of corrupt practices (Janecke, 2010). An example of some of the existing models, and their acronyms can provide an idea of the possibilities that this concept offers:  Build-develop-operate (BDO).  Design-construct-manage-finance (DCMF).  Buy-build-operate (BBO).  Lease-develop-operate (LDO).  Build-own-operate-transfer (BOOT).  Build-rent-own-transfer (BROT).  Build-lease-operate-transfer (BLOT).  Build-transfer-operate (BTO). As it can be observed the main activities are design, build, develop, operate, manage, finance, lease, rent and transfer. It may simply be managing or until full license for a project as a private activity is granted, only at the end of a specified time set forth in the previous contract, ownership to the public agency must be transferred, i.e. long-term final possession should always be public. There are other modalities and some authors consider that the final possession can be left to the private company. This is possible given the definitions given, since according to the European Commission, providing a service, which can be seen as outsourcing, could be considered PPP. These partnerships, as Graham (2011) notes provide some diversification benefits and development of non-aeronautical revenues, new areas for business, increased competition among airlines, airports and increased financial benefits for the state. In case of privatization, as a sale of shares, the greater benefits to be gained are the prompt monetary income derived from the total sale. On the other hand the drawbacks of this alliances and privatizations are the possibility of going from a public monopoly to a private monopoly, changing criteria of increased social benefit to increase economic benefits, which can also lead to excessive airline fees pricing, reduced service quality and under-investment. There is also a tenden-

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cy to perceive this as a lack of control of a public asset considered of national interest, which has a major impact on society and the environment. One of the key factors to avoid these drawbacks is in the legislation, which is a topic addressed in the efficiency and success of a PPP. Another point to prevent private monopoly is granting different airports individually and not as a network. Foster (1984) has studied the problems of network ownership compared to individual ownership, and has emphasized the potential that the latter has to provide competition among them. He even claims that the best type of possession is by local organizations, and that this is preferable to possession by national organizations. Actual outcome is found in different studies such as those performed by Vogel (2006) which prove the existence of significant differences when the owner is a private company showing that there is a better performance. Furthermore Oum et al. (2006) state that airports with private ownership majority reach higher levels of operating margins, and that private minority models are less effective, even less than when they are totally public.

4 Discussion on Improving the Spanish Airport System In the case of the Spanish airport system it is essential to determine the main objectives to be achieved. It is clear that one of the main objectives is the efficiency gain in airport management, in order to create a competitive system with no deficit. There is also the possibility to combine other objectives that might be interesting within what has been highlighted. For example, it could be important in the Spanish situation, given the current financial crisis situation and the difficulties to get involved in new high-value public infrastructure, to provide funding for certain airports which are near their operational capacity limit, such as Madrid Barajas and Barcelona El Prat, which may require operational enhancements or alternative high capacity airports in the future. Given the characteristics of this sector these funds should be planned for well in advance. These projects could be designed and funded through a PPP approach. The current situation of AENA with a debt of 14,000 million euros, is another factor to be considered. The difficulty lies in the complexity of making the right choice of model, which may also differ according to the type of airport, and adds further complexity here given the large number of operating airports. It must also be taken into account, as noted above, that the ownership of airports individually is more effective than as a network. This is confirmed by the efficiency study of Spanish airports, conducted by Tapiador and Matthew (2008) who, after measuring the efficiency of all airports individually, concluded that there are major differences between them and that different operating strategies for each should be performed.

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After seeing the different possibilities of PPP models, an attempt is made to balance reasonably well the advantages and disadvantages that could lead to the adoption of a specific PPP model. It is not possible to give an individualized solution for each airport given the size, but a proposed outline for airports with similar characteristics is possible. Airports will be classified in eight categories according to AENA, which considers factors such as size, geographic location and type of traffic, as quoted by Ruiz de Villa (2011). In the first place PPPs options will be chosen, since it does not seem interesting to sell airports unless it is a majority sale, because as Oum et al. (2006) have analyzed it may result in greater inefficiency, and lack of control. Moreover, since there is a possible opposition from various sectors of the population, PPP approaches provide the benefits of private management knowing that property remains with the state. Hub airports, major and middle island airports and regional airports, all with over 2.5 million passengers, according to AENA (2012), international flights, with great presence of tourist traffic and low cost operators are presented as the most attractive for private management. Some of them, like the Madrid and Barcelona hubs as shown in the Tapiador and Matthew (2008) study find that these airports are working at very high efficiency, but the profitability according to the Fedea study determines that they remain with a budget deficit. This confirms the need to improve the non-aeronautical revenues. According to these same studies few of them are profitable, but could be even more profitable since almost all of them do not reach the operating efficiency peak. The best option would be an administrative license agreement, or lease, operation and management for each airport, with all kinds of operating income over a period of years, as this would generate many profits to the state, which could charge a fee for the grant, and an annual rate on income. It could also manage to reduce the cost of the operational fees at these airports and create more traffic. This proposal was made for hub airports, but with high prices, and companies interested in obtaining the administrative license were not willing to pay such prices because of the difficulty of getting the expected financial returns. Minor airports have a small number of passengers, from 1.3 million to 0.2 million, according to AENA (2012a). All of them have the characteristic of having alternative airports within the radius of its range, as the case of Vigo and A Coruña. All of them present budget deficits and improvement possibilities for operational efficiency as Tapiador and Matthew (2008) have noted. They seem to be ideal as airports operated under a low-cost philosophy, as they are near major cities, are not large enough to be interesting for the number of passengers managed in a traditional way, which would not be profitable. They also suit the needs of low-cost airlines. This would be the only option for them to avoid a budget deficit situation. so as before should be done by administrative licenses to operate and manage, and perhaps in this case does not have to pay a high amount for the initial license fee, and only a proportion of income, given that the low-cost airlines always avoid 777


fixed costs, but can take cost variables that are readily attributable to each passenger. In this group of airports permissiveness to change must be greater, and certainly those interested in these airports are totally different from those of the previous group. Since they can compete with the closest regional airports they can be a vital key to enhance market competition. Minor island airports, with the exception of La Palma, have very few flights and are fully deficient, but the service should be maintained as they are an essential means of communication for the population living in these areas. These services should be guaranteed and protected by the state. Thus, the attraction posed to private companies, which try to get some kind of profitability is negligible. In principle, they should remain managed by AENA. Finally those considered as “other airports”, which are those with fewer than 100,000 passengers per year, and which do not need any operation, since they have nearby airports and other communications media. Management strategy should be completely remodeled in this case since given their location they would not be interesting even for low-cost carriers. Their main function would have to change and instead of commercial aviation they would have to convert to cargo airports or sport aviation. All of them have very high deficits because of the services that need to be provided. Organizations that are interested in their exploitation should sign contracts for maintenance and management which do not represent a cost to AENA. In a situation in which no company is interested in their exploitation they should be considered as an infrastructure sunk cost and perform operational closure. In case any local or regional entity is willing to finance them, airport management should be transferred. With this proposed remodeling, Aena Aeropuertos SA remains an airport operator primarily responsible for performing oversight and negotiation of agreements with private companies, and a manager of airports where service must be guaranteed and cannot be operated privately. This could end the deficit problem and create a more competitive and optimized airport system, which would ultimately benefit the country as a whole.

5 Conclusions There is an urgent need to avoid the budget deficit in the operational management of airports, which is an option that may require private management which may also eliminate political interference. Since airport management is an area of particular importance it is not interesting to lose control and the best option to privatize management is reaching Public Private Partnerships agreements with companies interested in the exploitation. The airport network is extensive and diverse, so each airport has different levels of efficiency, and specific management strategies for each airport should be made. Within the network there are airports which 778


are interesting from a commercial standpoint and others with low or no interest, so different PPP arrangements should be made for each of them. Some may not even be possible to exploit in a privately profitable way. Agreements should be granted separately and to different organizations, in order to promote competition in the sector and not turn them into a private monopoly.

6 References AENA (2012a) Estadísticas de tráfico. Available at http://www.aena-aeropuertos.es cited 16 Dec 2012 AENA (2012b) Información sobre Aena Aeropuertos SA. Available at http://www.aenaaeropuertos.es cited 16 Dec 2012 Carmona M. (2010) The regulatory function in public-private partnerships for the provision of transport infrastructure. Research in Transportation Economics 30 (2010): 110-125 Foster C. (1984). Privatising British airports: What's to be gained. Public Money 3(4): 19–23 FEDEA, Fundación de Estudio de Economía Aplicada (2012) Taxonomía de los Aeropuertos Españoles. Available at http://www.fedea.net/transporte/ cited 15 Dec 2012 Galindo C. (2012) AENA contempla más subidas de las tasas aeroportuarias para aliviar la deuda. El Pais. 24 May 2012. Available at http://www.elpais.com cited 18 Dec 2012 Graham A. (2011) The objectives and outcomes of airport privatisation. Research in Transportation Business & Management 1 (2011) 3–14 Janecke H. (2010). Managing and delivering an airport privatization programme: Case study of the Republic of Congo. Journal of Airport Management 5(1): 10–18 Oum T., Adler N., Yu C. (2006) Privatization, corporatization, ownership forms and their effects on the performance of the world's airports. Journal of Air Transport Management 12(2): 109– 121 Preferente.com (2012) La salida a Bolsa de Aena se realizará “en uno o dos años”. 26 Jul. 2012. Available at http://www.preferente.com cited 18 Dec 2012 Ruiz de Villa A. B. (2012) Transporte Aéreo: Marco institucional. Publicaciones de la Escuela Técnica Superior de Ingenieros Aeronáuticos, Universidad Politécnica de Madrid Tapiador F.J., Mateos A., Martí-Henneberg J. (2008). The geographical efficiency of Spain’s regional airports: A quantitative analysis. Journal of Air Transport Management 14 (2008): 205– 212 Vogel H. (2006) Impact of privatization on the financial and economic performance of European airports. The Aeronautical Journal 110 (1106): 197–213

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Towards Strategic Project Management Hermano V1, Martín-Cruz N2. Abstract This paper focuses on the application of the Dynamic Capabilities framework to Project Management discipline. A review of project management literature illustrates the new project and project managers’ conceptualization and the shift towards a more strategic perspective. Commonalities and overlaps between project management and dynamic capabilities approach are highlighted both from a theoretical and professional point of view. The findings indicate the closeness between project management and dynamic capabilities by creating an integrative framework useful both for top and project managers. Besides, we show the potential benefits of the application of strategic management theories to Project Management.

Keywords: Project Management; Strategic management; Theoretical framework; Dynamic capabilities approach.

1 Introduction Since the 1950s, when it was recognized as a distinct discipline, project management has become a widespread practice in modern organizations (Whittington et al. 1999). In today’s turbulent and dynamic environments, traditional elements of business success – owning tangible assets, controlling costs, maintaining qualityare necessary but appears to be insufficient to obtain sustainable abnormal results (Teece 2007). In order to compete in this environment, organizations are increasingly shifting towards more-flexible project-based structures instead of rigid traditional ones (Whittington et al. 1999, Nohria 1996). Based on the report “New 1 Víctor Hermano Rebolledo ( e-mail: [email protected]) INSISOC Research Group. Department of Business Management and Marketing. Business School of Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid. 2

Natalia Martín Cruz (e-mail: [email protected]) INSISOC Research Group. Head of the Department of Business Management and Marketing. Business School of Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid.

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challenges for a land on expedition”, developed by the Deutsche Bank, in 2020, the “project economy” delivers 15% of value creation in Germany (Hofmann, Rollwagen & Schneider 2007). Moreover, project-based organizations (PBOs) have been considered to obtain better results, especially in unstable and dynamic environments (Huemann, Keegan & Turner 2007, Thiry, Deguire 2007, Melkonian, Picq 2011). This “projectification” process comes along with a paradigm shift in project definition. As Turner and Müller (2003) claim, the traditional conceptualization of project as an endeavor or task is unable to fully gather all roles, functions and limits of projects, therefore, this definition is just not enough. Nowadays, projects are conceived as organizations’ best drivers for change (Thiry, Deguire 2007, Turner, Müller 2003). Even more, some authors perceive projects as powerful strategic weapons initiated to create economic value and thus, being source of sustainable competitive advantages (Shenhar et al. 2001, Meskendahl 2010). Therefore, projects are conceived as central element for implementing companies’ intended strategy (Meskendahl 2010), and are nowadays defined as agencies for change, and even, as temporary organizations (Turner, Müller 2003, van Donk, Molloy 2008). Therefore, a paradigm shift seems to be happening and projects are becoming vectors of organizations’ strategy (Thiry, Deguire 2007). Although project management theory has been frequently recognized as predominantly implicit and practitioner-driving, in the last years, project management academics have increased their efforts in a new attempt to create a strong theoretical framework for project management discipline. Specifically, some authors claim that a cross-fertilization among strategy and project management could create great opportunities to enrich analysis and techniques in both disciplines (Meskendahl 2010, Grundy 1998). However, although project and strategic management have developed parallel, there is a gap between these disciplines both in theory and in practice (Thiry, Deguire 2007, Turner, Müller 2003, Meskendahl 2010, Grundy 1998). A review of strategic management literature shows that Project Management does not appear as a keyword for papers nor for conferences (Thiry, Deguire 2007). Project management as a research topic is confined to specific project management journals such as the PMI Project Management Journal, or the IPMA International Journal of Project Management. This paper works, first, on the conceptualization of projects as temporary organizations, and the importance of PBOs as flexible organizational forms well prepared for competing in today’s turbulent environment. Therefore, the objective of this paper is to close the gap between project and strategic management. Specifically, we claim that project management constitutes a dynamic capability which helps PBOs to adapt to rapidly changing environments. We seek to show the potential convergence between dynamic capabilities and project management by providing a framework for the consideration of project management as a dynamic capability both from a theoretical and a professional point of view. Thus, we shed

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light on the need to find the fundamentals that allow for an explanation of PBOs as a superior form of organization.

2 From Project Management to Project-Based Organizations Traditionally, organizations formed temporal project teams inside their functional structure in order to deal with specially challenging operations (e.g. new products development; commissioning of a new procedure; etc.) or to respond to rapidly changing market conditions (Irja 2006). Projects were understood as temporal endeavours undertook to achieve a particular objective. Classic project management literature was only concerned for the critical success factors in project operations, while in a more professional side, the concerns focused on professionalizing project management techniques (Melkonian, Picq 2011). All these efforts were oriented to secure single project success. However, in a more and more complex and uncertain environment, undertaking successful projects has been recognized as necessary but no longer sufficient strategy to secure long term and sustainable performance (Melkonian, Picq 2011). Thus the focus has been shifted from individual projects to portfolios, and a new area of practice, known as Project Portfolio Management, has appeared (Melkonian, Picq 2011). The key point in project portfolio management is not to secure single project performance but to create structures able to optimize the use of resources among many projects and thus, allowing organizations to efficiently coordinate collections of projects (Thiry, Deguire 2007). Furthermore, nowadays project management literature has adopted an even more strategic perspective since the focus has moved from project portfolio management to the organizational level -PBOs (Melkonian, Picq 2011). Scholars claim that organizations carrying out their core operations mainly in project form -PBOs- could obtain better results in dynamic environments (Thiry, Deguire 2007, Melkonian, Picq 2011). Although profusely cited, the concept of PBO, also cited as project-oriented company, project-based firm, and p-form organization; is not without controversy. There is one literature stream emerging from Hobday’s seminal paper (2000) that identifies PBOs as those organizations executing projects in industries focused on complex industrial products and systems. These PBOs are intrinsically innovative as they continually reorganize their structure around the demands of each project and to changing client needs. Thus, these PBOs are very flexible and able to cope with project uncertainties and risks (Hobday, 2000). However, these PBOs suffer when company projects are not independent from each other. Specifically, these PBOs are weak in coordinating cross-project resources and promoting organizational knowledge and learning. Moreover, these PBOs could promote individual project objectives over the overall organization goals.

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Scholars have recently suggested that only PBOs capable of developing project capabilities would we able to overcome the dichotomy among the individual nature of projects and the long-term and stable objectives of the overall organization’s strategy (Melkonian, Picq 2011). Project capabilities are defined as the internal ability of a PBO to create lasting performance based on multiple short term projects (Davies, Brady 2000). Following Hobday (2000, p.874), a PBO is one in which the project is the primary unit for production organization, innovation, and competition, and project management is the main source for capabilities and knowledge formation. For the purpose of this paper, we define PBOs through a translation of Hobday’s (2000) ideas into the dynamic capabilities approach. Unlike earlier approaches (e.g. Porter’s competitive forces framework, or the resource-based view) which are static in nature, from the dynamic capabilities approach organizations obtain superior performance not just because of their assets endowment but through their ability for reconfiguring their competences to address rapidly changing environments –dynamic capabilities- (Teece, Pisano & Shuen 1997: 516). Drawing on the dynamic capabilities approach, we define PBOs as those where project capabilities shape not just project management processes but all internal and external competences of the organization. In a PBO, project (dynamic) capability represents the mechanism for integrating, building and reconfiguring organizational competences, so project (dynamic) capability constitutes the main source for a competitive advantage.

3 Project Management and Dynamic Capabilities: Implications from a Professional Perspective The cross-fertilization between dynamic capabilities approach and project management can be extended to a professional perspective to give theoretical meaning to the guidelines offered by the different global project management standards such as the well-known PMBOK®. In the following, we interpret the PMBOK®’s processes and indications throughout the dynamic capabilities theoretical framework. We focus on the main components and routines of dynamic capabilities and the guidelines provided by the PMBOK® for dealing with them. PMBOK® defines project management as the application of knowledge, skills, tools and techniques to project activities to meet the project requirements (Project Management Institute 2008). Furthermore, it recognizes that project management is accomplished through the appropriate application and integration of 42 processes. The observation of PMBOK®’s definition of project management as a collection of processes reminds to the definition of organizational capabilities given by Winter (2003) -collection of routines that confers a set of decision options for pro-

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ducing significant outputs -3. Although there are some authors claiming that the temporary nature of projects makes it difficult to develop routines so making also difficult to develop dynamic capabilities (Hobday 2000), recent research has shown that PBOs have viable alternatives both individual (e.g. managers of competencies) and collaborative (e.g. industry-wide social networks) by which they can create routines and distribute social learning (Cacciatori 2008). Therefore, and based on the work of Winter (2003) we consider organizational project capabilities as collection of routines that can be clarified through the study of the 42 processes (routines) contained in the PMBOK®. Regarding the components of dynamic capabilities and for the purpose of this paper, we assume the framework established by Teece et al. (1997) in their seminal paper where dynamic capabilities possess three different roles coordination/integration, learning, and reconfiguration/transformation (Teece et al. 1997). The first one, coordination/integration refers to the tasks managers perform for coordinating and integrating activities inside the firm and also for the coordination of external activities and technologies (Teece et al. 1997, p.518). The PMBOK® possess a whole chapter (chapter four) dedicated to project integration management in which the integration role is defined as the processes (routines) and activities needed to identify, define, combine, unify and coordinate the various processes and project management activities within the Project Management Process Group (Project Management Institute 2008). Processes in that chapter detail how to develop the project management plan, how to direct and manage project execution or how to monitor and control project work. Regarding the second role, learning, is defined as a process (routine) by which repetition and experimentation enable tasks to be performed better and quicker (Teece et al. 1997, p.520). By learning, firms recognize dysfunctional routines and prevent strategic blind spots. The learning role is a prevalent concept in the PMBOK®. Practitioners claim that after developing a project, the implementing organization and actors must have learned something, and the PMBOK® includes that idea by including document lessons learned as a task to perform during project closing. Finally, the reconfiguration/transformation role refers to the need to reconfigure the organizational asset structure to address environmental changes (Teece et al. 1997, p.520). The PMBOK® establishes the concepts of rolling wave of planning and progressive elaboration as two principles when developing project planning. Those two concepts refer to the process of making the project plan in successive waves as the project proceeds and later details become clearer. Moreover, PMBOK® suggests to create change requests as an output of almost all of its 42 processes. These change requests refer to modifications in project procedures, policies or documents that are requested by the project team due to issues found while project work is being performed. PMBOK® also advise project managers to perform the 3

Zollo and Winter (2002) define routines as stable patterns of behavior that characterize organizational reactions to variegated, internal, or external stimuli (p.340).

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task called integrated changed control by which project managers have to review all change requests, and manage changes to deliverables, organizational process assets, and project documents and plans. Teece et al. (1997) recognizes that both the firm asset endowment –positionand the strategic decision history –path- affect firm’s processes and so firm’s dynamic capabilities. In this sense, the PMBOK® offers guidance for dealing with both position and path of the firm. In almost all of its 42 processes (routines), the PMBOK® include two inputs called enterprise environmental factors and organizational process assets which refer to firm’s heritage and firm’s asset endowment respectively. Finally, an important aspect of dynamic capabilities is the commonalities/firmspecific duality. Dynamic capabilities are not exactly the same across firms even though they present common features and can be understood as best practices (Eisenhardt, Martin 2000). This duality is recognized by project management practitioners. On the one hand, the PMBOK® identifies the processes (routines) configuring the subset of the project management body of knowledge generally recognized as good practices. However, the PMBOK® itself notifies that the knowledge it describes, should not always be applied uniformly to all projects. Delving into this idea, the Project Management Institute has developed extensions of the PMBOK® like the construction extension of the PMBOK® or the government extension to the PMBOK® to provide more information on specific project types or industry information.

4 Conclusions, Implications, and Direction for Future Research This paper highlights that the new conceptualization of both projects and project managers is imbued with strategic essence. Project management literature focus on achieving success for the lonely project is being substituted by papers claiming that projects should be understood in relation to previous projects, future plans and the environment surrounding the implementing organization (Engwall 2003). Drawing on the dynamic capabilities approach we consider a PBO as an organization where project capabilities shape not just project management processes but all internal and external competences of the organization. By considering project management as a dynamic capability we offer an explanation of the better results PBOs are considered to obtain in dynamic and unstable environments (Thiry, Deguire 2007, Melkonian, Picq 2011). Thus, we show that dynamic capabilities and project management as well as project and top managers are much closer than what professionals of both disciplines believe. We claim that project management dynamic capability constitutes a source of competitive advantage for PBOs. From the project management point of view, the cross-fertilization first provides a strong theoretical framework, the dynamic capabilities approach, for the 785


project management discipline. A strong theoretical foundation is recognized as missing for the project management discipline (Turner, Müller 2003, Pollack 2007) and as one of the most important obstacles for the project management progress (Koskela, Howell 2002). Thus, we strengthen the incipient project management theoretical framework with the explanatory power and theoretical foundations of the dynamic capabilities approach. We also claim that dynamic capabilities foundations could be useful to face project management problems such as frequent project failures or slow rate of methodological renewal (Koskela, Howell 2002, Kharbanda, Pinto 1996). Specifically, the issue of project failure has been studied through the traditional CSFs – typically attached to the iron triangle, and through single project case studies focused on technical aspects. However, recent studies have demanded to focus on managerial aspects instead of technical ones, since for many cases, the root of failure is constituted by issues such as the decision-making process (Shepherd, Patzelt & Wolfe 2011). Finally, this paper suggests wide-ranging opportunities for future research. First of all, taking the dynamic capabilities as research background scholars could research the conditions under which the project management processes become dynamic capabilities. Secondly, once recognized that project management could be understood as a dynamic capability, the next step is to look empirically at the benefits that project management dynamic capabilities provide to the organizations possessing and developing it and their role as source of competitive advantages. One possible stream of research, following the path initiated by Thomas and Mullaly (2008), could focus on the measurement of the value created by project management application.

5 References Cacciatori, E. 2008, "Memory objects in project environments: Storing, retrieving and adapting learning in project-based firms", Research Policy, vol. 37, no. 9, pp. 1591-1601. Davies, A. & Brady, T. 2000, "Organisational capabilities and learning in complex product systems: towards repeatable solutions", Research Policy, vol. 29, no. 7-8, pp. 931-953. Eisenhardt, K.M. & Martin, J.A. 2000, "Dynamic capabilities: what are they?", Strategic Management Journal, vol. 21, no. 10-11, pp. 1105-1121. Engwall, M. 2003, "No project is an island: linking projects to history and context", Research Policy, vol. 32, no. 5, pp. 789-808. Grundy, T. 1998, "Strategy implementation and project management", International Journal of Project Management, vol. 16, no. 1, pp. 43-50. Hobday, M. 2000, "The project-based organisation: an ideal form for managing complex products and systems?", Research Policy, vol. 29, no. 7-8, pp. 871-893. Hofmann, J., Rollwagen, I. & Schneider, S. 2007, "Deutschland 2020–New challenges for a land on expedition", Current Issues.Deutsche Bank Research.Frankfurt am Main, .

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Huemann, M., Keegan, A. & Turner, J.R. 2007, "Human resource management in the projectoriented company: A review", International Journal of Project Management, vol. 25, no. 3, pp. 315-323. Irja, H. 2006, "Project management effectiveness in project-oriented business organizations", International Journal of Project Management, vol. 24, no. 3, pp. 216-225. Kharbanda, O.P. & Pinto, J.K. 1996, What Made Gertie Gallop?: Lessons from Project Failures, Van Nostrand Reinhold. Koskela, L. & Howell, G. 2002, "The underlying theory of project management is obsolete", Proceedings of the PMI Research ConferencePMI, , pp. 293. Melkonian, T. & Picq, T. 2011, "Building Project Capabilities in PBOs: Lessons from the French Special Forces", International Journal of Project Management, vol. 29, no. 4, pp. 455-467. Meskendahl, S. 2010, "The influence of business strategy on project portfolio management and its success — A conceptual framework", International Journal of Project Management, vol. 28, no. 8, pp. 807-817. Nohria, N. 1996, From the M-form to the N-form: Taking Stock of Changes in the Large Industrial Corporation, Division of Research, Harvard Business School. Pollack, J. 2007, "The changing paradigms of project management", International Journal of Project Management, vol. 25, no. 3, pp. 266-274. Project Management Institute 2008, A Guide to the Project Management Body of Knowledge, 4th edn, Project Management Institute, USA. Shenhar, A.J., Dvir, D., Levy, O. & Maltz, A.C. 2001, "Project success: a multidimensional strategic concept", Long range planning, vol. 34, no. 6, pp. 699-725. Shepherd, D.A., Patzelt, H. & Wolfe, M. 2011, "Moving forward from project failure: Negative emotions, affective commitment, and learning from the experience", Academy of Management Journal, vol. 54, no. 6, pp. 1229-1259. Teece, D.J. 2007, "Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance", Strategic Management Journal, vol. 28, no. 13, pp. 13191350. Teece, D.J., Pisano, G. & Shuen, A. 1997, "Dynamic capabilities and strategic management", Strategic Management Journal, vol. 18, no. 7, pp. 509-533. Thiry, M. & Deguire, M. 2007, "Recent developments in project-based organisations", International Journal of Project Management, vol. 25, no. 7, pp. 649-658. Thomas, J. & Mullaly, M. 2008, "Researching the value of project management", Project Management Institute, . Turner, J.R. & Müller, R. 2003, "On the nature of the project as a temporary organization", International Journal of Project Management, vol. 21, no. 1, pp. 1-8. van Donk, D.P. & Molloy, E. 2008, "From organising as projects to projects as organisations", International Journal of Project Management, vol. 26, no. 2, pp. 129-137. Whittington, R., Pettigrew, A., Peck, S., Fenton, E. & Conyon, M. 1999, "Change and complementarities in the new competitive landscape: A European panel study, 1992-1996", Organization Science, , pp. 583-600. Winter, S.G. 2003, "Understanding dynamic capabilities", Strategic Management Journal, vol. 24, no. 10, pp. 991-995. Zollo, M. & Winter, S.G. 2002, "Deliberate learning and the evolution of dynamic capabilities", Organization science, , pp. 339-351.

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Analysis of Common Maturity Models Applied to Project Management Montero G1 Abstract The application of maturity models to the Project Management may help organizations to integrate this methodology into their culture. This article tries to show the main current models, identifying their relevant aspects. Due to the low project management culture in most organisations, a mix of both of them is proposed.

Keywords: Project Management, Maturity Models, Maturity Scales.

1 Introduction Several organizations are realizing the importance of integrating Project Management into their organizational culture. Project Management itself is constantly evolving as a discipline of knowledge. This article attempts to analyze the more usual project management maturity models that currently organizations use.

2 Origin of Maturity Models and Its Application to Project Management The origin of process maturity concept was born into Total Quality frame (CookeDavies et al., 2001), where application of process control techniques showed that the increase of maturity had two consequences: Variability reduction inherent in the process. 1Guillermo

Montero Fernández - Vivancos ( e-mail: [email protected]) Dpto. de Organización Industrial y Gestión de Empresas II. Escuela Superior de Ingeniería. Universidad de Sevilla. Avenida de los Descubrimientos S/N, 41092 Sevilla.

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Increase of the process performance. Crosby (1979) presents a five increasing levels of maturity for the concept of quality in organizations. One of the best references about the maturity scale model is PPORF Method (Practical Program Of Revolutions in Factories) and was created by Iwao Kobayashi (1995). This describes 20 “Keys” that are crucial to develop a world class company. Other example of the model application is the KCG 20 Keys (Lareau, 2002), that considers maturity stages applied to any organizational area. After the origin, for extension this idea spreads to software organizations through Capability Maturity Models and developed by Software Engineering Institute (SEI) of the Carnegie-Mellon University between 1986 and 1993 (Paulk et al. 1993). This concept of process maturity progresses as the organizational process maturity. The model, called Capability Maturity Model Integration (CMMI®), establishes a scale of five stages to maturity: initial level, repeatable level, defined level, managed and optimized level. These five levels correspond to an ordinal scale to measure process maturity and capability of software organizations. In the 90, some of these models were developed, such as the Maturity Map created by McCauley (1993), Microframe Technologies' Model, which provide the framework for the capability analysis (Remy, 1997) or those developed by Ibbs and Kwak (1997) or Kerzner (2001). The Project Management Institute, PMI, created in 2001 a standard for the organizational maturity in the Project Management, named OPM3TM (Schlichter, 2001) and launched in December 2003. Another example for the maturity model application in Project Management is (PM)2, that integrates the previous project management practices and maturity models to increase their effectiveness (Kwak et al., 2002). The concept of project management maturity gained considerable traction in the early 2000s. Also the UK’s Office of Government Commerce (OGC) developed two models: firstly, the Portfolio, Programme and Project Management Maturity Model (P3M3©) in 2004 and then the PRINCE2™ Maturity Model (P2MM©) in 20052006, that is a derivation from the first one.

3 Main Project Management Maturity Models There are lots of models available that different organizations use. Herewith, five core existing models are considered:  Capability Maturity Model Integration (CMMI®) 789


 PRINCE2™ Maturity Model (P2MM©)  Portfolio, Programme and Project Management Maturity Model (P3M3©)  Organizational Project Management Maturity Model (OPM3®)  IPMA Project Excellence Model The table 1 shows the main aspects related to this five models. Table 1 Main aspects of Project Management Maturity Models. Maturity Model

Sector

Scope

Levels

Self-assessed

Facilitatorled

Acreditation

Software and systems engineering

22 process areas

5 levels

Yes

No

Yes

CMMI® Software and Continuous systems engineering

22 process areas

5 levels

Yes

No

Yes

P2MM©

All

PRINCE2 key aspects

5 levels

No

Yes

Yes

P3M3©

All

32 process aspects

5 levels

No

Yes

Yes

OPM3®

All

Best practices 4 levels for projects, portfolios and programmes

Yes

Optional

No

OPM3® All ProductSuite

Best practices 4 levels for projects, portfolios and programmes

No

Yes

Yes

PEM

9 criteria and 100 points Yes 22 subcriteria

Yes

No

CMMI® Staged

Only projects

3.1 Capability Maturity Model Integration (CMMI®) The Capability Maturity Model Integration (CMMI ®), owned by Software Engineering Institute (SEI), is oriented to software and systems engineering. This model probably is the most used, but with the drawback of the implementation framework to this specific sector. This model focuses on ‘what’ needs to be done, rather than ‘how’ it should be done. It has three versions: for developers, for Acquisition and for services. In this last one, it presents 24 process areas, and each process area has a set of goals and practices associated with them. In this case, the model presents two different representations: stages and continuous. The first one has five levels of maturity, from 1 to 5, in the process areas. 790


In the second representation, the model assess against a capability scale from 0 to 5.

3.2 PRINCE2™ Maturity Model (P2MM©) The PRINCE2™ Maturity Model (P2MM©) is owned by the UK’s Office of Government Commerce (OGC) in 2005-2006, as a derivation from its other model, Portfolio, Programme and Project Management Maturity Model (P3M3©). P2MM© does not itself contain detailed descriptions of the activities needed to support project management processes, then the model needs for its application that the PRINCE2™ would be considered. This model is a hierarchical one, which describes the key elements of the PRINCE2™ method that need to be embedded within an organization to achieve a certain maturity level. Each level focuses on a set of key process areas, each process area being unique to a specific level of the model and underpinning achievement of higher levels of maturity. Probably the main benefit of this model for organizations the strength evaluation within the PRINCE2™.

3.3 Portfolio, Programme and Project Management Maturity Model (P3M3©) The Portfolio, Programme and Project Management Maturity Model (P3M3©) is owned by the Office of Government Commerce (OGC) and was developed in 2004 to build programme and portfolio maturity elements into an existing project management maturity model. The P3M3© is essentially a set of structured descriptions of some 32 processes that span project, programme and portfolio management e.g. project definition, risk management and quality management. The process descriptions are allotted within the document structure to five different maturity levels from the lowest ‘Initial Process’ through ‘Repeatable Process’, ‘Defined Process’ and ‘Managed Process’ to the highest ‘Optimised Process’.

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3.4 Organizational Project Management Maturity Model (OPM3®) The Organizational Project Management Maturity Model (OPM3 ®) is a standard owned by the Project Management Institute (PMI) and was launched in 2003 to help organizations align diverse aspects of their operations with their overall business strategy. The standard defines globally developed and recognised industry ‘best practices’ that are necessary in each of these three domains, and the incremental ‘capabilities’ that are prerequisites to each ‘best practice’. Both the term ‘best practice’ and the term ‘capability’ are defined within the standard. The degree to which each ‘capability’ is practiced is defined in terms of one of four stages of process improvement: standardised, controlled, measured or improved. Also, the model considers the PMBOK® Guide in the implementation the project management maturity. One advantage of this model is its scalability, its relationship with PMBOK ® and the number of organizations that use it.

3.5 IPMA Project Excellence Model The Project Excellence Model is owned by the International Project Management Association (IPMA) and was developed in 1996 by the German Project Management Association from the European Foundation for Quality Management (EFQM) Excellence Model. The Project Excellence Model provides a framework for assessing how well a project team is delivering, or has delivered a project. It has nine criteria related to project excellence. Also, it has two different blocks: project management and project results. Each criteria is divided into several sub-criteria, for a total of 22 subcriteria. Each of these is described in a way that allows actual activities and results to be assessed. In order to evaluate the excellence of the project, each sub-criteria is scored from 0 to 100. Each sub-criteria is weighted within its criteria. The assessment is completed by the individual analysis of each criteria and the weighted sum of all. The great disadvantage of this model is its focus exclusively on individual projects, rather than penetration of project management in the corporate culture.

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4 Conclusions to Be Considered in Organizations without Project Management Culture Most of organizations do not consider the Project Management in their own culture. In a first analysis, with a representative sample of SMEs, none uses any project management methodology. In order to apply a maturity model to implement project management, the five previous ones are at a much higher level to develop a culture of project management in this business structures. Taken into account the CMMI®’s maturity scale for the staged representation, the levels are: Initial: Processes are ad hoc, unpredictable and reactive Managed: Basic processes are in place but may be different by project Defined: Processes are in place based on organisational standard models Quantitatively Managed: Processes are measured and controlled Optimising: Process improvement is a continual focus The analyzed organizations, which have not adopted process improvement programmes, are at level 1 and progress through the levels of maturity by adopting the goals and practices which are defined for the processes at each level. This model CMMI®, as well as P2MM©, P3M3© and OPM3®, are somewhat complex to establish goals to implement the project management culture. Although, the proposed scale can be used. There is another model, called Programme Management Maturity Model (PMMM) and developed by two of the APM Programme Management (ProgM) specific interest group officers, Paul Rayner and Geoff Reiss, that can be used as base for the scale application. This model examines programmes using ten key aspects of programme management and is linked to the Programme Management Improvement Process that provides a guide to improving maturity across these areas. An organization could identify its strengths and weakness in programme management maturity in comparison with other ones. The ten aspects of programme management covered by PMMM are: Management organisation Planning Management of benefits Management of stakeholders Issue and risk management Quality management and auditing Configuration management Internal communication Programme accounting and finances Scope and change 793


5 References Cooke-Davies TJ; Schlichter F. et al. (2001), ‘Beyond the PMBOK Guide’, PMI Annual Seminars and Symposium 2001, Nashville TS. Crosby PB, (1995) Quality is free: The art of making quality certain. New York: Penguin, 1979. Kobayashi, Iwao: 20 keys to workplace improvement. Portland, Ore: Productivity Press. 291 p. Lareau W (2002) Office Kaizen: Transforming Office Operations into Strategic Competitive Adventage. Milwaukee: ASQ Press. 184 p. Paulk M, Curtis C et al. (1993) Capability Maturity Model for Software (Version 1.1). Carnegie Mellon University, Software Engineering Institute. Downloaded from www.sei.cmu.edu/pub/documents on 10 April 2001. McCauley, M (1993) ‘‘Developing a project-driven organization’’ PM Network, September, 1993, p. 26 –30. Remy, R. (1997) ‘‘Adding focus to improvement efforts with PM3.’’ PM Network, July, 1997, p. 43– 47. Ibbs WC, Kwak, YH (1997). The benefits of project management. Financial and organizational rewards to corporations. Philadelphia: PMI Educational Foundation. Kerzner H (2001) Strategic planning for project management using a maturity model. New York: John Wiley & Sons. Schlichter J (2001) PMI’s organizational project management maturity model: emerging standards. PMI ’01 Annual Symposium, Nashville. Kwak YH; Ibbs W (2002) “Project Managemente Process Maturity (PM)2 Model”. Journal of Management in Engineering. July 2002. PROJECT MANAGEMENT INSTITUTE INC. (2010) PMBOK® Guide. 5Th Edition. Newtown Square, Pennsylvania: Project Management Institute, Inc. ASSOCIATION FOR PROJECT MANAGEMENT (2007) Models to improve the management of projects. APM. High Wycombe (UK). 55 p.

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Patterns in Innovative Companies in Rio de Janeiro (Brazil) Canós-Darós L 1, Santandreu-Mascarell C, Marin-Garcia JA, García-Sabater JJ Abstract In this paper we present the relationship between the generation of ideas and knowledge, organizational structure and information and communication technologies existing in the company. First, we present an integrated model as a basis to identify best practices that facilitate and encourage innovation. Then, we use grounded theory methodology, applied to one region with innovative entrepreneurial tradition and a service-based industry as Rio de Janeiro (Brazil).

Keywords: Organizational Structure, Ideas and Knowledge Management, Innovation, Grounded Theory, ICT.

1 Introduction: Innovative Capability and Flexibility We can found several definitions of innovation in the literature. In this paper we focus on innovative capability within the context of organizational agility, defined as an organizational capability that enables companies to be "infinitely adaptable and innovative without changing" (Dyer and Shafer, 1999:148). Moreover, Amabile et al. (1996) assume that the organizational context influences on the level and frequency of the innovative behavior of a company. Therefore, they define the innovative capacity as the ability to successfully implement new ideas in the company; they measure it according to the mechanisms that stimulate the flow of innovative ideas, for example, organizational structure and knowledge management. 1Lourdes Canós-Darós ( e-mail: [email protected]) ROGLE-Departamento de Organización de Empresas. Universitat Politècnica de Valencia. Camino de Vera s/n. 46022 Valencia.Spain.

* This paper has been partially supported by the projects CORSARI MAGIC DPI2010-18243 Ministerio de Ciencia e Innovación del Gobierno de España, TIN2008-06872-C04-02/TIN – Ministerio de Educación y Ciencia del Gobierno de España and PIME2013-A16 and PAID-0512-SP20120480 – Universitat Politècnica de València.

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This concept includes flexibility as a dynamic capability (Damanpour, 1991; Li and Atuahene-Gima, 2001). Flexible practices act both on people while maintaining and increasing their value and specificity, as on organizational capabilities (Lado and Wilson, 1994; Lepak and Snell, 1999). In that sense, flexible companies are those that change their internal structures without undergoing traumatic changes. Internal flexibility is associated with the search for new organizational structures that, in general, are characterized by hierarchical designs switch to more decentralized designs (Balogun and Johnson, 2004; Barkema et al., 2002). Therefore, this kind of flexibility is associated with the concept of functional flexibility that allows a company to change its structure and the nature of work to better respond to new contingencies (Atkinson, 1984; Lepak et al., 2003). In this vein, authors such as Van den Bosch et al. (1999) argue that the scope, flexibility and efficiency of the assimilation of knowledge depends on the company's organizational structure (functional, divisional or matrix). Others consider a flexible organizational structure as a strategic factor in the field of knowledge management (Forés and Camisón, 2008; Mas and Martinez, 2008). However, there are few studies that specify how this organizational structure affects the subsequent exploitation of knowledge generated by people, based on the information and the development of ideas that can lead to innovations. Therefore, our interest is in determining what forms of work or good practices based on the organizational structure allow the company to be agile and flexible. Information and Communication Technologies (ICT) complement and promote this, facilitating the necessary flow of information for the outcrop of ideas that will be transformed into knowledge. In this context, innovation is the final result of the creative activity of individuals in the organization (Perry-Smith and Shalley, 2003; Taggar, 2002; Tang, 1998), so that the kind of skills of workers conditions the company’s innovative capacity. High levels of competences and knowledge are required for these employees (Li et al., 2009). Consequently, we ask the following questions: What is the relationship between organizational structure, ICT and ideas and knowledge management in an innovative company? Are they a source of innovation?

1.1 Innovation, Organizational Structure, Ideas and Knowledge Management and ICT Organizational structure can be defined as the way in which the set of relationships (jobs, tasks, authority and decision flows) are ordered in a company by taking into account an appropriate level of communication and coordination between the people; evidently, this influences in information flows. It requires a continuous learning. This implies organizational changes that result in the coordination of 796


new ways of working, to achieve and maintain competitive advantage. An organizational structure should facilitate and enhance the selection, formulation and implementation of innovation strategies. Thus, organizational designs have evolved and changed from linear to network models (Velasco and Zamanillo, 2008). We want to point out that there is not a unique organizational structure that encourages innovation because this fact depends on other factors as the type of company, size, industry configuration and access to resources (Mintzberg, 1989). In this sense, business strategy should be focused on the identification and satisfaction of customer’s needs. This process has to be conceived from an intelligent organizational structure to acquire, create, develop, build and share continuous ideas and new knowledge in a dynamic process (Nonaka and Takeuchi, 1995). Also the generation of ideas and knowledge management has become critical factors for achieving and maintaining competitive advantage (Grant, 1996; Nonaka, 1994). An optimal use of ICT facilitates the flow of ideas and knowledge. ICT is a set of techniques, developments and advanced devices that integrate functions of storage, processing and transmission of data to be transformed into information (Baskerville et al., 2013). Both organizational structure and ideas management system have to be integrated through information systems based on ICT. We define information system as a set of procedures to manage the company’s information (Baskerville et al., 2013). It allows the collection of relevant data to process them properly in order to transform them into information, store information that can be useful and provide it to the decision makers in due time. Keep in mind that the distribution of ideas and knowledge is a central criterion in organizational design. Information is the key for good decision making, so it is necessary to consider its importance, nature, where and how it is produced, transfer costs, etc. Development of ICT has overcome, at least partially, the problem of the information location in different places. Moreover, ICT allow information to be available on line and at a relatively low cost (Laud and Thies, 1997; Tsoukas, 1996), what leads to some authors to identify new organizational design trends linked to ICT. However, there are multiple matches in many of these proposals, which may denote the possibility that different terms have being used to describe the same or similar organizational form (Hodge et al., 2002). What is clear is the existence of a change in the coordination activities mechanism, moving from direct supervision to normalization of results. Thus, it can be said that the debate on the efficient degree of centralization is enhanced by studying the impact of ICT (Malone, 1997; Wilson, 1999). As we can see, the development of ICT is affecting the way to work in companies, resulting in people the need to uncover new abilities, skills and competences. ICT affect jobs and communication and coordination relations. They also boost new information circuits to create and share ideas and knowledge, a main step for innovation. Ideas and knowledge management causes information flows, their analysis and the distribution to people who need it at the due time to be useful for decision making. Then, organizational structure design should focus on the collection, pro797


cessing and effective use of information to contribute to company performance. Consequently, companies and employees have to accept changes. In addition, some authors justify how competences and human resource management practices are related to the possession of certain organizational capabilities (Barney and Wright, 1998; Pfeffer, 1994), and how innovation and management tools are used to increase benefits (Albaladejo et al., 2009; Libaers et al., 2009).

1.2 Integrated Model of Organizational Structure and Management of Ideas (IMOSMI) In this context, we define an integrated model that relates information flows with generation of ideas and knowledge management under the organizational structure. The information and the knowledge are possessed by the persons who transform them into capacities and competences from which ideas arise to give place to innovations for improving the competitiveness and managerial productivity in the company. (see Figure 1).

Fig. 1 Integrated Model of Organizational Structure and Management of Ideas (IMOSMI)

This model aims to improve the effectiveness, efficiency and competitiveness of companies by implementing different good practices (concreted in the next section of this paper) that leads to innovation. The basis of this model is that companies must have an organizational structure and an ideas and knowledge management system that facilitate and encourage innovation by using ICT to share information between people (Santandreu and Canós, 2010). Their characteristics, which we can also consider as ways of working practices, can be synthesized in a flexible organizational structure. 798


2 Innovative Companies in Rio de Janeiro region To identify good practices arising from ideas and knowledge management covered in the organizational structure and in the information systems of the company, we use a qualitative methodology: grounded theory. This methodology is appropriate in this case since the subjects themselves are part of the object of study and because both variables and results have to do with the behavior and the human relationship. Grounded theory generates a conceptual inductive model; that is, from the observation of the real world, some hypotheses are developed to construct the theory. Thus, the researcher reaches general conclusions from a particular environment, from the experience of the studied subjects (Glaser, 2002). Thus, the process of grounded theory can be summarized as follows (Murillo and Lozano, 2006): 1. Collection and analysis of data are concurrent; 2. Data determine processes and products of research rather than preconceived theoretical frameworks; 3. Analytical processes give rise to the discovery and new theoretical development, not only verify already known theories; 4. Sampling is based on partial results emerging from the data. It is called theoretical sampling and is useful to refine, develop and complete categories; 5. The systematic use of analytical procedures leads to more abstract levels of analysis. A key feature is the circularity of the process. According to Glaser and Strauss (1967), although this method is a continuous growth process (each stage after a while turns into the next), previous stages remain operational throughout the analysis and provide ongoing development at the following stadium until the analysis is completed. This means that in this method there is an entanglement of data collection, coding, analysis and interpretation of information throughout the process, which, in some way reflects the holistic nature of qualitative research. Following this methodology, individual results are compared to each other and see if there are matches that allow the generalization of results to all individuals. Then, some categories or patterns can be established, in our case, they can be considered as good practices emerging from organizational structure, ideas and knowledge management, and ICT, leading to innovation. This exploratory study can be stated in three steps: 1) data collection; 2) sample selection; 3) data processing. To collect data we designed a semi-structured interview based in the literature revision, consisting of five parts comprising three objectives: 1) to determine the organizational structure to identify what type of structure is used; 2) to know if innovation is developed in the company, what type and how to determine if any innovation process exists; 3) to know how information, ideas and knowledge are managed and if a model exists. The interview was conducted with the CEOs of 14 innovative companies from different industries located in the region of Rio de Janeiro (Brazil). In this sense, and according to Bierly and Daly (2007), the inclusion of companies from different industries provides a global view, which is very convenient since this is an exploratory research. 799


A feature of grounded theory is that the sample is not known at the beginning of the analysis (García-Sabater and Marín-García, 2009). This is because the constant comparative method implies that as the interviews are conducted, and data are processed, in our case, by using Atlas.ti software. The process finishes when information is saturated, that is, when new data add no additional value. In the case of Rio Janeiro 14 interviews in total were conducted. In the experiment, interviews took two hours on average. They were recorded and transcribed into a text file, used in Atlas.ti software as a primary document. Then, codes are individually generated by searching for patterns that emerge from the study data. Atlas.ti groups those repeated codes, matching the ones common to the sample. The codes are categories or patterns, where theory is generated from, establishing possible relationships between them. Thus, we have identified common good practices to these innovative companies. Brazilian results show 34 good practices related to the organizational structure, ideas and knowledge management, and ICT, being all of the areas potential sources of innovation. Categories, patterns or good practices are 34 in total: constant search of information, external partners, organizing committee, share knowledge, share information, competitiveness, communication, confidence, creativity, quality, culture, clear definition of objectives, strategy, experience, administrative flexibility, training, intranet, investment and development, continuous improvement, mission, motivation, multidisciplinary, patents, workers profile, publication, HR recognition, social networking, regular meetings, information systems, innovation systems, sustainability, differentiated work, group work, project work, technology transfer and vision. As we can see, all are related with the organizational structure, ideas and knowledge management and/or ICT.

3 Contributions and Future Research The first contribution of this presentation is the creation of an integrated model (IMOSMI) considering organizational structure and management system of ideas and knowledge, all connected by a correct use of ICT, taking into account agility, flexibility, or innovative capabilities, among other corporative characteristics. The second contribution is the development of an experiment in some innovative companies in Rio de Janeiro (Brazil) to identify good practices included in IMOSMI. For this, grounded theory has been used. A deeper reflection about these results and its relations has to be made in future papers. In this sense, the implementation of some or all the identified good practices by managers who want to innovate would be proposed to contrast the results. Moreover, we want to analyze the financial statements of innovative companies in order to see how they reflect results or follow any particular model that can be found in the literature. In this context, diagnosed good practices competences in 800


business become the link with the University. Today, European Higher Education Area is moving to a teaching-learning process based on competences. Students will be competent professionals who have adequate ideas, knowledge, skills and attitudes to practice a profession. An example about the match between competences described in study plans and the real demand of employees can be found in Santandreu et al. (2011).

4 References Albaladejo M, Canós L, Maurí J, Ramón F (2009) Classification of the Innovation Management Tools in Knowledge Intensive Entrepreneurship: from University to Industry. Editorial UPV, Valencia. Amabile TM, Conti R, Coon H, Lazanby J (1996) Assessing the Work Environment for Creativity. Academy of Management Journal 39:1154-1184. Atkinson J (1984) Manpower Strategies for Flexible Organizations. Personnel Management August:28-31. Balogun J, Johnson G (2004) Organizational restructuring and middle manager sensemaking. Academy of Management Journal 47(4):523-549. Barkema MG, Baum JAC, Mannix EA (2002) Management Challenges in a New Time. Academy of Management Journal 45(5):916-930. Barney JB, Wright PM (1998) On Becoming a Strategic Player: the Role of Human Resources in Gaining Competitive Advantage. Human Resource Management 37(1):31-46. Baskerville R, De Marco M, Spagnoletti P (2013) Designing organizational systems. Springer. Bierly P, Daly P (2007) Alternative Knowledge Management Strategies, Competitive Environment, and Organizational Performance in Small Manufacturing Firms. Entrepreneurship Theory and Practice July:493-516. Damanpour F (1991) Organizational Innovation: A Meta-Analysis of Effect of Determinants and Moderators. Academy of Management Journal 34(3):555-590. Dyer L, Shafer RA (1999) From Human Resource Strategy to Organizational Effectiveness: Lessons from Research in Organizational Agility. Research in Personnel and Human Resource Management 4:145-174. Forés B, Camisón C (2008) La capacidad de absorción de conocimiento: factores determinantes internos y externos. Dirección y Organización 36:35-50. García-Sabater JJ, Marin-Garcia JA (2009) Facilitadores y barreras para la sostenibilidad de la mejora continua: Un estudio cualitativo en proveedores del automóvil de la Comunidad Valenciana. Intangible Capital 5(2):183-209. Glaser B (2002) Conceptualization: On theory and theorizing using grounded theory. International Journal of Qualitative Methods 1(2):1-31. Glaser B, Strauss A (1967) The discover of grounded: strategies for qualitative research. Aldine:Chicago. Grant RM (1996) Prospering in dynamically–competitive environments: Organizational capability as knowledge integration. Organization Science 7:375-387. Hodge B, Anthony WP, Gales LM (2002) Organization theory: a strategic approach. Prentice Hall. Lado AA, Wilson MC (1994) Human Resource Systems and Sustained Competitive Advantage: A Competency Based Perspective. Academy of Management Review 19:699-727. Laud RL, Thies PK (1997) Great Expectations: Structuring IT Organizations that Really Deliver. Business Horizons 40:25-36

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Lepak DP, Snell SA (1999) The Human Resource Architecture: Toward a Theory of Human Capital Allocation and Development. Academy of Management Review 24(1):31-48. Lepak DP, Takeuchi R, Snell SA (2003) Employment Flexibility and Firm Performance: Examining the Interaction Effects of Employment Mode, Environmental Dynamism and Technological Intensity. Journal of Management 29(5):681-703. Li H, Atuahene-Gima K (2001) Product Innovation Strategy and the Performance of New Technology Ventures in China. Academy of Management Journal 14:1123-1134. Li JM, Yang JS, Wu HH (2009) Analysis of competency differences among frontline employees from various service typologies: integrating the perspectives of the organisation and customers. Service Industries Journal 29(12):1763-1778. Libaers D, Hicks D, Porte A (2009) A taxonomy of small firm technology commercialization, Woks.bepress.com Malone TW (1997) Is empowerment just a fad? Control, decision making and IT. Sloan Management Review 38:23-36. Mas M, Martínez C (2008) Análisis del factor estratégico para alcanzar el éxito de un proyecto de gestión del conocimiento. Aplicación al sector de la consultoría. Dirección y Organización 37:52-59. Mintzberg H (1989) Mintzberg on Management: inside our strange world of organizations. Free Press, Chicago. Murillo, D, Lozano, J (2006) SMEs and CSR: An approach to CSR in their own words. Journal of Business Ethics, 67(3):227–240. Nonaka I (1994) A dynamic theory of organizational knowledge creation. Organization Science 5(1):14-37. Nonaka I, Takeuchi HA (1995) The Knowledge Creating Company. How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, New York. Perry-Smith JE, Shalley CE (2003) The Social side of Creativity: A Static and Dynamic Social Network Perspective. Academy of Management Review 28(1):89-106. Pfeffer J (1994) Competitive advantage through people: Unleashing the power of the work force. Harvard Business School Press. Santandreu C, Canós L (2010) An integrated model of organizational structure and ideas. INBAM 2010: Creativity and Innovation in an International Context, Valencia, 1-9. Santandreu C, Canós L, Pons C (2011) Competencies and skills for future Industrial Engineers defined in Spanish degrees. Journal of Industrial Engineering and Management 4(1):13-30. Taggar B (2002) Individual Creativity and Group Ability to Utilize Individual Creative Resources: A Multilevel Model. Academy of Management Journal 45(2):315-330. Tang HK (1998) An Integrative Model of Innovation in Organizations. Technovation 18(5):297309. Tsoukas H (1996) The firm as a distributed knowledge system: a constructionist approach. Strategic Management Journal 17:11-25 Van Den Bosch FAJ, Volberda HW, De Boer M (1999) Coevolution of firm absorptive capacity and knowledge environment: Organizational forms and combinative capabilities. Organization Science 10:551-568. Velasco E, Zamanillo I (2008) Evolución de las propuestas sobre el proceso de innovación: ¿Qué se puede incluir de su estudio? Investigaciones Europeas de Dirección y Economía de la Empresa 14(2):127-138. Wilson F (1999) Cultural control within the virtual organization. The Sociological Review 47:672-694.

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How Organizational Cybernetics Can Help to Organize Debates on Complex Issues Pérez Ríos J1, Velasco Jiménez I2, Sánchez Mayoral P3 Abstract In this paper we expose how concepts taken from the Systems Thinking field, and in particular Organizational Cybernetics (OC), can help decision makers to study complex issues with the help of the information and communication technologies (ICT). We present some software tools developed within the Systems Thinking and Organizational Cybernetics Research Group (STOCRG) of the University of Valladolid that based on OC concepts use ICTs to help groups of people to study complex issues in a collaborative way through Internet. We discuss some uses of OC to help collective decisions making and we show two international pioneering experiences in which the ICTs have been used in combination with OC concepts. In the first case the purpose was to create a collective scientific book by a group of scientists working at distance and, in the second case, to organize a major academic international event. We end the paper showing an example of specific software (Debates Organizer) developed in the STOCRG through the last 15 years to facilitate any size of groups of people through Internet the organization of debates on complex issues.

Keywords: Organizational Cybernetics, Team Syntegrity®, Debates Organizer 1José Pérez Ríos ( e-mail: [email protected]) Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela Técnica Superior de Ingeniería Informática. Universidad de Valladolid. Campus Miguel Delibes S/N, 47011 Valladolid. 2Iván

Velasco Jiménez  e-mail: [email protected] Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela Técnica Superior de Ingeniería Informática. Universidad de Valladolid. Campus Miguel Delibes S/N, 47011 Valladolid. 3Pablo

Sánchez Mayoral  e-mail: [email protected] Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela Técnica Superior de Ingeniería Informática. Universidad de Valladolid. Campus Miguel Delibes S/N, 47011 Valladolid. * This work has been supported in part by the Ministerio de Ciencia e Innovación (Plan Nacional de I+D+i) of Spain. Ref.: CSO2010-15745.

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1 Introduction In the last few decades the world has changed dramatically. Many are the interrelated factors involved in that change (socio-economic crisis, globalization, demographic, etc.). The consequence is that we live in a very complex social system. To qualify the level of complexity of a system (or a situation) Ashby (1956) proposed the concept of variety (number of possible states of a system) and set in his Law of Requisite Variety that “only variety can destroy variety”. At the start of the seventies, Conant and Ashby (1970) had argued, in the famous theorem that bears their name, that “a good regulator of a system must be a model of the system” and that the variety of the regulator must be at least equal to the variety of the system that it pretends to regulate. If we think in the role of managers of organizations as “governors” of them then they need models adequate to the task, that means models with requisite variety. The Systems Thinking field and in particular Organizational Cybernetics (OC) provide some models like the Viable System Model (VSM) and tools like Team Syntegrity® (TS)4 that can help decision takers to tackle the complex problems facing them. If we focus our attention in how to facilitate the decision-making and communication processes we should consider that, as Pérez Ríos (2008, 2012) expressed it: “The new frontier of humanity is, at the start of the XXIst century, not so much scientific or technological development as an understanding of the complex social systems in which we are immersed. Such understanding is fundamental for our being able to deal effectively with the problems of social tension facing mankind. We must explore new ways to organize and engage in relations that will enhance the processes of communication and decision-making…certain fundamental challenges which still have not been resolved in a satisfactory way: for example, the development of group-decision processes which are at the same time democratic, creative and efficient, or the replacement of hierarchical organizational structures by other more democratic ones in which all points of view can be effectively taken into consideration. “(Pérez Ríos 2012, pp. 201-202). But, at the same time that the world changed and experienced an increase in its dynamic complexity, a whole new set of technological tools related to information and communication technologies (ICT) became available. Also the interest about the role that these can play as a support to higher levels of people participation in discussions and decision-making kept increasing. Examples of those technologies can be found in what is generally known as “groupware”, which includes software for planning and programming in groups, computer-assisted cooperative undertakings, and the whole arsenal of tools that have appeared within the so-called Web 2.0 (Almuiña, Perez Rios et al., 2008, pp. 253-265). “The conjunction of these two

4

Team Syntegrity® and Syntegration® are registered trademarks by Team Syntegrity Inter-

nacional Inc. and Malik Management Zentrum St. Gallen.

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cornerstones—namely, on the one hand, the new conceptual framework for the design of organisational structures and decision processes, and, on the other, the availability of a technological support allowing remote collective intercommunication—opens up new horizons for relations between individuals and institutions.” (Pérez Ríos 2012, pp. 202). In this paper we focus our attention on the application of concepts taken from the Systems Thinking field and in particular Organizational Cybernetics (Beer 1979, 1981, 1985; Pérez Ríos 2012) to help decision makers to study complex issues with the help of the information and communication technologies. In it we present some software tools developed within the Systems Thinking and Organizational Cybernetics Research Group (STOCRG- INSISOC) of the University of Valladolid (UVA) that based on OC concepts use ICTs to help groups of people to study complex issues in a collaborative way through Internet. The paper is structure as follows. First we make reference to how OC has been applied to help collective decisions making. Next we show two international pioneering experiences in which ICTs have been used in combination with OC concepts. The first case purpose was to create a collective scientific book by a group of scientists working at distance and, in the second case, to organize a major academic international event. In the last part of this paper we show an example of specific software developed in the STOCRG through the last 15 years with the aim of helping any size of groups of people to organize debates on complex issues through Internet.

2 Organizational Cybernetics and Group Decision Making Among the diversity of conceptual tools that OC can provide to help collective decision-making we will focus our attention on Team Syntegrity®5 due to its value to facilitate those decision processes. “Team Syntegrity® consists basically of a methodology developed by Stafford Beer (1994) with the aim of offering a creative, synergetic and participative platform for studying complex problems…which we might regard as a structured means of creating and communicating a group awareness” (Pérez Ríos 2012, pp.203). The goals of the TS application can be summarized as follows: “1) To generate a high level of participation among the individuals concerned 2) To provide a structure and a system of communication that guarantee the non-hierarchical nature of the process 3) To benefit from the variety and wealth of knowledge supplied by each individual within the group, putting into practice the synergies derived from the interaction among all its members 4) To create a collective 5

A detailed description of the Team Syntegrity protocols can be found in Pérez Ríos (2000, 2008) and in chapter five of the book: Pérez Ríos (2012) Design and Diagnosis for Sustainable Organizations. The Viable System Method, Springer.

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awareness, if possible shared among all the members of the group, regarding the central issue being considered and analysed” (Pérez Ríos 2012, pp.205). The main phases in which is structured the process of application of TS are the following: a) Opening question. The TS application process starts when a question is asked concerning the issue to be studied or discussed. This question is normally (though not necessarily) of a general, open nature; b) Explosion of variety (Statements). In this stage, each participant prepares statements he/she considers relevant to the central question. The only requirements regarding these statements are that they can be refuted and are not very extensive; c) Reduction of Variety and grouping. After issuing and grouping the statements, we go on to generate Aggregated Statements; d) Assigning topics to people. When the topics for discussion have been identified, it is necessary to determine which persons among the group are going to take part in the debate on each of them. We need therefore to find out their preferences. Once these preferences have been ascertained, this information is processed with the aid of a computerised assignment algorithm 6, which tries to maximise the degree of satisfaction in the group; e) Generation of content. In this phase the different teams which debate each of the main topics generates the information that clarifies the topic. In the next section we will see some examples of how TS was used to help two different groups of people to work collaboratively through Internet.

3 Communication and Information Technologies and Group Decision-Making: Two cases The fast development and diffusion of ICTs opened new ways to apply elements of the OC to help people to debate complex issues without having to be necessarily in the same place. Two pioneering examples of this are the Stafford Beer Festschrift Project (SBFP) and the Horizonte 2000 Project. The Stafford Beer Festschrift Project (SBFP) is the first application in the world of TS, using ICTs. The purpose of the project was to set up a collective study in which over 30 cyberneticians (among them J. Pérez Ríos, co-author of this paper) from four continents and sixteen countries could create a scientific work, revealing the usefulness of S. Beer’s different theories for all kinds of organisations and for society in general. This work would be presented to Beer to celebrate his 70th birthday. The presentation in fact occurred on September 25 th 1996, at John Moore’s University in Liverpool. The undertaking was carried out between October 1995 and July 1996. Almost all of the work, consisting of both identifying the chapters it would include (12) and drawing up the content (more 6

The Systems Thinking and Organizational Cybernetics Research Group at the University of Valladolid developed a set of optimizing algorithms for various TS configurations.

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than 600 pages), was done remotely via Internet. This scientific work has been published under the title: To be and not to be that is the system: A tribute to Stafford Beer, CD ROM (Espejo, Schwaninger et al., 1997). In the book Intelligent Organizations, M. Schwaninger, co-director of the project writes about the elaboration process (Schwaninger, 2006, pp. 123-128). The second example is the Horizonte 2000 Project. The aim of this project was to promote the cooperation among the universities from Iberoamérica, Filipinas and those of Spanish influence in the U.S.A. The project was presented in the event named "I Encuentro de Rectores de Universidades Hispano-AmericanoFilipinas" which, organized by the University of Valladolid, took place in Valladolid (Spain) on 23-27 march 1998. Its purpose was expressed as: “To identify and to start new ways of relationships among the various Spanish speaking universities. It intends, from 1998 on, to open a new historical period of relationships based upon the equality, democracy and mutual trust. To make it possible and to foster this process the new information and communication technologies will be used.” (Almuiña, Pérez Ríos et al, 2000, pp.14-15). The debates system created to make this possible was based on OC principles and it used a new software tool created for this event (Iberforo-98 Project). We will comment some details of this tool in the next section.

4 Group Decision-Making Software Tools. Debates Organizer Based on OC principles and in some elements of the first phases of the TS approach we initiated in 1997 within the ST and OC Research Group of the UVA the development of two groups of software tools to support several phases of the process of knowledge capturing and organization of debates. The first group included software tools that helped the application of TS protocols. The second group included software tools oriented to facilitate the collective knowledge capturing and study of complex issues, as well as the realization of debates through Internet. These set of tools were presented in the Fourth Metaphorum Conference in Liverpool in 2006 (Pérez Ríos, 2006). The first group of tools (based in TS) includes: 1) Software to configure and organize groups sessions in different size options (number of persons: 30, 24, 28, 12, 6); 2) Software to optimize (maximize participants satisfaction) the assignments (persons to issues) in the physically organized sessions; 3) Software to facilitate through Internet the visualization in 3D of the various TS configurations (view of Topics and Participants, as vertex and struts respectively, in figures corresponding to various groups sizes/configurations as represented by the icosahedron-30, octahedron-12, tetrahedron-6, etc.). The second group of tools was oriented to help decision makers to study complex issue through Internet. Here we include two different software applications. 807


The first of them (Col-KCap) was created to help the members of a group to generate through Internet a causal map of the complex problem object of study (Pérez Ríos 1999). It allowed the incorporation of all kind of information both to the variables and to the relations between them, as well as the realization of a MIMAC study (cross-impact analysis) and classification of variables in four main groups (active, passive, critical and inert). The second set of software application (Debates Organizer) was oriented to facilitate the organization of debates of complex issues to any number of persons through Internet (www.debatesorganizer.org). The advantage of using this Internet modality of debates versus the physical meetings (i.e.: the meetings organized with TS, as mentioned in the previous paragraph) is that the persons who compose the group can be located anywhere in space and can intervene at the time that best fits their needs or availability. Another advantage is that a person is not limited to belong only to two specific teams (Topics), as happens in the physical applications of the TS (the two vertex connected by a strut). A person can participate “virtually” in as many Teams/Topics as she/he likes. Of course there are practical limitations about its number (time availability etc.). The first version of this software was used in the above-mentioned Project Horizonte 2000 (Pérez Ríos 1998, 2000) to organize the “I Encuentro de Rectores de Universidades Hispano-Americano-Filipinas” mentioned in the Section 3 (See Almuiña, Pérez Ríos et al. 2000). This project financed in part by the BSCH, was the precursor of the Universia project created in 2000 by the BSCH. The information and communication based software tools used in this project constituted the Iberforo-98 project, later called Iberfora-2000. One of its components was the software to facilitate the organization of debates whose functioning we describe below. The initial version of this software which was used by the rectors who participated in the “I Encuentro de Rectores” included these three main phases of the Internet based debate: a) Formulation of the Issue to be studied b) Expansion of Variety and c) Reduction of Variety and Aggregation of Ideas. An advanced version of this software was presented in the Metaphorum Conference in Liverpool (Pérez Ríos, 2006). Since then we have been using it continuously in our teaching activity in the UVA with engineering students (Information Science, Telecommunications etc.). Let us see briefly how it works. The application of the Debates Organizer to study of a complex issue follows the steps that we describe next. The organization of a debate starts with the identification of the people who is going to intervene in the process (can be located anywhere because their activity will be done through Internet) and the configuration of the debate. In Figure 1 (screenshots from the software Debates Organizer) we can see some of the menu options for the administrator to configure the application. Once created the debate the first step is the launching of the question that expresses the issue to be clarified/answered. This question is presented to the group as a debate kick-off in the form of a manifesto to the group. For example in the 808


case of the "I Encuentro de Rectores de Universidades Hispano-AmericanoFilipinas" the question was: “How to organize (now and in future) the relationships between the various Universities Hispano-Americano-Filipinas, based on a common language and culture, in order to get the maximum benefit for our societies?” Another example is the issue/question proposed to students of Information Science Engineering: ¿What do you think are the effects of the current financial crisis for society and what role ICTs can play in this new scenario? Once known the question the members of the group have a period of time to generate the statements/ideas that each of them considers it relates to answering the issue/question proposed (Figure 2).

Fig. 1 Debates Organizer main screens (Administrator and Users options)

Fig. 2 Debates Organizer (List of Statements/ Ideas)

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In the next step the members of the group propose the aggregation of statements (see Figure 3). The purpose of this phase is to consolidate related ideas into a more elaborated “Aggregated Statement”. Each of the Aggregated Statement finally agreed would constitute the Final topics which condense the answer of the group to the question/issue under study. This process (generation of ideas, aggregation and final consolidation) is enriched with the comments (visible to the group) to all ideas made by the group members through time. The final step is the Generation of Content for each of the Final Topics. This is done typically in physical meetings but some research is in process about its realization at least partially with the help of Internet.

Fig. 3 Debates Organizer (Example of Comment to a Statement and List of Aggregated Statements)

Fig. 4 Debates Organizer (Example of Aggregated Statements)

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5 Conclusions In this paper we presented some examples of applications of OC concepts and tools to help managers to study complex issues in a collaborative way. We commented two international projects (SBFP and Horizonte 2000) in which these have been applied in combination with ICT tools. We exposed as well several software developments done at the STOC research group with the aim of facilitating the organization of debate sessions through Internet. We provide also some information about how one of those -the debates organizer software- works. This application can be used not only to help managers of private companies to make group decisions but to all kind of organizations, no matter if they are public, private, big or small, for profit or non-profit etc. In fact one of our current lines of research is to explore how evolved version of this tools can provide support to a more collaborative and efficient citizens participation in public affairs.

7 References Almuiña C, Martín R. y Pérez Ríos J (eds.) (2000) Las Universidades iberoamericanas en la sociedad del conocimiento. Universidad de Valladolid. Valladolid, ISBN: 84-8448-03-3. Almuiña C, Pérez Ríos J et al. (2008) La relevancia de los medios de comunicación en Castilla y León. Consejo Económico y Social de Castilla y León. ISBN: 978-84-95308-37-5. Ashby WR (1956) An Introduction to Cybernetics,Vol. 2, Chapman Hall, London. Beer S (1979) The Heart of Enterprise. Wiley. Chichester. Beer S (1981) Brain of the Firm, 2nd edn. Wiley. Chichester. Beer S (1985) Diagnosing the System for Organizations. Wiley. Chichester. Beer S (1994) Beyond Dispute. The Invention of Team Syntegrity. Wiley. Chichester. Conant RC and Ashby WR (1970) “Every good regulator of a system must be model of that system”, Int. J. Systems Science, Vol. 1 No. 2, pp. 89-97. Espejo R, Schwaninger M et al. (1997) To be and not to be that is the system: A tribute to Stafford Beer. CD ROM, Wiesbaden; Carl Auer-Systeme Verlag. Pérez Ríos J (1998) La “sintegración en equipos” y el aprendizaje en las organizaciones. El caso de IBERFORO-98. Key note speech. I Reunión de Rectores de Universidades HispanoAmericanas-Filipinas. Marzo 1998, Valladolid, Spain. Pérez Ríos, J. (1999) MODELADO INTEGRADO DE SISTEMAS: Combinación de metodologías cualitativas y cuantitativas para el estudio de sistemas dinámicos. III Jornadas de Ingeniería de Organización, Barcelona. ISBN: 84-95355-00-0 Pérez Ríos J (2000) Nuevas formas organizativas en sociedades complejas. In Almuiña C, Martín R, Pérez Ríos J (eds.). Las Universidades Iberoamericanas en la sociedad del conocimiento. Universidad de Valladolid: Valladolid, Spain; 291–317. Pérez Ríos, J. (2006) Information and Communication Technologies And Organizational Cybernetics. The Fourth Metaphorum Conference. Liverpool John Moores University, Liverpool, U.K., MAY, 4th-5th, 2006 Pérez Ríos J (2008) Diseño y diagnóstico de organizaciones viables. Un enfoque sistémico. IBERFORA 20000. ISBN: 978-84-612-5845-1. Pérez Ríos J (2012) Design and diagnosis for sustainable organizations: The viable system method. Springer: Heidelberg, London, New York, NY.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Schwaninger M (2006) Intelligent Organizations. Powerful Models for Systemic Management. Springer Berlin: Heidelberg.

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The M.A.G. Factor. Management, Administration and Guidance. Where and How Much MAG Does Each Project Deserve and Need? A New, Original Assessment and Scoring System Taylor T1 Abstract This paper explains in outline a new and original assessment and scoring system to assist project managers in assessing the areas and levels of Management, Administration and Guidance (MAG) that clients may require when being involved in projects. The development of this system arose from consideration of client: project manager relationships on a variety of projects; and in particular the amounts of assistance and help that may need to be provided. A number of possible criteria, circumstances and influences were identified; and these have continued to be refined through project activities and by undertaking exercises with students on post graduate courses. Research and applications are continuing. Contributions, comments and corrections are welcome.

Keywords: Clients, Project Managers, Help and Assistance, Management, Administration and Guidance, Score System and analysis.

1Tom

Taylor ( e-mail:[email protected] ) Tom is a principal of dashdot; a joint founder of Buro Four and a retained advisor; and President of the Association for Project Management. Further information on all three of these organisations may be found on their websites. A profile on Tom is available on www.tomtaylorinfo.co.uk.

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1 Introduction This short paper seeks to introduce the MAG factor – a new original assessment and scoring system for a whole range of projects. A MAG factor assessment will greatly assist addressing the following conundrums: Why is it that some Clients appear to need more help than others with the management, administration and guidance (MAG) for their projects? Why is it that projects which seem to be similar, even identical, in fact require different MAG contributions and workloads? When there is only a limited MAG expertise and resource available where should they be applied most effectively? When there are particular MAG concerns what should be done about them? What type, style and ethos of project management are needed and available?

2 What is MAG? Management, Administration and Guidance When a client / customer identifies a project or is landed with a situation to which a project approach is most appropriate then they will at some point consider how the project is to be organised. From a client’s perspective the project management requirements may be broken down into three groups of: Management, Administration and Guidance – hence MAG. Management is the management of the project, programme or collection of projects. This will involve determining the project, devising the course to deliver it, selecting the team and driving all aspects of the project forward to achieve its goals. Leadership is involved and the strategic aspects are established and prioritised. Some Clients (or their internal managers) may want and feel able and willing to undertake this role throughout the project. Others may feel that they are in need of MAG help overall, or for some aspects and/or some stages. The question is: “How much Management help in the MAG Factor does the Client require?” Administration covers the more technical and tactical aspects of projects. Inevitably there is some administration involved in all projects – sometimes a lot – covering secretarial, accountancy, budgeting, payments, arranging events and meetings, keeping records, monitoring, analysing and reporting, etc. Much of this activity and data supports the people and organisations who are managing as above. Some clients have experienced in-house resources who are available and willing to undertake all or most or only some of these tasks. The project activities and administration needs usually grow as the project progresses. The question is: “How much Administration help in the MAG Factor does the client require for this project?”

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Guidance even when a client has confidence in their own Management and Administration there may be circumstances when they need Guidance in the definition or delivery aspects of a project. Whilst most clients have reasonable knowledge of the legal system, accountancy, human relations, property, etc. they still retain or go to specialist advisors for guidance. This may extend even to representations by such people but will not necessarily replace the overall management, decision making and ownership which will remain with the client or their designated project or operational representatives. Such guidance if required may be provided by mentors, advisors, gurus, friends, managers – as above, administrators – as above. So the question is “How much Guidance help in the MAG Factor does the Client need?”

3 Timing and Plans of Work Most projects can be broken down into discrete stages. For example for construction/building projects there are usually three key stages:  Feasibility: when the brief and scheme solution are established, key approvals and funding sought and go ahead received.  Pre-Construction: when the main detail design, procurement and orders are completed.  Construction: when the main works are executed with any remaining design and procurement through to completion – and probably a bit beyond to deal with settlement of accounts and any outstanding issues. And then there is:  Post Completion: this stage is vital in securing the original outcomes, benefits and more for the client that justified the resources and efforts in the first place. Therefore it is possible to undertake a MAG Factor review at the start of each of these stages, as well as any single time on a project when such matters are being addressed. In addition there are two other circumstances that a MAG Factor review might take place:  At times of difficulty/problems/crisis – this is when a review might address if the appropriate levels of client contribution and MAG help are being applied and to appropriate aspects of the project.  At the end of a project as part of the project debrief or lessons learned to ascertain where the pressures and problems occurred and how they were handled.

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4 Outputs From experience, research and application ten key criteria have been identified to establish the MAG factor plus some further other optional criteria. It is possible to apply these criteria to any project to establish:  the overall and average MAG Factor scores – in comparison with other projects and benchmarks,  the aspects on which low scores have been established and how they are to be maintained,  the aspects on which high scores have been established - and the consequential efforts and attention that are required on these aspects to deal with them or to endeavour to lower their scores  a common understanding within the client body on the likely MAG needs and solutions.  a common approach on how naturally limited MAG efforts are to be expended and prioritised.

5 Mag Scoring The recommended approach to scoring is to use a 1 to 10 approach; with 1 being low and 10 being high; “not applicable” , if really true, can score 0/zero/nil. The scores can be allocated in relation to the resource efforts to be applied to each criteria in a reasonable time period of say a week, month or period for a stage within a plan of work. In cases where the team can not agreed on a single score then they can record the range under consideration, move on and return on conclusion of the exercise. Similarly if some circumstances for a criteria would score high while others would score low then record circumstances, assumptions and scores for both – and place their resolution in the recommendations.

6 MAG Criteria Ten criteria have been identified as consistent influences which affect the amount and foci of MAG required on projects. The ten selected criteria with a brief description of each are as follows:

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Same or Different Sector Clients who operate within the same sector as the project will probably need less help. For example a bank might need less help bringing in revised banking regulations but might need more help in setting up Health and Safety arrangements. First Time Type / Volume Clients who are undertaking this type or size of project for the first time will probably need more help. For example a retailer who has previously acquired and fitted out their shops on an individual basis would need more help for say a national acquisition and makeover of fifty units. First Time Contract / Procurement New, different or complex contract and procurement will probably need more help. For example in understanding and applying the first design and build arrangement or multi packaged contracts or foreign sourced services or products. Similarly assembling suitable component tender lists – with sourcing, assessing and selecting in a new market place or against new requirements will require more effort. In Occupation / Use Clients with premises in occupation or ongoing operations will need more help with their capital projects. Also for example places adjacent to day-to-day use – road widening; airport facilities; railway track, signalling and stations – these all requires more help, than a green field situation. Individual or Committee Culture (double edged) Single headed clients probably need less help then say large complex committees – possibly. Except sometimes the individual client can be quite demanding and/or distant; while the experienced committee can be effective, authoritative and prompt – possibly. Funding Externally funded projects probably need more help to secure monies, satisfy funders, deal with payments, etc. compared with internally, simple or self funding. For example projects with Lottery backing and/or the need for public fundraising will need help with financial expertise and fund raising resourcing. Own Occupations / Use Projects for self occupation probably need more help. Owner occupiers have been known to demonstrate characteristics of being fussy, multi headed, have difficulties making decisions, and wish to change their minds to achieve perfection – 817


while at the same time they may work on projects for others without these features. In Relationships (double edged) Clients in established satisfactory partnering, technical staff employed or other relationships will need less new help – possibly. However it may be that not all the team members are in such relationships with the client and/or the relationships have become causal and not consistent with the formal agreements or reasonable expectations – possibly. Stakeholders Projects with diverse or multiple stakeholders will probably need more help. Management, coordination and liaison of stakeholders and participants can be underestimated as soft skills, compared with the other more tangible hard tasks. Availability (double edged) Clients with predominant day jobs and distractions will need more help with their additional projects – or will they? However some clients with busy schedules can be quite decisive and hands off, whilst clients with time on their hands can become over involved(?) Other Criteria There may be other circumstances in which clients require more help with the management, administration and guidance (MAG) of their projects which can be individually recognised.  For example “Health Safety and Welfare” requirements are a high priority and require extra attention in power generation and transmission projects as well as other sectors. Additional help may be required when these are particular issues.  “Diverse Locations” such as in manufacture at various plants of the components which constitute modern aircraft – compounded by language, culture, time zone differences.  “Unknowns, Uncertainties and Complexity” cover situations where there are likely to be a greater number of changes than usual on a project; or there are more unknowns at a stage then might reasonably be expected (these circumstances should also be reflected in higher than usual budget contingencies to deal with them as well as aspects of Agile Management and Complex Project Management).

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7 Way Forward The recommended way forward for the first time is on the following lines: Read over and become familiar with the criteria. Select all or some of the case study projects as trials – below. Select a team including the client for a workshop set of exercises which hopefully will include quite experienced and less experienced people working in mixed sets of two or three or individually. Undertake the case studies and complete their MAG Factor scores and prepare the recommendations – discuss the outcomes – use a sample score sheet. [Inevitably there are ranges of interpretations for each case study and how to apply each criteria and as a group. There are no right answers. Some sample model answers are available to aid discussions of the outcomes.] Now the real thing! Provide a brief summary of your project to hand, add some assumptions, including for whole project duration or a stage only, assess the project against the criteria and any other criteria that may be pertinent – calculate the scores and make recommendations for the organisation of the project. Discuss the project, the assumptions, the scores and recommendations to decide what is to be done to clarify any issues, make decisions, implement decisions and set date or circumstances to monitor the MAG criteria and undertake further review(s). It is advisable to identify, consider and record any further assumptions the team may wish to adopt from the outline project description and the application of criteria.

8 Case Studies The following case studies, all with construction sector content, are offered to test readers’ approach to the MAG Factor. Readers can add their own case studies as previous or hypothetical projects with other features or from other sectors. Road Signs in Blobshire To replace all road signs in Blobshire UK with miles and kilometre measurements to new European standards within eighteen months More Housing Phase 3B of a housing estate for a further 120 semi-detached and detached two and three bedroom units on previously agricultural land by “Top Ten House Builders Co. Ltd”

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Rejuvenated Theatre Demolition of 50% of community theatre premises, rebuild, refurbish, extend as part of urban regeneration with European, regional, local and public funding contributions – to correspond with 100 year anniversary – while continuing theatre productions elsewhere. Mixed Development at Transport Interchange First new, privately-developed mainline railway station in a city centre on contaminated railway land, 800m from existing station, with specially assembled consortium covering commercial offices, property, construction with design, retail operator, railway company and local authority – with some social residential, some leisure, some public space and link to adjacent separate bus/coach station and tram terminus. Improved Security to Retail Units Following a series of break ins and robberies on security and insurance advice it has been decided to improve security to 1000 shop units throughout the country and 20 in North America with replacement locks throughout, internal CCTV systems to half and internal or external shutters to about quarter - to be undertaken in evenings and Sundays over a concentrated four week period as soon as possible.

9 Conclusions In all project situations there is a need for competent, good practice, helpful Management, Administration and Guidance. The reverse is not appropriate or helpful e.g. inexperienced or remote or very light management; or bureaucratic or burdensome or inadequate administration; or inappropriate or mistimed or self-servering guidance. The MAG Factor is a fairly simple concept to understand. It provides a considered and measured way to deal with a range of issues which otherwise can be vague and difficult – and on which possibly only intuition and good/bad experience would otherwise be used. However despite the simplicity developing skills in applying and using the MAG Factor approach takes some time and effort – hence the inclusion of case studies and suggestions of a joint workshop approach to bring out understanding and assist applications. Skills in use will be improved by being organised in the approach, carefully considering criteria (and changing or adding other criteria), by keeping previous score profiles, and observing the influences of refining project descriptions or assumptions.

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This approach can also be of assistance to or be combined with risk reviews, benefits management, governance contributions etc. Persons and organisations who have a structured view concerning Management, Administration and Guidance by using the MAG Factor or similar will be able to provide leadership and efficiency to projects and have advantages over persons who do not have such outlooks or information. Good Luck with your projects.

10 References T.Taylor (2008) “How to Select the Right Project Manager”. Published by Dashdot T.Taylor (2010) “Sustainability Interventions – for managers of projects and programmes – with some serious opportunities, challenges and dilemmas” Published by CEBE and Dashdot T.Taylor (2011) “Leadership in Action”. Published by Dashdot

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EN-06 Service Systems

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Tourism Destination Web Monitor: A Technological Platform for the Acquisition of Tourist Information through the Web Presence of the DMOs Rebon F1, Gerrikagoiti J.K2, Ochoa Laburu C3 Abstract In order to measure, analyze and model the behavior of visitors to the different virtual spaces, CICtourGUNE (Centre for Cooperative Research in Tourism) has created a pioneer platform, Tourism Destination Web Monitor. This article describes the platform, its structure and its potential as a support for possible subsequent research.

Keywords: Tourism Destination Web Monitor, Tourist Destination Image, Web Analytics, User Behavior

1 Introduction The World Tourism Organization (UNWTO 2012) foresees that world tourism will continue to grow between 2% and 4% in 2013, and is expected that by 2030 the tourism industry will generate 9.6% of world GDP with 300 million direct jobs (OMT 2012). Before the current situation of economic crisis, Governments were aware of the importance of tourist economic activity and the crucial role that tourism plays in

1

Fidel Rebón ( e-mail: [email protected]) CIC Tourgune. Paseo Mikeletegi 71 - 3.planta, Parque Tecnológico de Miramón, 2009 San Sebastián 2

Jon Kepa Gerrikagoitia ( e-mail: [email protected]) CIC Tourgune. Paseo Mikeletegi 71 - 3.planta, Parque Tecnológico de Miramón, 2009 San Sebastián

3

Carlos Ochoa Laburu ( e-mail: [email protected]) Escuela Politécnica, UPV/EHU, Plaza de Europa 1, 20018 San Sebastián

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the development of regions (Wanhill et al. 1998). Today, it is vital to make efforts in this sector; since it has a great capacity of influence in the social and economic development. To have great tourist resources is not enough to attract visitors to a destination. It is the image that tourists have and their attitude toward that destination, the two factors that trigger their choice (Ahmed 1996). Baloglu & McCleary (1999) defined the image as the mental representation of beliefs, feelings, and the overall impression of the individual on a destination. Bulnes (2008) offers us a more precise definition: "is the individual or holistic perception of the individual on a specific destination, highlighting its functional and psychological components". This image is created by means of stimulation and personal factors. The first relate the amount and nature of the information to which individuals are exposed and the seconds to the motivations, the sociodemographic characteristics and its cultural geographic origin (Santana et al. 2004). There are several works that demonstrate the variety and the type of information that have to be used in order to have significant effects on the image of a destination (Andrade 2010). In recent years there have been modifications on the habits of information consumption by tourist consumers when they plan their tourist activities. There has been a shift from traditional consultation sources towards the employment of new technologies. It is here where the study of destination web sites emerges as a source of information and its significant influence on the perceived image. The creation and management of a distinct and attractive image of tourist destinations is a key component in the process of positioning a tourist destination in the minds of individuals (Calantone et al. 1989 and Kotler et al. 1993). Therefore, the DMO, Destination Management Organization, should act as a "promoter of destination", facilitating and catalyzing the tourism development from the competitive and sustainable point of view (Presenza 2006). CICtourGUNE has created a pioneer platform, Tourism Destination Web Monitor with the compromise of measure, analyze and model the behavior of visitors to the different virtual spaces. This article defines the platform, its structure and its potential as a support for possible subsequent research.

2 Tourism Destination Web Monitor Nowadays the study of tourism cannot be based only on data generated by statistical institutes or the traditional studies of collecting census data or samples in place. The digital fingerprint left by companies, institutions, visitors, tourists and travelers interested in any potential destination allow the approach to the knowledge of the tourism phenomenon from a new and long rang point of view. The content generated by users on the web through social media, the access to 826


websites of destination and the brokerage websites, as well as another activities in a virtual environment, allow to know patterns of behavior, consumption or particular circumstances, to analyze the creation of brands and carry out analysis of impacts or the opinions expressed spontaneously among others. This way, the knowledge about customers or consumers and tourism markets can be improved, as well as the way the different actors of the tourism sector interact with them more efficiently and effectively. The aim of the platform is to measure, analyze and model the behavior of visitors in different virtual areas (region, territories, tourist brands, associations, capitals, districts, municipalities) in which a destination is promoted. To do this, there is a tool of tracking that captures the interaction of visitors to websites, getting automatically the information of the digital fingerprint that they are leaving. The platform helps to know the network system comprising the various sites and the relationships between them through visitor interactions. So that we can achieve a holistic understanding of the destination as a whole and in a disaggregated way. The holistic positioning of the destination will depend on the traffic that the network it is capable to capture. And the monitor will help to define strategies to capture it. In Fig.1 we show the general stages of the process that the Tourism Destination Web Monitor perform. First the user's data are acquired through different platforms available on the market. This will depend on which the user is using at that time to interact with the website of the tourist destination: a desktop PC, a smart mobile, a tablet or a pda. The collected data are processed on external servers to later convert them into useful information that will be monitored. Once that the monitored results are available, we proceed to analyze and evaluate the in order to draw conclusions about the consumer profile of those destinations.

Fig. 1 General stages of Tourism Destination Web Monitor

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With the availability of analytical data from different target sites in a disaggregated way, we can compare them and make joint policies between different DMOs. Also, this is a scalable solution that it can evolve over time as the DMOs generate new questions to the platform.

2.1 Architecture of Tourism Destination Web Monitor The technical platform (Fig. 2) begins to capture data before the visitor enters the web page of the destination, recording the search engine and the web searched word that has led to the destination, in the case that the entry is not direct. It is possible by means of the incorporation of a small code that must be hosted on each destination website. User´ data are obtained using an open source web analytics platform and stored in a MySQL4 database. Once data are stored in the MySQL database, they are processed and stored in a SQL5 Server database through an ETL (Extract, Transform and Load). This is a daily process, although it could be adapted to any temporality, where data are recorded the previous day not to saturate the server. In order to interact with the data, a cube with dimensions and fact tables is generated through an Analysis Services6 project. The project will provide the design, creation and management of multidimensional structures that contain data aggregated from the SQL Server database where we have located our data. This information is displayed in a simple and clear way through reports and / or graphics that are incorporated into a Sharepoint 7 solution. This solution allows fast web access from any place and platform. Once the information is accessible, it will be treated using indicators to answer to the questions that we formulate. In Fig. 3 we collect a series of those questions.

4 It is database of Oracle Corporation and/or its affiliates 5 It is database of Microsoft Corporation 6 It delivers online analytical processing (OLAP) and data mining 7 It is the business collaboration platform to manage content through the Office interface

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Fig. 2 Architecture Tourism Destination Web Monitor

Fig. 3 Some of the questions you should reply Tourism Destination Web Monitor

2.2 Indicators With this the platform we can design a series of basic indicators as well as a series of complex indicators resulting from a more elaborated and deep study of data extracted from the digital fingerprint of the visitor. These indicators provide an overview that allows us to compare indicators across different web sites of destinations becoming possible to implement benchmarking processes. Simple indicators:  Total visits: the number of visits which has received a tourist website in a given period  Unique visitors: the number of “different” visitors who have accessed the website in a given period  Bounce rate: the percentage of visitors who access the web, which does not perform any additional action and remain on it less than 15 seconds  Total of actions: the total number of actions within a page

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 Total visit time: it is the sum of the duration of all visits made by visitors on the website in a given period. The unit of measurement is seconds Complex indicators:  Input´s URL versus output´s URL: area through which the user enters and area through which the user exits the Web  Number of links between DMOs: the total of visits coming from other DMOs in a specific period  Ratio of image perception: ratio that valued the image of the destination with respect to the culture of the visitor in a specific period  Economic valuation of the destination: ratio that valued economically the web site of the DMO in a specific period  Visitor profile: category of consumer's web site during a time slot  Other indicators

3 Implementation of Tourism Destination Web Monitor The implementation of the technological platform has detected four major levels of complexity: a) it has a large number of actors. There are many virtual spaces which should attend the Tourism Destination Web Monitor and each of them with their particular vision (region, territory, tourist marks, associations, capitals, districts, municipalities), b) the interactions and influences between different DMOs. These virtual spaces are set up hierarchically in an explicit or in an implicit way c) the dynamics of the relationship of the parties concerned. It is a very fragmented sector, with little cohesion which must work to recognize the parties and maximize joint profits, d) the interactions between different levels of Government. Currently there is not a proper interpretation about what administrative models, centralized or decentralized, can be the most effective in managing the complex interactions between different organizations. Currently the platform is in the implementation phase; therefore we can’t provide the scientific community with results. We can anticipate that the Tourism Destination Web Monitor will be implemented in the Basque Tourism Observatory and in Medellin (Colombia), through an international project of technology transfer. If the data are integrated with Social Media Monitor, the platform can study jointly the image projected, perceived and shared. We must not forget that tourism is "a powerful collective imaginability creator" (Ruiz & Menero 2011), and that it is there that the real revolution occurs in the conception of a tourism destination brand. That image is often in the memory even when products have disappeared (Costa 2004).

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In the future, within the lines of research of this monitor, we should contemplate the capability to analyze the association between culture and the influence on the perceived tourist image, the impact of the internet as a source of information induced, if the investment made over the image of the destination is profitable or be able to contribute in the comparison of the perception of the image between different media: web, social media, brochures, surveys,... In addition to being, a selflearning expert system that allows the creation of destination´s websites dynamically adapting to consumer profile.

4 Conclusions At the current juncture, as a strategic sector of the economy, tourism should be a priority commitment by its cross-cutting nature and its ease to be oriented toward markets that show the first signs of recovery. Manage and communicate a positive image of a destination generates three basic benefits: (1) increased future demand based on communication, (2) an increase of tourist satisfaction and loyalty to the destination, facilitating the identification of improvement aspects of the destination, and (3) allow the correct positioning of the destination, identifying its competitive position relative to other competing destinations (Moreno Gil et al. 2012). Virtual spaces are an important channel of marketing for institutions and business network of the destinations, providing enormous volumes of information accessible for potential tourists (Wang & Fesenmaier 2006). Its emergence as an intercommunication tools has allowed tourists and resident population to amplify their traditional channels of influence as prescriptors of the benefits or shortcomings of products, business entities or tourist destinations (Buhalis & Law 2008). The Tourism Destination Web Monitor will help us to develop a good management and communication of the image, because it allows to know what the users want, what pages are they looking for, what products or contents are those that most interest them and what their behavior is. Finally, it enables us to stimulate the consumption of the site by showing contents aligned with the real needs of potential visitors and digital surveys focused on strategic objectives and segments.

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5 References Ahmed, Z.U., (1996). The need for the identification of the constituents of a destination’s tourist image: A promotion segmentation perspective. Journal of Professional Services Marketing, 14(1), pp.37–60. Andrade, M.J., (2010). La imagen del destino turístico. La imagen percibida del turismo rural en Galicia. Universidad de la Coruña. Baloglu, S. & McCleary, K.W., 1999. A model of destination image formation. Annals of tourism research, 26(4), pp.868–897. Buhalis, D. & Law, R., (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet. The state of eTourism research. Tourism management, 29(4), pp.609–623. Bulnes, D.M., (2008). La imagen del destino turístico La Habana. Diseño de un instrumento de medición. p.85. Calantone, R.J. et al., (1989). Multiple multinational tourism positioning using correspondence analysis. Journal of travel research, 28(2), pp.25–32. Costa, J., (2004). La imagen de marca. Un fenómeno social. Barcelona: Editorial Paidós. Col. Diseño. Kotler, P., Haider, D.H. & Rein, I., (1993). Attracting Investment, Industry, and Tourism to Cities, States and Nations-Marketing Places. Moreno Gil, S., Beerli Palacio, A. & León Ledesma, J., (2012). Entender la imagen de un destino turístico: factores que la integran y la influencia de las motivaciones. Criterio Libre, (16), pp.115–142. OMT, (2012). El turismo internacional mantiene su pujanza a pesar de la incertidumbre económica., Available at: http://www2.unwto.org/es/press-release/2012-11-08/el-turismointernacional-mantiene-su-pujanza-pesar-de-la-incertidumbre-econ. Presenza, A., (2006). EL DESEMPEÑO DE UN DESTINO TURÍSTICO?. ¿QUIÉN GESTIONA EL DESTINO?. ¿QUIÉN REALIZA EL ROL AUDITOR? Revista de análisis turístico, 2(2), pp.43–55. Ruiz, M.P. & Menero, E.M.O., (2011). Procesos de “re-imageneering” turístico: el eclipse de la identidad local de Valencia. Cuadernos de Turismo, 28, pp.191–214. Santana, M., Delia, J. & Beerli Palacio, A., 2004. Cómo influyen las fuentes de información en la imagen percibida de los destinos turísticos. Revista española de investigación de marketing, 8(2), pp.7–34. UNWTO, (2012). World Tourism Barometer., Wang, Y. & Fesenmaier, D.R., (2006). Identifying the success factors of web-based marketing strategy: An investigation of convention and visitors bureaus in the United States. Journal of Travel Research, 44(3), pp.239–249. Wanhill, S. et al., (1998). The economic aspects of location marketing. Economic and management methods for tourism and hospitality research., pp.159–195.

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Methodology for Analysis and Decision Making by Sampling in Buildings Aparicio P1, Guadix J2, Onieva L3, Escudero A4 Abstract The sampling of the users comfort, allows observing and predicting the level of comfort on the HVAC system. The development of online sampling systems assists in the recognition of the behaviour patterns that occur in the offices. This paper presents a methodology specially designed and developed in order to make easier knowledge extraction and representation, in this way it possible to make decisions about the comfort in buildings. The users are evaluated by using a standard set of key questions in order to measure the level of satisfaction respect to environmental factors, thanks to a questionnaire of imprecise answers. We seek an improvement in the building users, regardless of their particularities.

Keywords: Comfort, HVAC, Expert System, Occupant, Sampling

1 Introduction Efficient design tools for the thermal performance of buildings have a huge potential to slow down the profligate use of energy and reduce global environmental and housing problems. Consequently, a new philosophy is proposed which will ensure the development of efficient design tools in future, while also taking into account the interests of our occupants. Based on this philosophy, a new design tool was proposed a new model of decision for the parameters in the building (Aparicio, 2011).

1Pablo Aparicio Ruiz ( e-mail: [email protected]) Grupo IO. Departamento de Organización Industrial y Gestión de Empresas II. Escuela Técnica Superior de Ingenieros. Universidad de Sevilla. Camino de los Descubrimientos s/n 41092. 2José

Guadix Martín ( e-mail: [email protected])

3

Luis Onieva Giménez ( e-mail: [email protected])

4Alejandro

Escudero Santana( e-mail: [email protected]).

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Many human comfort models were developed in the last years attempt to predict a better approximation to reality, such as a human feels in a given environment. In general, the patterns of thermal comfort models are based on studies carried out on specific populations in a specific space, which are often analysed using models that follow the idea that these can be used in all building types in the same manner. An HVAC system in which is poorly selected operating parameters may cause reduced productivity, because thermal comfort is known to have a significant influence on the productivity and satisfaction of occupants in a building environment (Akimoto, 2009). These systems obviously need to have sufficient decision-making ability to be able to take action on the level of comfort while saving as much energy as possible. Due to differing perceptions of what is ‘comfortable’, that occur because some people are more tolerant to broader climatic conditions than others. Obviously, whether the standard is accepted or not clearly depends on the place's weather and the building's conditions. Therefore, without questioning the standard, comfort systems whose ventilation and air-conditioning is based on personalised comfort models must be developed. There are different examples both in printed or internet-based studies, where the sampling was based on surveys using sampling methods. The aim of these surveys was to obtain the staff’s general level of comfort at the start or end of the day. These studies, that included many different types of buildings, used information on the physical characteristics of the buildings and the work spaces. However, comfort values associated with the room were not taken into account in these studies (Huizenga, 2002). But as Brager says “An important premise of the adaptive model is that the person is no longer a passive recipient of the given thermal environment, but instead is an active agent interacting with the personenvironment system via multiple feedback loops.”(Brager, 1998).

2 Methodology The methodology is presented in Fig. 1, for making decision of the parameters of an HVAC system. First, it is performed comfort samplings of the occupants, and at the same time it is obtained the space parameters of study. This data is stored and processed. With this information processed, the system obtains the decision criteria to be applied to the search for a solution that will improve comfort and save energy in the building. Once this information is made available (Phase 1), it must make a study of the cost of modifying the parameters of temperature and humidity respect to the variation of comfort for the users, based on the information stored. The system must select the value that satisfies (Phase 2), in the best way

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possible, the criteria selected in the previous phase. Finally, we must apply the settings in the system. Sampling

Data processing

Decision criteria

Space parameters

Decision making in the HVAC system

Phase 1 Cost and comfort analysis

Phase 2

Fig. 1 Methodology

2.1 Sampling, the Online Comfort Survey It has been shown that there is often an acute discrepancy between the comfort objective and subjective comfort (Meir et al., 2009). In view of the objective of comfort presented by ASHRAE thermal comfort in this methodology is used the survey as a fundamental element of subjective data collection (Ashrae, 1997). The survey allows knowing the different perceptions of the users about indoors comfort levels. The system stores information relating to the comfort related to the temperature and humidity at the moment when the survey data are collected. It is selected the international standard ISO 10551:1995 which looks at the ergonomics of the thermal environment as a basis employing subjective judgment scales. Even so, in spite of the requests of those surveyed, all systems must be limited to certain norms whether determined by the ergonomics expert or by the laws or regulations of a country. The survey was performed using seven judgment values: three based on personal thermal condition (perceptual and emotional evaluation and temperature preferences), two based on the thermal environment (personal acceptance and tolerance) and two based on emotional state (level of stress and worker’s mood). The information from the perceptual evaluation was used in the system developed and the main questionnaire is shown in (Aparicio, 2011). The users filled in a second survey in addition to these questions, which was performed at the same time as the first one. Both surveys were performed only once during the day. The second survey contained questions which focused on personal information, sex, age, height, weight and type of clothing.

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2.2 The System Architecture The structure of the system is being investigated, as shown in the Fig. 2, it is based on the user's response to the surveys, rather than being controlled by a remote control to select the set-point of the temperature. This allows to control the humidity, which generally could not be chosen by users. USER INTERFACE

ROOM Communication networks

Temperature and humidity sensor Light sensor

Subjective answers

Microcontroller

…

Surveys Result

External and internal data Knowledge base HR(%) Costs T(ºC)

Phase 2

Comfort Criteria Fuzzy Result

Phase 1

HVAC Fig. 2 The system architecture

The survey information together with the data of temperature, humidity and occupation given by the sensors are stored in a database. The fuzzy logic system gets the information to examine the criteria for selecting the proper temperature and humidity in this first phase. The reasoning of fuzzy logic (FL) are very simple and flexible, the "naturalness" of its approach and not its far-reaching complexity. FL is suitable with imprecise data as comfort, this is used in everyday language, but the same vocabulary to different people may have different values, these values are known thanks to a questionnaire of imprecise answers. The fuzzy logic allows to ensure the reaction of the system on based to the experience of people. The design provides an online reliable pattern detection system but at the same time, an easy implementation. The situational patterns search permit to obtain useful information in takes decision. 836


Through sensors and thanks to the current technological tools with Internet access, the users could be assessed and their comfort could be personalized, in all situations and wherever. In addition, they can register the desired changes about the room states. The objective of the model is to provide a reliable system with an easy implementation, hence the simplicity of the inputs required (variables): percentage and variation of occupancy, the evaluation may be dissatisfied by heat, satisfied and dissatisfied by cold. During the process, the system applied the fuzzy logic to convert the variables to fuzzy variables (fuzzification). Once the components of each variable are obtained, a set of logical rules is calculated considering the variation from the previous period (inference process). An example of rule is, "The preference that should be given to the saving energy if the occupation of the building is low, its variation is negative (the users are leaving the rooms), the number of users dissatisfied by heat is decreasing and its variation is also negative". The answers of the fuzzy rules (comfort, neutral and savings) are used to show that a significant change in global level exists of comfort and represents the configuration to which the system must give preference. Finally, to make a decision about which demand that must prevail (the user comfort or saving into a central system), it is necessary to transform the previous results of the inference process into a single interpretable result mathematically in the form of probability (defuzzification). Furthermore, as not only the flow size is considered but also this variation in a period before, through the careful preparation of the rules, not only the pattern of comfort can be detected, but also the error in next period can be predicted with a very small probability. All this, using a little amount of possible information and independently of temperature or the particularities of each user. The decision logics rules, in case that several types would be detected, the answer would be given with greater probability value. This analysis is always made after a specific time period and a subsequent decision is made with regard to the climate setting type. In a second phase of the system, taking into account the outcome of the fuzzy logic system, and information stored in the comfort of each individual, together with the data or cost function of the change of condition, the change value is the value at which the change in the measurement result is considered desirable due to the comfort and saving criterias. This second system takes the decision on the HVAC, it must be preserved and implemented in the following periods of time. Individual user values are grouped in the system, generating rates of states of comfort regarding different climatic conditions of the rooms (after training the system). In Fig. 2, based on these values, it is known the difference of comfort regarding the current room status. Furthermore, if it is known the consumption differential for a temperature change in a room. The most interested change is selected with respect to the criterion given by the fuzzy logic system.The survey responses are stored individually for each user, the system learns the individual results, and these can be compacted into a general model or for each room. 837


It is stored for each interval of temperature and humidity, the average acceptance by the user group. After the first day, we find temperature and humidity ranges for which we would not know any data, in (Fig. 3) is represented by crosses.

Fig. 3 First Day

But over time, we will found similar comfort models which will follow the Fanger comfort curve (Fig. 4a), but certainly more real to user comfort (Fig. 4b). As shown in Fig. 4b, assuming that we are at a point (22°C, 50% RH) only has to calculate the differential of comfort with respect to the closest points. The amount of energy that must be applied, must be lower due to evaporative systems, those systems can significantly reduce the energy consumed to a change in the degree of comfort. This kind of systems has shown around 15% savings in annual energy consumption of the building, while maintaining the comfort most of the hours in the year. (Khandelwal, 2011). The architecture of this system aims to bring new decisions to be taken on such systems, where users are aware of the humidity, but they will not be able to control their changes.

TOO HOT

HOT COMFORT ZONE COOL TOO COOL

Fig. 4 (a) The figure at left shows the comfort curve of Fanger (Mondelo, 1995). (b) The figure at right shows a possible degree of comfort in a building.

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3 Experiment and Discussions The model has been checked in one real case scenario in two work spaces of the Higher Technical School of Engineering of the University of Seville. The area was heated by two fan-coil units which were part of a central heating system and the same temperature decision was taken for all the equipment of the different areas. In (Aparicio, 2011) could be seen an example of survey result as comfort condition, personal and thermal condition or the emotional condition, and an example of one of the response to one of the questions on the comfort. Besides, you can see the temperature and humidity along the day. This system reflects the need to look for savings and comfort, although the tendency leant more towards comfort due to the high occupation of the space, which was modified according to the users' answers to the questionnaire.

Fig. 5 (a) The figure at left shows the core body temperature waveforms averaged with respect to time of day for young and older subjects (Duffy, 1998). (b) The figure at right shows the rectal temperatures in men, women taking hormonal contraceptives, and women in the phases of their menstrual cycles (Backer, 2001).

The trend in the system, allows you to be away from specific situations, due to psychological factors, health (body temperature), the menstrual cycle in women (Fig. 5b), etc. For these reasons, some people may require a specific temperature due to the difference in the corporal temperature as you can see in (Fig. 5a). However, in the building the user should adapt to the group. The needs of comfort are related to the body thermal curve, and at the beginning in the morning, the results in (Aparicio, 2011) is shown needs of comfort which are reduced in the same way as body temperature increases. This methodology is developed to create an automatic own model of comfort in each building. A dynamic comfort model is developed as alternative to the comfort based on fixed values. In the future we plan to show that this approach is better suited to the reality; however, attention also must be shown in the adaptive comfort models, though the adaptive comfort model is not design to be applied in buildings with HVAC systems. 839


The corpus of this other research line is based in the idea of the human body maintains thermal equilibrium with its environment by means of physiological thermoregulation. But beyond these automatic processes, there is a suite of responses which enable building occupants to adapt to indoor and outdoor climates by means of behavioural adjustments (clothing, windows, fans, etc.), physiological adaptations (acclimatisation), and psychological adjustments (expectations). This idea is included in the methodology shown by means of sampling by survey, with which this information is captured. It is therefore necessary to study, as the adaptive model can help improve this methodology.

4 Conclusion The methodology proposed to control system allows easier evaluation of the indoor climate by using surveys. It is expected that the outcome of this project will show that the control based on thermal comfort surveys provides better comfort at a lower cost than that provided by thermostatic control techniques. There is a need to assure that the saving energy consumption perspective is explicitly present, without prejudice to the comfort in the building occupants. Nowadays, these two perspectives are not connected. This research is an opportunity to balance comfort and energy. The HVAC systems efficiency and flexibility need to be balanced with considerations of users. A new methodology and HVAC control strategy and decision criteria that regulates thermal comfort levels was presented. The system will dynamically adapt to changes in comfort, will store the user responses dynamically to meet your individual comfort. This allows knowing the effect of changes in the decisions of the system. Logically, we are developing a technique in order to prevent the problems and infighting for the selection of temperature within a workspace, where the air conditioning is not to everyone's taste. However, this decision problem can be solved by this system, by obtaining a decision criterion based on sampling, in order to create indoor comfort and energy savings that the EU requires us for the year 2020.

5 References Akimoto, T., Tanabe, S., Yanai, T., Sasaki, M. Thermal comfort and productivity - Evaluation of workplace environment in a task conditioned office, Building and Environment, Volume 45(1) (2010) 45-50.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Aparicio, P., Guadix, J., Muñuzuri, J., Onieva, L. Detecting Comfort-Based Climate Settings Using Surveys. Proceedings of the World Congress on Engineering 2011. Journal Lecture Notes in Engineering and Computer Science, 2191(1) (2011) 1021-1026. Ashrae handbook-fundamentals. American Society of HRAC Conditioning Engineers (1997). Baker, F.C., Waner, J.I., Vieira, E.F., Taylor, S.R., Driver, H.S., Mitchell, D. Sleep and 24 hour body temperatures: a comparison in young men, naturally cycling women and women taking hormonal contraceptives. Journal of Physiology, 530-3 (2001) 565-74. Brager, G.S., Dear, R.J. Thermal adaptation in the built environment: a literature review, Energy and Buildings, 27 (1) (1998) 83-96. Duffy, J.F., Dijk, D.J., Klerman, E.B., Czeisler, C.A. Later endogenous circadian temperature nadir relative to an earlier wake time in older people. Am. J. Physiol., 275 (1998). Huizenga, C., Laeser, K., Arens, E. A web-based occupant satisfaction survey for benchmarking building quality. Indoor Air, (2002) 1-6. Khandelwal, A., Talukdar, P., Jain, S. Energy savings in a building using regenerative evaporative cooling. Energy and Buildings, (2011) 43 581–591. Meir, I.A., Garb, Y., Jiao, D., Cicelsky, A. Post Occupancy Evaluation: An Inevitable Step Toward Sustainability. Advances in Building Energy Research, 3 (2009) 189-220.

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E-Government Interoperability Frameworks: Administration to Business Andres B1, Poler R2 Abstract Interoperability has been show as a problem to solve when enterprises establish collaborative relationships and it is widely studied when relations are established between enterprises. This paper goes further and focuses on frameworks that e-Government agencies have drawn up for achieving interoperability between public administrations and business. A comparative study on different interoperability frameworks is developed, particularly United States, European Union and United Kingdom e-government initiatives are analysed.

Keywords: E-Government, Collaboration, Interoperability, Smes, G2B

1 Introduction: Interoperability and e-Government Current manufacturing industrial environments require an intensive exchange of information among enterprises and administrations and a strong support of information technology (IT) in order to deal with common goals and achieve integrated solutions for providing interoperability within the network (Ortiz and Hawa, 2002). Interoperability facilitates the transfer of information flows at data, processes and services level. Despite the advantages, there are a number of conceptual, organisational and technological barriers that affects interoperability (Boza et al., 2008) being a notable limitation when collaborative processes are established (Andrés and Poler, 2012). Regarding the relations among enterprises (B2B), interoperability problem is widely studied in the literature. Architecture solutions,

1Beatriz

Andres Navarro ( e-mail: [email protected]) Research Centre on Production management and Engineering (CIGIP). Universitat Politècnica de València (UPV). Plaza Ferràndiz y Carbonell, 2, 03801 Alcoy, Spain. 2Raul

Poler Escoto ( e-mail: [email protected]) Research Centre on Production management and Engineering (CIGIP). Universitat Politècnica de València (UPV). Plaza Ferràndiz y Carbonell, 2, 03801 Alcoy, Spain.

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such as LISI (Architecture Working Group, 1998), IDEAS (IDEAS, 2002), European Interoperability Framework (EIF) (IDABC, 2004), INTEROP (Chen y Dassisti, 2006), E-health (NEHTA, 2005) and ATHENA (ATHENA, 2006) are identified to overcome interoperability. Solutions regarding conceptual frameworks (Bénaben et al., 2010) and platforms (Poler et al., 2007) are also identified. On other hand, technological tools are the most used solution alternatives to deal with interoperability, including service oriented architectures (SOA), enterprise service business (ESB) and web services among others (Franco et al., 2009; Bénaben et al., 2010). This paper is focused on the study of frameworks to achieve interoperability at Business to Administration level considering the e-Government concept. Table 1 provides definitions of concepts used hereafter for better understanding. Table 1 Concepts definition Concept Interoperability

e-government

Interoperability in e-Government context Interoperability Framework

Definition The ability to exchange interpretable information among software entities and use it (IEEE, 1990). The ability of a system to exchange information and services in a heterogeneous organizational and technological environment (Chen et al., 2006). The use of ICT in public administration, combined with organizational change and new skills, in order to improve public services and democratic processes and strengthen support to public policies (European Commission, 2003)(Cegarra Navarro et al., 2007) The ability of ICT systems and business processes to support the sharing of information and knowledge (IDABC 2004). The concept of interoperability goes beyond technical standards for data exchange, and includes issues such as legal constraints, inter/intraorganizational workflows amongst organizations and understand the data ontology (Fairchild and de Vuyst, 2007) Refers to the basic technical specifications e-government agencies should adopt. Enables the interoperability between information systems from different agencies in order to provide services to citizens and business in an integrated way (Guijarro, 2007)

Regarding e-Government, different stakeholder categories are identified (Rowley, 2011): Government-to-Government (G2G), Government-to-Citizen (G2C) and Government-to-Business (G2B). This paper is focused on G2B in order to identify frameworks that treat interoperability issues when collaborative relationships are established between administrations and enterprises. A comparative analysis is established in order to contrast the same characteristics of different eGovernment interoperability frameworks considering the G2B context.

2 Background INTEROP-VLab (International Virtual Laboratory for Enterprise Interoperability, 2013) pursues to support Enterprise Interoperability (EI), Enterprise Systems Applications (ESA) and Future Internet (FI) domains. INTEROP-VLab is a networked association whose members are pooled in autonomous “Poles” in a same geographical area; the Spanish Pole is represented by INTERVAL Association in 843


the Universitat Politècnica de València. In accordance to the INTEROP-VLab research, this paper focuses on the G2B interoperability point of view involving the collaboration of public and private entities in the provision of services (Guijarro, 2009). E-Government has become one of the key factors for the public sector guaranteeing transparency, accountability and interface with citizens, businesses and administrations. Few studies have treated the factors contributing to the integration or implementation of e-Government in companies (Cegarra et al., 2007). Public organisations such as United Nations and the OECD (Organisation for Economic Co-operation and Development) have generated comparative studies analysing the e-government initiatives. Nevertheless, these studies do not focus in a comparative analysis on frameworks to deal with interoperability problems in G2B context, thus this study is focused to do it. Administrations are committed to provide accessible and cost-effective public services through the use of ICT, acknowledging the significance of e-government for social inclusion and economic growth. Table 2 identifies six major initiatives on e-Government to deal with the interoperability. Table 2 e-Government Interoperability Frameworks (Guijarro, 2007) Country

Framework eGovernment Unit United eGovernment Interoperability Kingdom Framework Le Cadre Commun France d’Interoperabilité Standards and Architectures Germany for e-government Applications Danish eGov interoperability Denmark Framework Interoperable Delivery of European eGovernment services to Public Administrations, Business and European Citizens Union European Interoperability Framework United States

Enterprise Architecture Guidance

eGU eGIF CCI

Based on Specifications and policies for any cross-agency collaboration and for e-government service, covering interconnectivity, data integration, e-services access and content management. Strength public electronic systems coherence and enables multi-agency electronic service delivery

SAGA

Guideline to orientation aid for decisions makers in the egovernment teams in German administrations

DIF

Guideline to public agencies as they develop IT plans and projects

IDABC

Supporting tool for European Parliament and Council interoperability and access to Trans-European Networks for the data exchange between European Institutions, Agencies and governments in Member States.

Common framework about interoperability issues that should be addressed when implementing pan-European e-Government IDABC services. Has strong influence on national interoperability EIF frameworks developing join working programs together with the e-Government agencies of the Member States Procurement guideline for government departments to ensure EAG that systems separately acquired would be able to interwork

An important aspect is that e-government may better meet the needs of the private sector increasing the competitiveness of the economy. E-government can particularly benefit SMEs, which often face difficulties when dealing with administrations. Thus, the development of quality e-government services allows to overcome such barriers (Tzikopoulos et al., 2012).

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2.1 European Interoperability Framework (EIF) Approximately 80% of economic growth comes from SMEs and 95% of businesses in Europe are SMEs, therefore government’s strategies on supporting SMEs readiness and acceptance of e-government services are becoming more important (Adeshara et al., 2004). The European initiative for e-government consists of (i) the development of internet-based services to improve access to public information and services, (ii) the improvement of transparency of public administrations, (iii) full exploitation of information technology within public administrations and (iv) establish e-procurement (Strejcek and Theil, 2002). The European Interoperability Framework (EIF) was developed as the reference document on interoperability for the IDABC program, and supports the pan-European delivery of electronic government services with a set of policies, standards and guidelines describing the way in which organisations should agree to do business with each other (IDABC, 2004). The main objective of the EIF is to support the EU strategy for providing user-centred eServices and interoperability between public administrations, citizens and business (Fairchild and Vuyst, 2007). EIF allows Europe’s citizens and enterprises to move freely between Member States and allows firms to do cross-border trade across Europe’s borders, to transact business electronically with European administrations and companies (IDABC, 2004).

3 Interoperability Frameworks: a Comparative Study The e-government initiatives are treated in this section due to organisations need to integrate their IT infrastructures to support the integration, both at administrations and enterprise level, to increase their efficiency. SMEs lack of expertise and financial resources to invest in the necessary technologies makes the government support fundamental (Chen et al., 2011). A common theme in e-government context is the use of open standards to promote interoperability. A comparison on eGovernment interoperability in US, EU and UK frameworks is shown regarding standardisation and interoperability e-government deployment (table 3); a set of nine areas are identified in order to compare the different e-Government Interoperability Frameworks (Guijarro, 2007). Besides considering the US, EU and UK frameworks, the eGIF4M, developed in Mozambique is also considered in order to have a broader view. Provided characteristics are considered in order to compare different standards among the interoperability frameworks and identify which areas are more developed in each one (see table 4).

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 3. Comprehensive comparison on e-Government policies regarding interoperability (US, EU, UK) based on Guijarro (2009) Interoperability Framework (Cuntry)

Devoted to

 Public and private sector interests  Federal government is not expected to cast an influence on the choice of technologies in egovernment systems and services deployment

Employment

 Only under special circumstances government-unique standards are allowed  Federal agencies establish voluntary consensus standards that are identified as the alternative and mandatory choice  Standardisation is coherently applied in e-government deployment  Voluntary consensus standards are prioritised against government-unique standards, although any other sort of industry standards may be chosen

STANDARDISATION

Standards

 American National Standards Institute’s (ANSI)  Document: United States Standards Strategy (USSS)  National Standards Strategy (NSS)

Implications

E-GOVERNMENT DEPLOYMENT

EAG (United States)

Interoperability

 Government regulations  Government participation  Standards development  Government procurement Office of Management and Budget (OMB) has executed its guidance through the Federal Enterprise Architecture Project Management Office (FEAPMO) and in cooperation with the Federal Chief Information Officer (CIO) Council Alignment of all Departments and cross-agency architectures with a Federal Enterprise Architecture. The FEA consists of basic reference models, namely: Business, Service Component, Technical, Data and Performance Reference Model Common business processes, common components, common technologies and common data assets across different governmental departments and to eliminate redundancy

IDABC EIF (European Union)  National standards bodies (NSBs)  European Committee for Standardisation (CEN)  European Committee for Electrotechnical Standardisation (Cenelec)  European Telecommunications Standards Institute (ETSI)  European Standards Organisations (ESO)  More coercive powers than does ANSI as a result of his authority to eliminate conflicts among national standards  Neither public nor private standards are excluded, but a preference for standards developed by the ESOs is implicit  For a standard to be European, it has to be adopted by one of the ESOs and be publicly available  Non-coherent implementation of the standardisation and public procurement regulations in egovernment deployment  EU-wide regulations exhibit preference to the European standards over any other sort of standard, some governments often implement practices in egovernment deployment that are not aligned to those regulations, and in some cases those practices are opposed to them

e-GIF (United Kingdom)

 Technical Standard Catalogue

 The criteria for selecting standards that will be part of the e-GIF are the following: interoperability, market support, scalability, openness and international standards

 Appropriate international standards will take preference over European standards, and European standards will take preference over UK standards

-

-

Avoids prescribing any concrete architecture or standard catalogue, which is to be the main objective of successive releases of the Architecture Guidelines

-

The EIF does not aim to replace national interoperability guidance but focuses on supplementing them by adding the pan-European dimension. Anyway, the influence of EIF over national interoperability frameworks is important. In spite of the clear stage defined by both the Architecture Guidelines and the EIF, the European Commission sometimes makes an incoherent application of its own egovernment interoperability guidelines outside the IDABC funded projects

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e-GIF mandates sets of standards and policies for joined-up and webenabled government. It covers four areas: interconnectivity, data integration, e-services access and content management

-

Interoperabilit y Areas

847

Council's security regulations (2001/264/EC), Security services, Government Secure Intranet (GSI), OASIS PKI, Web service security, Firewalls, Protection against viruses Open standard

s/mime, SALM Voluntary consensus standards

Open

-

WSS, SAML, xACML, Enc XML, HTTPSS, SSL, S/MIME, RFC2527, ISO/IEC

-

Security services

-

Security Standards for Smartcards, Issue 1.1, December 2003’, namely CC, ETSI, FIPS and EMVCo, which is located on GovTalk

JDBC, WebDAV

-

-

Data management services

-

-

e EU IDA (Interchange of Data between Administrations) programme as bases for European standards, XML, GovTalk, Web services based on SOAP and WSDL, UDDI

MIME, T.120, H.323

electronic interchange of data between administrations (IDA), web service

-

eGIF4M (Mozambique) IP, LDAP, FTP, HTTP, SMTP, POP, DNS, NTP, SOAP, SIP ASCII, UTF, XML, SAX, DOM, XSLT, Xpath, SQL, RSS, UBL, HL UML, ER, RDF, OWL, SAWSDL, DTD, XMLS, SQL DDL, xNAL, xCRL, xBRL, URI, URL DOC, RTF, PDF, ODF, GIF, PNG, JPEG, BMP, WAV, mp3, OGG, DivX, mpeg, avi, HTML, XHTML, ZIP, RAR

World Wide Web, HTML, WS-I,

DTV, mobile phone, PDA, smart card, Internet, public kiosks, digital TV, WAP phones

World Wide Web Consortium, kiosks, web-TV, mobile connectivity HTML, Business Interoperability Interfaces (BII), Interface design principles

XML, e-GMS

XML, XSL, UML, RDF

XML family of standards, UML or RDF for data modelling, XSLT Dublin Core

IPv4, HTTP, S/MIME

TCP/IP, HTTP and S/MIME

eGIF

e-Government Interoperability Frameworks IDABC EIF

Network Services

Technical Specifications

Organises standards around Services

WAP, J2EE, .NET, web services

-

Access

Data interexchange services

-

Content management metadata

HTML Symbian

-

Data Integration

Human computer interface services

-

EAG

Interconnection

Areas

Table 4 e-Government Interoperability Frameworks comparison regarding interoperability areas and standards around services



The European Interoperability Framework (IDABC EIF) is characterised by establishing interoperability in e-government services and it is initially aimed on interoperability areas with inclusion of standards around services but this inclusion is still at early stages (Guijarro, 2009). On the other hand, the approach in the United States (EAG) is more comprehensive, because it focuses on the adoption of semantic technologies in e-government more solid and clearer focused than the considered in European initiatives (Guijarro, 2009). Given the results derived from the comparative analysis, both the US and the EU present risks to fulfil the interoperability envisioned by their respective e-government strategies. Egovernment deployment would end up in systems that fail to provide interoperable services because they do not adhere to either voluntary consensus standards in the US or European standards in the EU.

4 Conclusions Considering the importance on interoperability when establishing collaborative processes, this paper focuses on the treatment of interoperable frameworks regarding the collaborative relations SMEs establish with public administrations (G2B). As regards of public administrations the e-Government is an important issue so as to achieve integration processes in G2B. Two comparative studies are developed in order to have an insight of the current situation in e-Government Interoperability Frameworks (eGIFs) regarding interoperability and standards, both in Europe and United States, besides this, a comparative analysis is also determined regarding the situation in Mozambique to have a broad view. Through comparing the EU and US eGIFs we can observe that several gaps are found, especially within the EU eGIF, concluding that US frameworks are more advanced and developed. The provided analysis allows to firstly identify common variables in order to make a comparison among e-Government Interoperability Frameworks. Secondly, it is concluded that the given e-Government Interoperability Frameworks are considered as useful tool to solve the interoperability problem between enterprises and public administration in one hand to apply interoperability to exchange data and on other hand to interpret the exchanged information to exploit the knowledge in G2B relations. In the development of this paper we have identified a lack of research in G2B perspective (occasionally named Public-private partnership, PPP) due to most work and reports on the study of e-Government readiness is focused towards the G2C (government to citizen) point of view.

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5 References Adeshara P, Juric R, Kuljis J, Ray Paul R (2004) A Survey of Acceptance of e-Government Services in the UK. Journal of Computing and Information Technology - CIT 12(2)143-150 Andrés B, Poler R (2012) Relevant Problems in Collaborative Processes of Non-Hierarchical Manufacturing Networks. In Prado JC, García J, Comesaña JA, Fernández AJ (eds.) 6th International Conference on Industrial Engineering and Industrial Management, 90-97,Vigo Architecture Working Group (AWG) (1998) Levels of Information Systems Interoperability (LISI), March 30. C4ISR ATHENA, 2006. ATHENA Integrated Project Bénaben F, Boissel-Dallier N, Lorré JP, Pingaud H (2010) Semantic Reconciliation in Interoperability Management through Model-Driven Approach. In: Camarinha-Matos LM, Boucher X, Afsarmanesh H (eds). Collaborative Networks for a Sustainable World. 11th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2010. Saint-Etienne, France, October 11-13 2010: Springer. 705-712 Boza A, Navarro R, Vicens E (2008) La Vista De Información En El Modelado Del Proceso De Planificación Colaborativa De Una RdS/D: Diseño De Un Modelo Informacional Genérico Integrado, 22-28, Burgos Cegarra Navarro JG, Dewhurst FW, Briones Peñalver AJ (2007) Factors affecting the use of egovernment in the telecommunications industry of spain. Technovation 27:595-604 Chen D, Dassisti M, Elvesæter B (2006) INTEROP Deliverable DI. 1b Interoperability Knowledge Corpus. Intermediate Report Chen H, Papazafeiropoulou A, Wu Ch (2011) An E-Government Initiative to Support Supply Chain Integration for Small to Medium Sized Enterprises: Successes and Challenges. Advances in Information Systems Volume 42(4):63-80 European Commission (2003), The Role of E-government for Europe’s Future, Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions, European Commission, Brussels Fairchild A, de Vuyst B (2007) Governmental Collaboration and Infrastructural Standards in Belgium. The Electronic Journal of e-Government 5(2):145 - 152 Franco RD, Ortiz A, Lario F (2009) Modeling Extended Manufacturing Processes with ServiceOriented Entities. Service Business 3(1)31-50 Guijarro L (2007) Interoperability frameworks and enterprise architectures in e-government initiatives in Europe and the United States. Government Information Quarterly 24:89-101 Guijarro L (2009) Semantic Interoperability in eGovernment initiatives. Interfaces 31:174-180 IDABC (2004) European Interoperability Framework for pan-European e-government Services. Luxembourg, European Communities IDEAS: Interoperability Development for Enterprise Application and Software (2002) Thematic Network, IDEAS: Interoperability Development for Enterprise Application and SoftwareRoadmaps, Annex 1 IEEE (1990) Institute of Electrical and Electronics Engineers. IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries. New York International Virtual Laboratory for Enterprise Interoperability (2013) http://www.interopvlab.eu/ NEHTA, National E-Health Transition Authority, 2005. Towards an Interoperability Framework, Version 1.8 Ortiz A, Hawa M (2002) Extended Enterprise for Supply Chain Management. Why, when and how to Apply it. A Reference Model for Collaborative Planning in the Automative Sector Poler R, Ortiz A, Lario FC, AlbaM (2007) An interoperable platform to implement collaborative forecasting in OEM supply chains. In: G. Doumeingts, J. Müller, G. Morel and B. Vallespir, eds. Enterprise Interoperability - New Challenges and Approaches. London: Springer

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Rowley J (2011) e-Government stakeholders—Who are they and what do they want? International Journal of Information Management 31:53-62 Strejcek G, Theil M (2012) Technology push, legislation pull? E-government in the European Union. Decision Support Systems. 34:305-313 Tzikopoulos A, Manouselis N, Kastrantas K, Costopoulou C (2012) An online information system to support blended training of rural SMEs on e-government. Program: electronic library and information systems 46(1):123-143

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Economic Performance and Financial Profitability: Two Study Cases in F&B Industry Santandreu-Mascarell C1, Canós-Darós L, Vidal-Carreras PI, ValeroHerrero M Abstract In this paper we describe some economic and financial ratios in order to reflect about the need to introduce some standards in annual account about innovation and intangible assets. For this, we compare two innovative companies with data from Food & Beverage (F&B) industry, and we show some differences that have to be explained.

Keywords: Food and Beverage Industry, Economic Performance, Financial Profitability, Innovation, Intangible Assets.

1 Introduction KPMG performed for the first time an economic-financial study about Food and Beverage industry (F&B) in Valencia (Spain) using as a base the ranking business in 2010 of the 21 companies with higher sales. Criteria for selecting companies were the performance and the availability of information from managers. Information is based in 2009 and 2010 balance sheets. This report presents main economic and financial ratios, together with aggregated assets and liabilities. Data can be seen in kpmg.es. As it is well known, the objective of financial statements is to represent the true image of the company, its real value. Economic-financial ratios give information about profitability and financial returns obtained on the basis of investments made

1Cristina

Santandreu-Mascarell ( e-mail: [email protected]) IGIC-Departamento de Organización de Empresas. Universitat Politècnica de Valencia. C/Paranimf, 1, 46730 Grau de Gandia (Valencia).Spain.

* This paper has been partially supported by the projects CORSARI MAGIC DPI2010-18243 Ministerio de Ciencia e Innovación del Gobierno de España and TIN2008-06872-C04-02/TIN – Ministerio de Educación y Ciencia del Gobierno de España.

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by the company to produce goods or services, and from funding sources used for this (information shown in annual accounts). The result is useful for making decisions about investment, but it have to be compared with those of other similar companies and with the industry average. In this paper we use KMPG ratios as industry benchmark. Moreover, we note that selected companies in KMPG study were considered as innovative companies, and all of them present information related with this topic in their web pages. The list of selected companies is: Compañia Levantina de Bebidas Gaseosas, S.A.; Embutidos F. Martínez R., S.A. Importaco, S.A; La Española Alimentaria Alcoyana, S.A.; Maicerías Españolas, S.A.; Miguel Aguilar, S.L.; Producciones Agropecuarias del Turia, S.A.; Roquette Laisa España, S.A.; Refresco Iberia, S.L.; Sada S.A.; Valencia, S.A.; Martínez Loriente, S.A.; Font Salem, S.L.; Jesús Navarro, S.A.; Asociación de Industrias Alicantinas del Helado y Derivados, S.A.; Desarrollos Alimentarios Frescos, S.A.; Grefusa, S.L.; Lactalis Restauración, S.L.; Natra Cacao, S.L.; Chocolates Valor, S.A.; Verdifresh, S.L.; Dulcesol. Nowadays, it is very complex to show true value of the company in annual accounts because there are many variables in the environment very difficult to quantify, such as different types of intangibles. In addition, accounting standards are rigid. Our study case is an economic and financial analysis of two companies belonging to F&B industry that are not considered in KPMG report. We want to compare them with F&B industry economic and financial data. Companies under study, that we name JM and BG because of confidentiality, have been selected from the results of a qualitative research about innovative companies developed by using grounded theory methodology (Canós and Santandreu, 2010). Both the study of the economic and financial performance of JM and BG has been made based in balance sheets and accounting data from 2003 to 2010. Presented ratios have been calculated based on the available information (not only accounting) to make it as real as possible.

2 Economical and Financial Analysis of Companies BG and JM: Comparison with F&B Data Given that the objective of the finance function is to maximize the value of the company to its owners, and shareholder returns is measured by the return on equity (economic study), also known as financial returns (financial study), it can be summarized that financial returns is based, among others, in: a) The returns of the company’s assets, i.e. both the short and long term investments; and b) Financing ways, therefore, financial needs and costs. Moreover, we have to consider taxes or an analysis of the stock exchange market, but they are not included in the aim of 852


this paper. We will discuss these topics always from the perspective of risk and profitability. All this is the result of the management of the company. It comes from a good information and knowledge management, ways of working, integration by coordination to achieve the same goals, just to produce goods and services required by the customer.

2.1 Economical Analysis Economic profitability measures the generation of benefits in proportion to assets regardless of financing. Difference between companies’ accounts lies in how each one establishes the assets structure related to non-current and current profits. We could discuss many ratios that give important information such as the balance sheet or annual accounts of the company, but we will discuss only those we consider interesting for this paper (Weill, 2008). In this sense, we are going to show the F&B industry reference and the 8-years average data (from 2003 to 2010) of JM and BG, and ratios of the last year (2010). Table 1 Economical analysis. JM (average)

BG (average)

F&B industry

JM (2010)

BG (2010)

Economic profitability

0.038

0.138

0.083

0.064

0.153

Asset rotation

0.961

1.001

1.544

1.04

1.022

Noncurrent asset rotation

1.839

2.609

3.361

2.507

2.783

Current asset rotation

2.101

1.634

2.685

1.777

1.614

The profitability of JM company during the period of study was a 3.8%, ranging from 1.4% to 6.4%. In the last year, it was almost two points lower than the profitability of the studied companies accepted as industry benchmark. Meanwhile, the average of BG is 13.8%, ranging between 11% and almost 19%, being on the last year 15%, well above the industry. Then, we have two different cases. In 2010 the economic profitability of F&B is 8.3%. By comparing JM and BG companies to the industry, we can see that JM has a lower profitability, so that, the industry takes greater return on its asset composition, while BG assets generate a much higher return than the sector. This fact indicates that we should study more in depth the composition and valuation of assets when decision making.

853


In both companies , JM and BG, we can see a lower asset rotation, hovering around 100%, than the industry, in average as well referred to 2010 (154% in F&B industry). Nowadays, these data should be better analyzed differentiating profitability generated by noncurrent assets tan current assets’ returns.

2.2 Financial Analysis Financial profitability measures the ability of the company to reward shareholders. For them, it represents the opportunity cost of the funds held in the company. It enables the comparison with the returns to be gained in other investments (González et al., 2002). In financial analysis is discussed, among others, liquidity, solvency, the liability structure and coverage. These data provide information on how the company is in a particular time and it is used to make decisions. Following the same structure as in the previous section, we use data from F&B industry for comparison in order to get results as realistic as possible. We consider these data as referent in the sector. About companies JM and BG, we use the average of the ratios of the studied period (2003-2010) and data from balance sheet and annual accounts in 2010. We can see this information in Table 2. Table 2 Financial analysis. JM (average)

BG (average)

F&B industry

JM (2010)

BG (2010)

0.059

0.139

0.093

0.141

0.162

Current ratio

1.286

2.261

1.593

1.494

2.482

Acid test

0.690

1.497

1.231

0.895

1.625

Cash ratio

0.062

0.177

0.143

0.016

0.090

Solvency

1.612

3.338

2.316

1.619

3.479

Charge period

77.338

109.277

40

108.913

93.037

Payment period

224.462

160.537

53

113.828

188.25

Financial profitability Liquidity

Liability structure Indebtedness ratio

2.060

0.475

0.765

1.818

0.417

Indebtedness structure

0.578

0.911

0.811

0.634

0.887

854


As we can observe, company JM has a financial profitability of 5.9% in average. This figure is not so much representative, because in 2003 it had a return of 2%, and it increased to 14% in 2010; the evolution is dramatic. 14% is higher than the average of F&B (9%) in this year. In consequence, shareholders consider the company has a positive status about its business. The liquidity current ratio stands at almost 129%, that is, the company amply covers short-term debts (current liabilities) with current assets. Nowadays, acid test is equal to 69%, since this ratio does not take into account stocks. Ignoring the stocks the company could not cover its short-term liabilities with its current assets. This indicates the company has a high level of stocks. In this case, JM should review its stock management policy. Because cash ratio is 6.2%, JM would not be able to face its short-term liabilities with liquid resources only. Note that cash ratio for F&B industry is 14% and JM ratio is 6.2% (less than half). Solvency of the company remains around 161%, thus covering their total debts to third parties with their assets, but below the industry with 213%. Although all these data are seen as favorable by the meaning of results, also serve as an evidence to think questions as: How could I face my debts? Could I get more return by changing liability structure? Charge and payment periods are on average more or less 77 days and 224 days. This data would indicate that JM follows a correct policy because it charges much before paying, but really the evolution of the studied period (2003-2010) shows that the charge period has increased from 70 to 108 days and the payment period has decreased from 221 to 113 days. Then, the gap has decreased a lot. JM should review this policy and analyze the reason to be in this situation, as it could lead to solvability problems because they gap is lower than 5 days between charge and payment. About indebtedness ratio, its average is 206%. JM has a constant average in the period observed. It means that, for each 2 euro of borrowings, JM has 1 euro of equity. Indebtedness structure is about 60%; more than half of the resources are in the short term according to last year data. F&B industry has a much lower indebtedness ratio (76%) and a indebtedness structure slightly higher around 81%. Should JM change equity ratio of and debt capital? Should it change the liability structure as suggested above? On the other hand, BG has an average of 13.9% financial profitability, return after taxes; in 2010 it was 14%, still higher than F&B average: 9,3%. Current ratio stands at 226%. So, the company covers short-term debts (current liabilities) with its assets. This figure remains in 2010 near F&V average and above (248%). Acid test or decreases to 150% of average, since this ratio does not take into account stocks. Still, BG could meet its current liabilities with its current assets; this large difference indicates that BG has a high level of stocks. However, BG acid test in 2010 is 163% and F&B is 123%, the distance is not so far. 855


BG cash ratio average is 17.7% and industry cash ratio average is 14%. In BG current asset more representative items are stock and commercial debts. It would not be able to face its short-term liabilities only with its liquid assets. Solvency of the company remains around 334%; assets cover total debt. Average in 2010 was 348%, standing well above the sector. Charge and payment periods respectively are, on average, 109 and 160 days. This data would indicate a correct policy. From 2003 to 2010, charge period has decreased from 104 to 93 days and the payment period has increased to 188 days, contrary to what happened in JM. This is a very positive advantage from the industry point of view, but a deeper review is needed because, for instance, its image can be damaged if BG pressures too many the customers or delay a lot the payment to suppliers. Indebtedness ratio remains constant from 2003 to 2010 at an average of 47.5%, that is, per 47.5 euro from borrowings BG has 1 euro of equity, similar to 2010 data (42%). It has a structure whose liabilities are greater than borrowings. Indebtedness structure, 91%, indicates the majority of short term borrowings, and it is very close to the industry.

3 Should Innovative Companies Annual Account Show more Data? Users of accounting and financial information periodically issued by companies can hardly found in annual accounts quantitative references to concepts associated with innovation, because intangible assets are not on the balance sheet (if we identify them with their costs). Financial information, as shown in the study of the ratios, is useful to current and future investors, creditors and other users to make decisions about investment, credit and similar. Therefore, because intangibles have become a key determinant of corporate value in new knowledge and information economy, companies should give information in financial statements. Then, there is no alternative to rethink used criteria for their preparation (Moreno and Rico, 2002). However, given the great difficulty of modifying the current locked and complex structure of accounting, other proposals aimed towards addressing intangibles in the management report (Cañibano et al ., 2000). In any case, clearly highlights the need to provide external users of accounting information a better measure of the value of organizations to reduce, where possible, the distance between the market value of the companies and the value in financial statements, i.e. to create statements that reflect the true image of the company. The problem arises when valuing these intangibles and how they may or may not be included in the information provided by traditional financial statements (Craig and Dribell, 2006). 856


In conclusion, more information should be shown in annual account, completing financial statements with information about intangibles and other innovation ratios. This is justified by some papers that determine that intangible assets, ways of working or the university level (competencies), make an innovative company (Canós et al., 2011; Moreno and Rico, 2002; March and Yagüe, 2009). Companies need an instrument enabling them to measure their performance indicators that are not limited to economic and financial, but a step forward and taking into consideration such characteristics. Then, the performance of such organizations should be quantified; intangible and innovation ratios have to be determined whether they are assets, liabilities, income or expenses. In this case, the difficulty is that what is measured is the performance of people providing a view of the situation of human resources in the organization to be included in the economic-financial ratios allowing financial statements fairly reflect its goal: the true image of the company, its real value.

4 References Cañibano L, Garcia-Ayuso M, Sánchez P (2000) La valoración de los intangibles: estudios de innovación vs información contable financiera. Análisis financiero 80:6-24. Canós-Darós L, Santandreu-Mascarell C (2010) An integrated model of organizational structure and ideas. INBAM Conference, Valencia. Canós-Darós L, Santandreu-Mascarell C, Garcia-Sabater J, Marin-Garcia JM (2011) Five information-based key factors for innovative companies in Sethi SP, Bogataj M, Ros-McDonnell L. Industrial Engineering: Innovative networks. Craig J, Dibrell C (2006) The Natural Environment, Innovation, and Firm Performance: A Comparative Study. Family Business Review 19(4): 275. González AL, Correa A, Acosta M (2002) Factores determinantes de la rentabilidad financiera de las PYMES. Revista Española de Financiación y Contabilidad 112:395. March Jordá I, Yagüe RM (2009) Desempeño en empresas de economía social. Un modelo para su medición. Revista de Economía Pública, Social y Cooperativa 64:105-131. Moreno I, Rico JM (2002) Los activos humanos como factores de competitividad de la empresa y su tratamiento contable. Revista universidad EAFIT 125. Weill L (2008) Leverage and corporate performance: Does Institutional Environment Matter? Small Business Economics 30(3):251.

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Appropriate Work Design in Lean Production Systems Dombrowski U1, Hellmich E-M.2, Mielke T.3 Abstract The demographic change has a substantial impact on the age structure of manufacturing enterprises. The specific needs of older employees have to be considered thoroughly in the design of future work systems. Today, many enterprises organize their processes according to the principles of lean production systems. In order to achieve a sustainable implementation of age and aging appropriate work design, the existing lean production systems need an appropriate modification. The paper presents an analysis of today’s work design concerning age and aging. Furthermore, it introduces four approaches for age and aging appropriate work in lean production systems.

Keywords: Lean Production System, Demographic Change, Age and Aging Appropriate, Ergonomics, Occupational Health and Safety

1 Introduction The demographic change is one of the key challenges that the European Union needs to overcome. Indicators for a demographic change are found in all EU-27 countries but some of them are affected more severely. For example, compared to the other EU-27 countries Germany shows one of the lowest fertility rates, one of

1Uwe Dombrowski( e-mail: [email protected]) Executive Director, Institute for Advanced Industrial Management. Technische Universität Braunschweig. Langer Kamp 19, 38106 Braunschweig, Germany. 2Eva-Maria

Hellmich ( e-mail: [email protected]) Research Assistant, Institute for Advanced Industrial Management. Technische Universität Braunschweig. Langer Kamp 19, 38106 Braunschweig, Germany. 3Tim

Mielke ( e-mail: [email protected]) Research Assistant, Institute for Advanced Industrial Management. Technische Universität Braunschweig. Langer Kamp 19, 38106 Braunschweig, Germany.

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the highest life expectancies and the oldest population which is already declining. (European Commission, 2011) At the moment, about 50 million people in Germany are in an employable age. In 2060, it might be only 33 million. (BMI, 2011) A second important development in this context is the rising labor participation of older workers. In 2000, 38% of employees aged 55-64 were in gainful employment. Only ten years later, this share rose to 58%. (BMAS, 2012) Therefore, enterprises have to cope with these unprecedented challenges. In this context, health and especially occupational health and safety will gain in importance. Enterprises have to assure the achievement potential during the whole working life. In order to cope with the changing abilities of older workers, especially manufacturing enterprises have to improve the age and aging appropriate (A³) work design. Today’s manufacturing industry designs its processes according to lean production systems (LPS), which represent state of the art manufacturing. (VDI, 2012) LPS are also called holistic production systems, which aim at the comprehensive and sustainable design of production. (Dombrowski, et al., 2010) However, practical experience shows that these systems focus on the improvement of quality, time and costs. The demographic change and the thereby rising importance of A³ work design have not been regarded so far. For a sustainable consideration of the changes due to an older workforce, A³ work design should be integrated in the widely spread lean production systems. Therefore, the principles, methods and tools of existing LPS have been analyzed to assess the actual significance of A³ work design in LPS. Based on the results, four strategies were derived that show possibilities for further development of LPS towards A³ work design.

2 Work Design in Lean Production Systems In modern manufacturing enterprises, lean production systems specify the details of each and every work process. LPS claim to consider the three aspects technology, organization and people. (Spath & Braun, 2003) A lean production system (LPS) is ”an enterprise-specific compilation of rules, standards, methods and tools, as well as the appropriate underlying philosophy and culture for the comprehensive and sustainable design of production. An LPS enables an enterprise to meet the requirements of today´s business environment, taking into account technological, organizational, work-force-related and economic aspects”. (Dombrowski & Schmidt, 2008) The superior goal of all LPS is the sustainable elimination of waste in all processes. (VDI, 2012), (Ohno, 1988) In this context, waste is determined from a customer’s point of view and includes all activities that do not add value to the product. As waste elimination is a basic approach in LPS, many descriptions exist. The most common are the following seven types of waste (VDI, 2012), (Ohno, 1988), 859


(Liker, 2004), (Womack & Jones, 1996): Overproduction, Waiting, Transporting, Over-processing, Inventories, Unnecessary motion and Defects. Some authors name an eighth type, the waste of unused employee creativity. (Liker, 2004) Several methods and tools support the avoidance and elimination of waste. These methods and tools are embedded in a superior structure that links the enterprise’s strategy to the principles, methods and tools of the LPS. Despite the enterprise-specific compilation of LPS, a general structure was identified, which is shown in Fig. 1. The fundamental elements of LPS are the enterprise’s targets, processes, principles, methods and tools. (VDI, 2012). One of the main differences between LPS and traditional mass production systems is the improvement process. In contrast to mass production, LPS use the continuous improvement of all processes in small but frequent steps. This improvement needs various decentralized steps that contribute to the superior goal of zero waste. (VDI, 2012) The LPS principles are based on an enterprise-specific collection, which causes a variety of principles. Most of them can be traced back to the same eight basic principles that have been described in the LPS guideline of the German association of engineers (VDI, 2012). These basic principles will be described in the following. targets

Enterprise processes

principles

methods tools

Fig. 1 Organization and structure of a lean production system

The elimination of waste is a fundamental principle that has already been mentioned above. Since waste is everything that does not contribute to customer value. The second principle is the continuous improvement process (CIP). Its aim is to question all current practices all the time and to improve them frequently. Standardization of processes is an important condition for the waste elimination and continuous improvement process. Standards help to sustain the improved state and show deviations from the desired process. The fourth principle, zero defects, contains methods and tools to prevent the appearance and identification of defects. The flow principle helps to avoid excess inventory, which results in shorter lead times. In ideal state, the lead time equals the processing time. The pull principle focuses on the material flow as well. According to this principle, every product 860


has to be linked to customer demand. Visual management is used to illustrate the actual state and the current standards. Thereby, deviations from standards can be recognized at a glance. The principle of employee orientation and management by objectives includes methods and tools for leadership in LPS.

3 Age and Aging Appropriate Work Due to the demographic change, enterprises have to adapt their future work design to an older workforce. One response to the increasing age of the workforce is the age and aging appropriate (A³) work design. The A³ work design should ensure that the processes in enterprises are designed for assuring the achievement potential during the whole working life. Therefore the A³ work design contributes positively to health, motivation and qualification of the employees across their entire working life. (Buck, et al., 2002) The age appropriate work design is aimed at adopting special measures for the group of older employees, whose performance has already changed in the course of their working lives. In comparison, the aging appropriate work design regards preventive measures. These preventive measures are supposed to maintain the achievement potential over the whole working live. Thereby false strains are avoided directly. (Kistler, et al., 2006) A lot of different measures can be attributed to the A³ work design. In particular, these measures can be allcoated to six different aspects. (Buck, et al., 2002): Ergonomic work design, Promotion of occupational health and safety, Job enrichment, Reduction of time pressure at work, Implementation of exculpatory working time models and Job rotation

4 Analysis of A³ Work Design in Lean Production Systems A recent study of the German Federal Ministry of Labour and Social Affairs shows that only 5.1 % of the examined enterprises design their processes under age and aging appropriate work aspects. Thereby enterprises have to focus on an A³ work design to cope with changing conditions. (BMAS, 2012) Based on these findings, the Institute for Advanced Industrial Management conducted a further analysis regarding A³ work design. Since LPS represent state of the art manufacturing, it was investigated how A³ work design is integrated in LPS. The LPS were analyzed in terms of their direct impact on age and aging appropriate work design. Furthermore, it was of interest whether the different LPS could at least positively influence the A³ work design if they do not have a direct impact.

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The analysis was based on the LPS guideline of the German association of engineers (VDI 2870) and the LPS of 22 enterprises. The considered enterprises operate in ten different industry sectors. Thus, it was a heterogeneous group. Most frequently represented were the automotive original equipment manufacturers (OEM) (four enterprises) and suppliers (OES) (seven enterprises). Each of the 22 enterprises have a specific LPS considering their individual requirements. So, the LPS did not only vary in their number of levels of detail, design principles and methods. They also differed in terms of content. For comparability, all of the LPS examined were normalized to the structure of the VDI 2870. Based on this standardization, the targets, principles and methods of the various LPS were analyzed concerning their consideration of A³ work design. As shown before, the A³ work design can be divided into six aspects. In this analysis, only the aspects of ergonomic work design and promotion of occupational health and safety were examined. As regards the promotion of occupational health and safety, the focus was on the consideration of occupational safety. At the target level, no direct consideration of ergonomic work design and occupational safety could be identified. The enterprise targets rather aim at involving the employees in the enterprise processes. They focus on increasing the employees’ satisfaction, identification with the enterprise, motivation and longterm employment. These aspects, however, do not lead directly to an improvement of A³ work design in terms of ergonomic work design and occupational safety. At least, they increase the motivation of employees and thus have a positive impact on the aging appropiate work design. Furthermore, it was found that ergonomic work design is not considered in any of the analyzed LPS on the principle-level. However, occupational safety is fixed in five enterprises on this level.

Fig.2 A³ Analysis of LPS

In the next step, the LPS methods have been regarded. The analysis of the methods has shown that overall 21.1% of the 805 considered methods could have a positive impact on ergonomic work design and occupational safety if they were 862


applied with this aim. Therefore, they are improving the A³ work design potentially or directly. As shown in Fig. 2, 5.2% of the methods may improve the ergonomic work design. An exemplary method is the job rotation. Job rotation means that employees change their jobs in regular intervals, which avoids a one-sided strain. Direct improvement of the ergonomic work design is included in only 0.6% of the methods. One exemplary method for direct improvement in terms of the LPS is “ergonomic work analysis tools”. The further analysis showed that 15.9% of the methods could have a positive impact on occupational safety, such as the method 5S. Result of 5S is a well-organized workplace based on standardization. This leads to an improvement in occupational safety because of avoiding accidents due to misplaced items. Only 1% of the 805 methods directly affect occupational safety. An exemplary method for this is "Visualized Safety". Corresponding results have come out in a second analysis. Thereby, workshops and projects of a German automotive manufacturer were evaluated. It was checked whether aspects for improving the ergonomic work design were part of the projects and workshops or not. The analysis of a total of 52 workshops and nine projects showed that only 5.7% of the workshops and 22.2% of the projects have focused on an improvement in ergonomics. In summary, it can be said that especially ergonomic work design is still not well enough considered in the examined LPS. In particular, it should be noted that no principle of the observed LPS directly improves the ergonomic work design. Also the consideration of ergonomic work design at the method level is very low. Only 0.6% of the examined methods take aim at direct improvement of ergonomic work design. At the moment, occupational safety is considered in five out of 23 LPS at the principle level. Just 1% of the methods have a direct impact on occupational safety. But the analysis has also shown, that many LPS methods could have a positive impact on A³ work design.

5 Strategies for A³ Work Design in LPS The previous analysis of present LPS has shown that A³ work design has not been considered consistently. As the results indicate, several methods already existing offer possibilities to improve A³ work design. Many methods just have to be refocused on the specific topic and do not need much adaption. In summary, enterprises could use the potential of LPS for A³ work design in order to cope with the new requirements due to the demographic change. Four strategies will be described in the following, which show four different ways to integrate A³ work design into existing LPS. The strategies consider the causalities in the above described LPS structure and the findings from recent analyses of existing LPS. This is necessary to achieve the desired effects and to change the LPS sustainably. The four strategies are shown in Fig. 3. 863


The structural integration describes an additional principle that regards A³ work design. The principle has to refer to a strategic goal of the enterprise in order to ensure a consistent structure. This strategy allows clustering of particular methods and tools and assures their systematic use. If the LPS follows an A³ principle, it will most likely be part of the visual LPS depiction. These depictions often serve as a logo or symbol of the LPS and are widely used in slideshows, brochures and other marketing material. Thereby, the structural integration supports the degree of awareness for A³ work design. The most common depictions of LPS are a house, a circle and the enterprise’s product. (Dombrowski, et al., 2006) The second strategy is based on a systemic integration of A³ work design. Therefore, the principle of waste elimination can be adapted. This principle represents the foundation for other principles and is a key element of every LPS. In general, this principle has the goal to eliminate activities that do not increase customer value. (VDI, 2012) Waste elimination could also contribute to eliminating activities that compromise the employee’s health and safety. Waste would then be defined from the customer’s and employee’s point of view. Consequently, the description of waste should be improved by adding non-ergonomic work, mental pressure, hazardous material, noise or other unsafe working conditions. 1 Structural integration

• A³ work design is linked to the enterpriese’s strategy and represented by a particular principle.

Systemic integration

• The definition of waste is adapted to A³. New types of waste could be nonergonomic work, mental pressure, hazardous material, noise …

2

3

Integration of new methods and tools

• Specific methods and tools for the improvement of ergonomics or occupational health and safety are integrated.

Modification of existing principles, methods and tools

• Established principles, methods and tools are modified to support A³ work design.

4

Fig. 3 Strategies for A³ work design in LPS (Dombrowski & Mielke, 2012)

The shop floor implementation of A³ Work design requires the integration of A³ methods and tools in the existing LPS. This allows to continuously integrate A³ work design into daily routines. The previously introduced analysis has shown a lack of methods that support A³ work design in LPS. Especially methods and tools for the assessment and improvement of ergonomic work conditions should be integrated. Such methods are already widely known but are not part of the LPS and due to that, not part of work design. Many enterprises already use the ergonomic 864


assembly worksheet (EAWS). (MTMaktuell, 2011) If the EAWS would be integrated in LPS, a comprehensive application could be achieved. Another benefit would be the early ergonomic assessment during the design of the process. Besides EAWS, other methods have to be integrated. Especially the so called screening methods should be used. Their results are less detailed but easy to use and no special training is necessary. The fourth strategy uses a modification of existing principles, methods and tools. Therefore, the systemic integration should have been applied. With the new understanding of waste, several basic LPS methods can contribute to A³ work design. For example, PDCA, five whys or benchmarking are easily deployable on the improvement of ergonomic work conditions or occupational health and safety. Other methods might need a little adjustment. Poka yoke could not only be used to achieve failure-proof processes, it could also provide malposition-proof processes. The well known 5S method could be extended to a 6S method: sorting, set in order, sweep, secure, standardize and sustain. Besides individual methods, also principles could be modified. The principle of standardization would be very suitable for A³ work design. Thereby, not only quality, time and costs would be regarded, the best processes in terms of occupational health and safety would be standardized as well. Another possibility is the implementation of a zero disease principle, derived from the zero defects principle. It could cluster methods and tools that reduce absenteeism due to employee illness.

6 Conclusions Many industrial countries already show significant symptoms of a demographic change. The low fertility rate and high life expectancy result in a higher average age of workforces. Enterprises have to adapt their processes to the age specific requirements of their employees. The age and aging appropriate (A³) work design combines approaches of occupational health and safety, ergonomics and age specific solutions like better lighting. The A³ work design should be integrated in already existing and well established lean production systems (LPS) in order to achieve a sustainable application. An analysis has shown that A³ work design is not suficiently regarded in presently existing LPS. Some LPS have implemented individual methods for ergonomics or safety but lack a comprehensive integration. Therefore, four strategies were introduced that show solutions to integrate A³ work design in future LPS.

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7 References BMAS, 2012. Fortschrittsreport "Altersgerechte Arbeitswelt", Berlin: Federal Ministry of Labour and Social Affairs. BMI, 2011. Demography Report, Berlin: Federal Ministry of the Interior. Buck, H., Kistler, E. & Mendius, H.-G., 2002. Demographischer Wandel in der Arbeitswelt. Stuttgart: Broschürenreihe: Demograpghie und Erwerbsarbeit. Dombrowski, U., Palluck, M. & Schmidt, S., 2006. Strukturelle Analyse Ganzheitlicher Produktionssysteme, ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, pp.553-556, No. 10. Dombrowski, U. & Schmidt, S., 2008. Framework for the Planning and Control of Lean Production System Implementation., International Journal of Agile Manufacturing. Dombrowski, U., Mielke, T. & Schulze, S., 2010. Impact of Lean Production Systems Implementation on Labor Conditions, Cernobbio, Italy: Accepted for APMS 2010. Dombrowski, U. & Mielke, T., 2012. Entwicklungspfade zur Lösung des Demografieproblems in Deutschland. Berlin: GITO-Verlag. European Commission, 2011. Demography Report 2010: Older, more numerous and diverse Europeans, Luxembourg: Publications Office of the European Union. Kistler, E. et al., 2006. Altersgerechte Arbeitsbedingungen. Dortmund: BAuA. Liker, J. K., 2004. The Toyota Way. New York: McGraw-Hill. MTMaktuell, 2011. Instruktoren aus fünf Ländern. EAWS. MTMaktuell, 1, pp. 24-25. Ohno, T., 1988. Toyota Production System. N. Y.: Productivity Press. Spath, D. & Braun, M., 2003. Menschengerechte Arbeitsgestaltung als Führungsaufgabe. wt Werkstattstechnik online, Issue H. 1/2, pp. 75-79. VDI, 2012. VDI 2870 - Lean production systems. Berlin: VDI, Beuth Verlag. Womack, J. P. & Jones, D. T., 2003. Lean Thinking. New York: Free Press.

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Model of a Public Private Partnership in the Spanish Health Context Pérez J1 Abstract The actual economic-financial crisis in Europe and specifically in Spain, and the present and future consequences associated, are endangering one of the most important achievements of democratic societies. Public Private Partnerships (PPPs), or any other ancestors or extensions, are associations between public power and private initiative, emphasize different aspects depending on the time (in fifties to develop public services, in sixties the urban renewal, in nineties the great infrastructures…), but the new way of organizing the public services, can be the most ideal and effective expression to develop them. It´s intended align the PPPs, with terminology and skills of Project Management, so as simulate the start up inside a Business Case. It´s included too, some innovative elements, which they are inside National Health Services, but no integrated like a whole. The standard of PPP, and Good Governance Policies are a second stage to implement it, always using to improve the benefits of citizens. The bad or incomplete use means a dangerous way to impoverish the most of people.

Keywords: Property and Risk, The Bests of Private Sector, Legitimize Departments, Learned Lessons Register, Complex Process

1 What We Need to Build “The Model” When a great problem come to light, or rather, when exists some threat endangering our well-being, the seeking of solution must be a whole solution, a complex solution and a seriously solution. In these moments, the genial ideas beginning to wake up, the great and efficient ideas arise, and all the people think oddly, that they are coherent and convincing solutions. However, nobody hadn´t noticed before. 1

Jesús Pérez ( e-mail [email protected]) INSISOC Group. Universidad de Valladolid.

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But moreover, in the present moments come into the play actors who take advantage of the special situation. It´s sure that these actors will play to obtain the maxim earnings from their investments; It´s legitimate!! This is the mission of private sector, and it´s what the Governments needs to collaborate with them. The private sector offers us the competence, the skills to do the tasks more efficient than the public sector. But, we´ll ( the citizens )accept it, only if the rules of the match include a free competition system, it´s the same, a system than works with the best companies competing to achieve their goals and a referee (the government) would worry of the requirements. Then, we´re going to use some keys given by a various fields of knowledge, to obtain a model valid to start an integration. To use “the whole integration” concept, I thought that the better was to seek a framework to set ideas. Framework Before set in making of this Alive Document, it´s important to define the concept of Business Case from Prince2. 1. It´s an iterative document with a permanent trading, which must demonstrate the viability. 2. It must answer, Why? 3. It must demonstrate too, why the Project has to continue (hasn´t to leave). We could go on telling interesting issues, to argue why it´s the reason to use this document (BC), but the most important it´s the useful to persuade at funder what we are doing and why we are doing, and in this case the funders are everybody, from individual taxpayers to great fortunes, which we want to achieve attract. Now, it´s divide this point so: 1. Summary of inputs given by the environment 2. Use the terminology that provides PPP knowledge to make simulations 3. Learned lessons given by other countries and other sectors

1.1 Summary of Inputs Given by the Environment Many of inputs which need to be known to set an initial design of a PPP to provide health services, are received by World Health Organization (WHO). Another source of knowledge and provider of ideas it´s “Health at a Glance Europe 2012”, an annual publication realized by Organisation for Economic Cooperation & Development and funded by European Union.

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Moreover, the first world (in economic terms) has another play rules, dictated by social networks, which shown all aspects that are hidden before. This great window, called Internet and social networks, oblige to the governments to explain the reasons to implement or no implement an reform, a cut or a resources reallocation. It´s the first stage that the most of people become aware of the needed of changes, and only can be achieved by a legitimated leadership. Here starts the success of this great project. We are going to use these premises to start the simulation: 1. Primary Care like a Red Line, the transfer isn´t let 2. Universality it´s an untouchable concept 3. It´s danger to finance the Local Health with External Founds (which must be returned) 4. Re-allocating resources to Prevent Medicine 5. Be Careful with missing epidemics and healthy conditions 6. The demographic curve makes no sustainable the actual system – Aged Rate = People 65 years older / Total People *100 – OverAged Rate = People 85 years older / People 65 years older * 100 7. The people is awareness with the problem, and accept logical changes 8. The estimations are more clears in lack of money times 9. All the parties need health services. It involves a lot of votes 10.The private health can not be profitable, too 11.The troubles in Spain are associated with The Underfinancing, the health assets are enough 12.The construction sector and the great purchases in state assets have obtained and managed too much resources, mortgaging future incomes Furthermore, we need a couple of ideas to demonstrate the suitability of a planned model. In Europe exists a key concept to measure the quality of the health system, named “Healthy Life Years”, that means Number of years of life free of activity limitation (62 years the women & 61 years the men). If we want to focus in this ratio, and besides, maintaining or increasing the traditional ratio of “Life Expectancy” (that has increased 6 years between 1980 & 2010 in EU), we should provide ourselves a new model to maintain our achieves without endangering the Public substance. In fact, the medical advances from 1940 are majority destined to old people, it´s the same, to extend the life. Finally, a few ideas of Current Health Expenditure. It´s composed of Personal Health Care (curative care, rehabilitative care, long-term care, ancillary services & medicine goods) + Collective Services (public health services + health administration).

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These costs are financed by Public Coverage (taxations + payroll taxes) and Private Complement (Cost-sharing, Pay-out-of-pocket & Duplicate markets). What is the way to maintain the system? How we marry “Healthy Life Years” and “Life Expectancy”? Are the citizens willing to pay more?

1.2 Use the Terminology that Provides PPP Knowledge to make Simulations It´s presents the PPPs like the main ingredient of this model. It´s pretend to show a few theory features of PPP, and incise the good governance in PPP applications. The motive to use PPP is the assistance to finance a commercially viable infrastructures when there are a financing gap or when the government policies are traditional, but it isn´t possible when these state is considered like insolvent. Concepts of PPP “A contractual agreement between the government and private sector paves the way for delivery for public infrastructure and/or public services” “Long-Term contracts between a private party and a government agency, for providing a public asset or service, in which the private party bears significant risk and management responsibility” PPP Value Drivers Risk Transfer-Risk Retained Full Integration incentivizes whole of life costing Innovations to seek solutions of specifying outputs Reduce costs to use public assets Focus on service delivery Transparency of costs and funding Mobilization to additional funding Accountability Stages 1 / Infrastructure Assets are New or Exist? We are going to work with existent assets, it´s the same Brownfield, for upgrading & managing existing infrastructure to a private company, that could include rehabilitating & maintaining.

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2 / What functions we transfer to the private responsibility? Here, we must focus in the operate function, whom can making in various ways: providing a bulk service, providing services directly to users or providing support services. 3 / What “PPP payment mechanism” we use? There are two classic types of payment; collecting fees from service users or by government, or a mix of both. The suitable type of payment to a model like the proposed is “Availability Payment”, by contractually defined quality. This stage introduce the term “Value for Money”, that in this case, must let what services can be exploited by private sector, and in what quality rate must be delivered to the citizens. Finally, and clearly, it´s understood in this time the public role. The public sector has the following roles, which aren´t delegable; – Decision-makers. – Referees. The public sector must to choose the best offers of tenders. – Supervise the private sector in the best interest to the citizens. Particularly, the governments be guided putting the people first, looking for necessity, with economic criteria and involve stakeholders. Furthermore, the public sector will try maintain the property of assets, and if it isn´t possible will allocate the property in relation to avoid or mitigate risks. In summary, an approach to Good Governance Principles in PPPs.

1.3 Learned Lessons: another Countries another Sectors Help us to Begin the Business Case v0. In this point we are going to identify some learned lessons in the application of PPPs in other countries and /or other type of PPPs. I prefer present them like a list, instead a redaction form because they´re very intuitive ideas.  The PPP Contract Management will consider long periods of time to set durable strategies, but not overmuch to miss the essence for that there was created.  The economic crisis can break a PPP based in collecting fees from service users.  Involve with private partners to identify which projects can be financed for PPPS.  The PPP design ought to proactively be controlled by the public sector, even when the private sector execute it.  The stages of PPPs Control & Monitoring of the Financing will be done by public sector.  Two of the main causes of PPP failures are an undefined transfer of risks and delays in the start date.  It´s very common identifying a lot of risks, but no update all of them.

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 Creating of a Public Department of PPPs, that would be the link between all actors. Besides, we will collect some applications given by specialized press. For example, in Sweden exists the SAINT GORAN´S hospital, which is one of the better examples of public private partnerships in the practice. It´s a paradigmatic case, because use the VALUE FOR MONEY, in all operative decisions, and is so because the hospital is organised on the twin lean principles: flow & quality, it´s the same, the principles that identify Value for Money. Another examples are given in Spanish press, because the public sector have come to realize of the strength of the private companies, if they act in a competition framework. So, the health media is talking of public private partnership in chronically ill patients, whom occupy beds and other resources in hospitals and would be treated by other means. Finally, we are facing with a little changes in the form of contract or develop technological advances, which are costly to taxpayers.

2 How we Use the Inputs to Obtain a Model In the first point, we identified a lot of inputs of various sources of knowledge. These were named and well-identified, but without placing. Besides, we established like framework, like a work paper a Business Case. Finally, we suggested a couple of examples of the application a PPP in the reality, in two different countries (one Latin and other Nordic). The Project Management can help us, in this paper, for rationalize the whole information, setting in a document, starting to act and controlling and monitoring in order to correcting deviations. In this chapter will see a couple of tools to modeling, but, the most important aspect is WHO IS WORKING AND FOR WHOM IS WORKING. All the attempts will be wrong and costly for the citizens, if the actors aren´t the betters. This is one of the main mission of the project manager, think about the better. Both Ipma and Pmi or Prince2 reinforce the leadership concept and the ethic principle is essential condition of a successful project. If the Project consists in a great PPP related to health, this aspect increases exponentially. We use the approach of Value for Money to demonstrate the feasibility and/or adequacy, it´s the same, to answer “Is the better for the citizens”?

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2.1 Establishment of Business Case v0 and Transformation in Business Case v1 In order to follow the mandate of European Union, we are going to modelling a PPP based in “Fall the Hospital Admissions for uncontrolled chronic conditions”. This is the main objective to improve the system. A second objective should be a better allocate of resources to make it. The motivation for using a Business Case consists in the justification to go on with the procedure. So, it´s a flexible and dynamic document with several stages to have a glance. To set an initial BC, we need an Organization Chart, a complete table of stakeholders and place them. Besides, we need building a Work Breakdown Structure (WBS) to place all the activities related in the previous point. Furthermore, it´s necessary use the templates relating with Risks and Integrated Changes Control. Integrated Changes Control

Risk Management

Organization Chart

BC v0

Stakeholders

WBS

Value For Money Ex Ante

Fig. 1 BC v0 in Construction

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2.2 Risk Management Plan & Integrated Changes Control There are two tools, two templates that shown the dynamism of this modelling. In the previous point, we have identified the importance of risk concept, specially linked at transfer of them. Both learned lessons and theoretical knowledge of PPP emphasise in the allocate responsibility and risk like one the most important aspect in this process. So, we need a template which includes as an initial situation so the changes, the several situations of these identified risks. For example, if these risks have been mitigated or avoided. Besides, new risks will be added. The last tool that I would want refer is “Integrated Changes Control”. We are choosing this template because we need a document to be validated by a legitimated organism. This document will contain all the information necessary that will help in decision-making. However, to consider useful this template and specially a document valid to continue the project or leaving this one, only should be contain value information. Another function of I.C.C. is to become in a permanent and numbered document that the most important stakeholder can see.

2.3 Value for Money to measure the Adequacy of PPP procedure Finally, it´s presented a figured term named Value for Money Ex Ante, like a concept to convert a lot of qualitative data in a number to help in decision-making. To arrive at this approach, we have taken a very serious study of “Corporación Nacional para el Desarrollo”, an organization of Government of Uruguay, who has identified various variables that they are keys to a successful project. Then, the numeric conversion consists in choose the main variables and do an easy formula to arrive a Definitive Figure. If it´s inside range accepted the process can continue. Variable X1 ( Part of a Strategic Plan) X2 ( Size Over 40MM€) X5 ( Graat Number of Stakeholders) X10 ( Create Competition) X16 ( No Urgent Process) TOTAL

Weighting 20 25 15 30 10

Fig. 2 VfM, Toward a Numeric Value

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Score 5 4 4 3 3

Result 1 1 0,6 0,9 0,3 3,8


3 Conclusions In the presentation of this paper, I´m trying to add value to the role of Project Management in the field of Health Management. A second conclusion that I have pretended include, it´s show the PPPs like a powerful weapon to build and/or to manage the most important issues to the citizens. It´s basic to implant and to apply the PPPs with methodology, without relax the controls and indicators and specially it´s critical choosing the most appropriate leaders. The last reflexion that I would refer it´s to take like complex the goal, no the means to achieve it. The main objective is meet the expectations of the citizens, in the whole meaning, that is as patient or user and like taxpayer. As we have seen in the point number 2, the framework can be easy if the ideas are well worked. Currently, we have seen a lot of news related with various fields of health management, like constructions or health process. In my opinion, many of them are opposite what I have pretended, because they are implanted for restrictions in the short term. What is to be achieved, is the belief in PPPs for guarantee the well being of the people, not only of few people.

4 References UNECE, Guidebook on Promoting Good Governance in PPP OECD (2012), Health at a Glance: Europe 2012, OECD Publishing PPIAF and World Bank Institute (2012) Public-Private Partnerships REEFRENCE GUIDE The World Health Report 2008-primary Health Care (Now more Than Ever), World Health Organization Gayle Allard & Amanda Trabant: The third way: on the border between the public and private (2008), Center of Innovation of the Public Sector of the Price & Waterhouse Foundation & IE Repullo, José R. e Iniesta, Antonio (2008) Systems and Health Services. Díez Santos Editions. PMI (2008). Project Management Body of Knowledge (PMBOK). 4ª Edition Dombkins, David (2012) PPP Contract Management, How To Manual. UNECE (United Nations Economic Commission for Europe) Alimarket Articles, 2012 & 2013 The Economist Articles 2013 Pérez Martínez, Jesús (2012) Integration of PPPs in the National Health Services University of Valladolid AEIPRO-IPMA (2009). NCB- National Competence Baseline. V 3.1. Editorial UPV Corporación Nacional para el Desarrollo (2011). Índice de Elegibilidad para seleccionar proyectos de Asociaciones Público-Privada en infraestructuras y servicios.

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Complex Networks Applied to Communication Management in Emergency Crisis Ruiz Martín C1, Ramírez Ferrero M2, González Álvarez J.L3, Poza D4 Abstract The Nuclear Emergency (NE) influence domain spreads over a large number of systems of different nature. Nuclear Emergency Plans (NEPs) are usually designed using a top-down approach, establishing a hierarchy working as a command chain. Although this provides advantages in terms of control, it might not be flexible enough to face unpredicted emergent behaviours due to complex interactions among the systems involved. Using a real case study, this work discusses the results of the communication and command chain network analysis to facilitate the assessment of key indicators to improve the NEP: resilience, adaptability and responsiveness.

Keywords: Nuclear Emergency, Nuclear Emergency Plan, Complex Networks, Communication

1

Cristina Ruiz Martín ( e-mail: [email protected]) Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid. 2 Mario Ramírez Ferrero ( e-mail: [email protected]) Grupo INSISOC. Universidad de Burgos.

3 José Luis González Álvarez ( e-mail: [email protected]) Unidad de Protección Civil y Emergencias. Delegación del Gobierno en Castilla y León. Valladolid. 4

David J. Poza ( e-mail: [email protected]) Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid. * Authors have been supported by Spanish Ministry of Science and Innovation (CONSOLIDER CSD2010-00034), Regional Government of Castilla y León (VA056A12-2), BPMSat and University of Valladolid. Special thanks to Delegación del Gobierno en Castilla y León and INSISOC’s colleagues.

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1 Introduction NEPs have to be designed for the compliance of a framework of laws, regulations and directives. Traditional approaches to warrantee this compliance use a topdown perspective to establish a hierarchical structure similar to a military command chain. This approach is focused on providing a quick, organised and effective response. It has advantages in terms of control and lack of behaviour uncertainty and information ambiguity. However, it makes more difficult to analyse the systems involved in the emergency because it does not allow management mechanisms to handle emergence due to complex interrelations among these systems. Unexpected or unmanaged emergent behaviours can modify the designed work of the system. This NEP case study (Spanish Government Gazette, 1985 and 2009) deals with the NE assuming the existence of an error-free command chain, the lack of undesired behaviours such as identity theft and that the countermeasures planed will be enough to control and mitigate the emergency. Nevertheless, after the accident at TEPCO’s Fukushima Nuclear Power Plant (NPP), the International Atomic Energy Agency (IAEA) stated the needed of improvements to strengthen management systems, response arrangements and transparency and effectiveness of communication mechanisms (Langlois, 2012). In other works, information systems for emergency response have been proposed (Turoff et al., 2003), multi-criteria decision making mechanisms have been published for radiological disasters (Parlak et al., 2012) (Geldermanna et al., 2009) or other scenarios such as e-government (Shan et al., 2012), methods for evacuation management support has been defined (Lv et al., 2013), studies about task time prediction have been carried out (Park et al., 2007), but they do not tackle the problem under an organizational and communication management point of view. Knowledge management has to be considered during a NE because of its socio-technical dimension; understanding information and communication management is a prerequisite to solve the crisis (Dogan et al., 2011). Following the work at (Ramirez et al., 2013) and (Ruiz et al., 2013), the aim of this paper will be to discuss the results of the NEP Communication Network (CN) and Command Chain Network (CCN) analysis with several purposes: to propose resilience improvements, and to identify imprecisions, complementarities and synergies to develop a better comprehensive plan, taking into account that the role of people involved in higher levels of the hierarchy is more a coordinating than a directing one. To present these objectives the following structure will be applied: section 2 will describe the modelling and analysis methodology used; section 3 will describe the NEP; section 4 will discuss the results of the CN & CCN analysis on the basis of complex networks methodology; eventually, section 5 will exhibit the conclusions and future lines of this work.

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2 Modelling and Analysis Methodology The methodology currently used in the roadmap to conceptualise and build the NEP model is based on Agent-Based Modelling (ABM) techniques, and it is summarised in Figure 1 (Galán et al., 2009). MODELLING PROCESS

THEMATICIAN

NUCLEAR EMERGENCY PLAN Abstraction NUCLEAR EMERGENCY PLAN NON-FORMAL MODEL

Analysis Interpretation Application

NUCLEAR EMERGENCY PLAN FORMAL MODEL

PROGRAMMER

COMPUTER SCIENTIST

MODELLER

Design

NUCLEAR EMERGENCY PLAN Inference NETWORK MODEL

RESULTS

Approximation

NUCLEAR EMERGENCY PLAN EXECUTABLE MODEL Coding Inference

COMPUTER PROGRAM

Fig. 1 Modelling process.

The first step was to build a theoretical model with the information provided by one of the responsible for the emergency plan (Spanish Government Gazette, 1985 and 2009). The people involved in the plan (agents), the communications among them (distinguishing the different media), the messages and the actions to be taken and the resources to be committed were identified. Then, as a starting and reference point, the model was formalised assuming that only those communications and actions specified in the NEP exist. Communications not specified in the NEP could be an important source for unpredictable emergent behaviour, so they will be taken into account in future scenarios. Once the formal model was developed, before building an executable model and carrying out dynamic analysis taking into account the interrelations among agents by actions (future works will tackle this issues), an initial study of the characteristics and properties of CN & CCN on the basis of complex networks was 878


carried out. It provided metrics to extract important information at this first stage. The result discussion is explained in section 4. It is worth mention that, for this work, according to Figure 1 scheme, the modeller, computer scientist and programmer roles have been handled by the same person. The inference process in the modeller role consists of obtaining the different parameters from the network.

3 Nuclear Emergency Plan Description The NEP establishes 3 control zones around the nuclear power plant. Its location is such that these zones extend over 77 municipalities in 3 provinces of 3 autonomous regions of the country, each one with its own regional/local administration and organisms. The NEP defines the organisational structure of the bodies involved, the resources to be committed, communication channels, situations and actions to be taken before (preventive), during (control and mitigation) and after (recovery) the emergency.

3.1 Organisational structure Depending on the implication of each organism in the emergency, two types of bodies are considered: competent and concerned. While competent bodies have direct action on the NE, concerned ones only act in some cases but may be required to inform or take some actions, so the NEP Director has to inform them about the emergency evolution. Government Presidency NSC President

NEP Director

NSC Inspector at the NPP Executive Body

PENCRA Director

Concerned Bodies

Information and Communication Cabinet

Fig. 2 Head Structure of the NEP

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Advisory Committee


Figure 2 represents the head structure of the NEP. The chair is delegated on the NEP Director, which is the overall responsible for the decisions taken, although higher National Government ranks can relieve him and assume control if necessary. Every single order must come from the NEP Director and be communicated following the hierarchy. No member accepts orders that do not come directly from any of his superiors or from the Public Security and Order Group, since they are also considered as authorities. Nuclear Safety Commission (NSC) President and PENCRA Director are at the same level as NEP Director. They have to be informed about every action taken to solve the crisis and its evolution. NSC Inspector at the NPP communicates the measures taken to solve the incident at the nuclear power plant to NEP Director directly, but he is a member of the NSC. The Advisory Committee has to advise NEP Director in decision making. Information and Communication Cabinet is charge with the media. The Executive Body has to materialise the actions commanded by the NEP Director to solve de crisis, and it is constituted by several groups, (Radiological, Health, Logistical Support, Public Security and Order and Technical Assistance and Coordination) each one with its own predefined structure. The Team Leaders of these groups are included in the head structure of the NEP. Additional Team Leaders from other institutions can be invited to join the Executive Body at the discretion of the NEP Director.

3.2 Resources and Communications Depending on their nature, three kinds of resources are considered in the NEP: specific resources (only used in NEs, such as radiation measurement and surveillance equipment); not-specific resources (also used for other emergencies); and general use resources (used for a general purpose but also needed during a NE). These resources can also be classified distinguishing between those already available since the emergency beginning (radiological protection equipment, etc.) and those the NEP Director has to request and that will be available after a period of time (CBRN equipment, buses, etc.). Two types of communications can be considered: those due to the NEP, mainly related to the command chain and information requests and reports, and those not planned but still appearing among or inside the systems. Focused on the first ones, it can be distinguished between the whole communication network, analysed at (Ramirez et al., 2013), and just the Command Chain Network (CCN) analysed at (Ruiz et al., 2013).

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3.3 States and Actuations to Overcome the Emergency Different situations to be declared at the discretion of the NEP Director are identified at the NEP. Within them, sets of actions are described relating to emergency declaration or conclusion, deployment and repositioning of teams, protection, information request, reporting, resolution of conflicts, and request of resources. It also details the operational behaviour to be followed during the whole emergency. The NE will always be governed centrally; teams may operate independently, but subordinated to the central government.

4 Discussion and Analysis of the Nuclear Emergency Plan To build the NEP model used in this research, the people involved in the nuclear emergency (agents), their hierarchy, the messages and commands, the senders and receivers and the actions to be developed by the agents have been identified. At this step we detected that one of the groups of the Executive Body (Logistical Support Group) has not documented its structure and each member’s responsibility. Inside the group, this fact can cause that the adaptation time for new hires will be longer. Between the remaining groups, it carries out that other stakeholders don’t know the way they work and they would not be able to detect possible inefficiencies. The assumptions made to build the NEP were very restrictive. It was developed assuming that there would not be contradictory or incompatible commands, everyone involved in the nuclear emergency will abide the commands as soon as possible without undesirable behaviours. Due to the great number of agents involved in the emergency, the implementation of a management communication system would reduce the probability of receiving contradictory or incompatible orders and the probability of communication channels collapse. Furthermore, it would facilitate the information managing. The functional requirements to this system are: (1) a data base implementation (with different query and write permissions) with the orders and actions assigned to the teams. (2) An auto-confirmation system for the information reception or action developed that writes this information on the data base. Once the model was built, a Communication and a Command Chain Network analysis has been done on the basis of complex networks. Figure 3 show the CN once the emergency has been declared, the executive body is assembled but no further action has been taken (Ramirez et al., 2013), (Ruiz et al., 2013). These analyses have provided metrics to evaluate and improve the NEP. It has been detected that the CN is not resilient enough. There are some services (Health Group & Logistical Support Group) whose CCN is handled by a single communication channel, so a failure in this channel can cause the isolation 881


of some agents, services or groups. To improve the NEP resilience is necessary to implement communication redundancies to avoid problems caused by a single communication channel breakdown.

Fig. 3 NEP’s Communication Network once the emergency has been declared, the executive body is assembled but no further action has been taken.

The centrality and prestige analysis has shown that in general, the most important nodes are the ones expected from the NEP design. There is an exception. The PageRank (a measure of how important is a node taken into account its connections – number of agents a node can command and number of nodes he can be commanded by) in the CCN in the deployed scenario (once all teams have been positioned) points out the most important node is the Local Emergency Plan Head of one municipality as he is the only one with a PageRank value higher to 75% of the maximum, but the design indicates the most important node should be the NEP Director. The explanation for this result is that this municipality is comparatively big and the Local Emergency Plan Head has a relatively high number of agents following his commands. On the other hand, he can be commanded by all the workers at Coordination and Technical Assistance Group and by two teams from Security and Public Order Service located at his municipality. There are several workers at Coordination and Technical Assistance Group who can order all the Local Emergency Plan Heads. This has revealed the possible existence of authentication problems of the personnel when an order is edict. 882


5 References B.O.E. (Spanish Government Gazette). January, 1985. “Law 2/1985, 21 January, on Civil Protection”. B.O.E (Spanish Government Gazette). September, 2009. “Royal Decree 1428/2009, September 11th, on the modification of the Nuclear Emergency Basic Plan approved in the Royal Decree 1546/2004”. Dogan H, Henshaw M, Ragsdell G, 2011 “The Risk of Information Management Without Knowledge Management: A Case Study”, Journal of Information & Knowledge Management, vol. 10, n 4, pp. 393-408. Galán J.M, Izquierdo L.R, Izquierdo S.S, Santos J.I, del Olmo R, López-Paredes A, Edmonds B, 2009 “Errors and artefacts in Agent-Based Modelling”, Journal of Artificial Societies & Social Simulation 12(1)1 Geldermanna J., Bertscha V., Treitza M., Frenchb S., Papamichailb K. N., Hämäläinenc R. P. 2009. “Multi-criteria decision support and evaluation of strategies for nuclear remediation management”. Omega. The International Journal of Management Science 37: 238-251. Langlois L. Accepted November 26th 2012, unpublished. “IAEA Action Plan on nuclear safety”. Energy Strategy Reviews. Lv Y., Huangb G.H., Guob L., Li Y.P., Daid C., Wange X.W., Sunb W. 2013. “A scenario-based modeling approach for emergency evacuation management and risk analysis under multiple uncertainties”. Journal of Hazardous Materials 246-247: 234-244 Newman M. E. J. 2003. “The structure and function of complex networks”, SIAM Review 45: 167-256 Park J., Jung W. 2007. “A study on the development of a task complexity measure for emergency operating procedures of nuclear power plants”. Reliability Engineering and System Safety 92: 1102–1116 Parlak A. I., Lambert J. H., Guterbock T. M., Clements J. L. 2012. “Population behavioral scenarios influencing radiological disaster preparedness and planning”. Accident Analysis and Prevention 48: 353-362. Ramirez M., Ruiz C., Gonzalez J. L., Lopez A. 2013 “Modelling of a Nuclear Emergency Plan: A Systems of Systems Engineering Approach” 8 th International Conference on System of Systems Engineering (SoSE) (in press, available at:. http://www.insisoc.org/SoSE2013/ ) Ruiz C, Gonzalez JL, Ramirez M, Lopez A. 2013 “Modelling of a Nuclear Emergency Plan: Command Chain Network Analysis” Intelligent Systems and Decision Making for Risk Analysis and Crisis Response: Proceedings of the 4th International Conference on Risk Analysis and Crisis Response, Istanbul, Turkey, 27-29 August 2013 Shan S., Wang L., Li L., Chen Y. 2012. “An emergency response decision support system framework for application in e-government”. Information Technology and Management 13: 411-427. Turoff M., Chumer M., Van de Walle B., Yao X. 2003. “The Design of a Dynamic Emergency Response Management Information System (DERMIS)”. Journal of Information Technology Theory and Application 5 (4).

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EN-07 Education

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Applying the LEGOstics Concept in Formal Education at Technical University of Cartagena Bojan P, de la Fuente Aragón MV1, Ros McDonnell L Abstract The LEGOstics training programs are under continuous development in Industrial Management Laboratory at UPCT (Spain), working together with Szabó-Szoba R&D Laboratory at Széchenyi University (Győr, Hungary). The main purpose of these innovative simulation projects is to construct special reallife environments for modeling logistics systems and phenomena (the nature of product and information flow in a supply chain, the meaning of delivery in time shipments, material handling and order picking processes of a warehouse or a factory, flexible manufacturing, work-in-process inventory management, lean thinking, etc). During the learning-by-doing LEGOstics trainings participants can get practical knowledge and develop many innovative skills to be able to construct, design and re-engineer sustainable and efficient logistics processes, and feel the responsibility of making decisions. In our paper we present how we implemented LEGOstics concept into the formal education focusing on the experiences we got during 2011-2013 at Technical University of Cartagena (Spain).

Keywords: Logistic Processes Simulation, Learning-by-doing, LEGOstics.

1 LEGOstics Modelling of Logistics Processes The collective noun LEGOstics is coming from the LEGO and LOGISTICS words: LEGO products are very suitable for modeling such semi-virtual (in most cases non-semi, but real) logistics environments. The bricks and parts are very popular, and considered as high quality innovative products to help in development of constructive skills.

1Mª

Victoria de la Fuente Aragón ( e-mail: [email protected]) Grupo GIO. ETSII. Universidad Politécnica de Cartagena. C/Dr. Fleming, s/n, 30202 Cartagena (SPAIN)

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It is important to highlight that we are using these products in totally new applications. What is really innovative in LEGOstics Laboratory: “How to use?”, not “Which type of products to use?”, so in education environments we can use also metal construction boards or any other wood-bricks – the reason why LEGO products were chosen was: the students are very familiar with, and these modelled environments are also “mobile” applications (Bajor and Bódis, 2011). The goal is to develop different environments on the same platform: analyzing and developing the processes according to the technology and real nature of logistics systems (warehousing, material handling, production and transportation). (Haapasalo and Hyvönen, 2001; Holweg and Bicheno, 2002). The present work shows the two projects developed at present course in UPCT: the GRETA and the TRUDI project.

2 The GrEta Project GrEta is a self-developed, non-official LEGO product, based on our intention to construct a relatively simple model, what is possible to build with many and totally flexible ways. The result is a nice car: GrEta.

Fig. 1 The GrEta standardized production management training

At the GrEta BoardGame there are four participants around the plotting board, each of them are assembly workers, responsible to fulfil a given assembly process and manage the material flow. During the game, the students are working together on the same model, assembling a few parts of the model, and usually there is a “master” place for final assembling. GrEta car has 8 separate functional parts: chassis, wheels, engine, engine hood, seat, computer unit, cabin, lamps. Inside the parts there are several ways again to construct, so constructing GrEta for four people has a lot of possible strategies and 888


production system structures, according to the decisions of the team based on the different personal attributes. (Haapasalo and Hyvönen, 2001; Holweg and Bicheno, 2002). They can get experience in production teamwork (allocate procedures according to different features of a given workstation – speed, accuracy, quality checking, etc.), and also in process analysis (after a round they discuss their observations, make some changes, do it again, evaluate the consequences, etc.) The main questions are: 1. 2. 3. 4.

What is the real meaning of efficiency at a given case? How to improve capacity utilization? What to measure and how to measure? How to fit different processes following each other on the best way?

Using GrEta with many types of groups (students, logistics experts, assembling workers, etc.), the participants don’t compete with each other, because their job is to improve productivity and provide high-level quality checking at the same time. Our experience is during the round by round optimization results in fast time reduction (initial average is 15 minutes, then gradually lowers to 8 and finally 3-5 minutes). The discussions generally considering:  initial strategy – better sharing of the assembling tasks  flow control – better managing of material flow (prior actions, matchmismatch of concurrent tasks)  improving the individual assembling speed, parallel assembling During spontaneous discussions a lot of theoretical knowledge is coming into practice:  Controlling viewpoint – not just financial, but time-based indicators  Sensing viewpoint – automatic detection of bottlenecks and inactive times  Performance measurement with comparing the current strategy to the previous solutions

3 The TRUDI Project The Trudi LEGOstics plotting board initially was constructed to help in the selection of new employees at a hungarian manufacturer company. With the Trudi Project the research group is developing a special mass-production system, focused on several functions: bottleneck problem analysis approach, work-in-process inventory management viewpoint, lean philosophy implementation problems, etc. (Szander et al., 2012). The plotting board is separated for 4 parts as work-stations, each sector has an operator. The 4 types of roles as system operators are: Picking, Parts assembling, 889


Final assembling, Disassembling and Selection. The system architecture is modular and convertible. The materials easily flow across the workstations. The shelving system is infinitely variable and can be placed anywhere on the table. Between the work places we use boxes for material handling.

Fig. 2 The TRUDI plotting board in operation

3.1 Measurements and Scientific Aspects of TRUDI LEGOstics Simulation Measurement of logistics performance is one of the critical factors for being able to develop a well-balanced supply chain (Holweg and Bicheno, 2002; Lewis and Maylor (2007). It is possible to measure the takt-time of each operator, and buildup a systematic and coherent performance measurement system. We realized that it’s not enough to synchronize the different processes based on their time requests. It’s a possible direction of development and new results can come if we apply barcodes on the boxes – so we can automatically monitor the products and performance of the operators during the process. As concluded during the trainings, LEGOstics simulations have many promising insights for scientific research – as we can highlight in Table 1: Table 1 LEGOstics simulations promising insights for scientific research Inventory management

Production system re-engineering

Bullwhip-effect

MRP

WIP inventory problems

JIT

Order policy

KANBAN

Outsourcing: Make or Buy decisions

Lean thinking (different colours of product – parts can stay in the same box!)

890


4 Preparation for Implementation – Create a LEGOstics Classroom Our goal was to implement the LEGOstics method into the formal education in the frame of an international collaboration between the Széchenyi István University (Győr, Hungary) and the Technical University of Cartagena – UPCT (Spain). The UPCT provided the classroom and the necessary equipments. For the first step the interactive environment was created, where we prepared the plotting boards and elaborated the course of the trainings together with the teachers of UPCT and a couple of UPCT students. When everything was prepared (trainings, trainers, and infrastructure) we integrate the LEGOstics trainings into the schedule supplementing the theoretical teaching with some practical aspects.

5 Scenario of a Lesson The lessons start with a short introduction about the learning-by-doing method and the LEGOstics, presenting the plotting boards, working processes, what the trainings are representing. Later, the participants start playing the GrEta or Trudi simulations. During the trainings, students discuss their experiences round-by-round, they describe the problems appeared. They have to make decisions and search for possible solutions: how to organize the working processes, arrange the layouts, assign the time and allocate the tasks. On each lesson, the trainers or some voluntary observers filled the report; all data of the processes (time, ideas, and problems) was registered.

5.1 Scenario of the Trudi Training The Trudi plotting board itself is rather flexible than the GrEta Board. In this simulation it is difficult to recognize the task of the operators for external observers and also for the participants. According to individual skills the bottleneck can appear at different work stations, they can get the experience about the mechanism of push and pull systems this way.

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Fig. 3 The visual guides, playing and measurement of TRUDI

There is no need for central control, the process automates itself. The operators have to communicate and collaborate, they can use visual signs to help each other and handle the system. The steps of the Trudi training are the following:  Presenting the work stations tasks (selection, order picking, assembling, disassembling)  Playing one or two sample round, being familiar with the process  Playing, measuring, evaluating, optimization

5.2 Further Direction of Development in Trudi Model Next stage of development in the Trudi plotting board is automatic measurement, or measurement with informatics support. On the trainings we realised that registering the details of the processes may get too complicated. Using some electronic devices can be an effective solution: the electronic devices with the proper programs can collect and analyze the data from this LEGOstics environment. The bests are barcodes or QR codes. The QR code can store more data and easier to read it. So we chose to use tablets, because it has the features we need: a camera, being mobile, with rechargeable batteries, appropriate screen, input possi892


bilities, and a proper operation system, software for reading QR codes and collect the data. We will put the codes to the boxes of Trudi, and use the tablet to read them, during the game. The software will save the time of reading, and the code of the item. It will be saved to the memory, in a .csv file, we can export for further use. The operator’s task consists only two easy steps: first read the codes, than save. Take much less time than the old type paper based administration.

6 Experiences The LEGOstics method was implemented in the formal education from first grade of Bachelor and final grade of Master level. In that period in Cartagena (Spain) there were more than 10 trainings, with the participation of about 100 students. We experienced that the students were really motivated to learn the logistics phenomena in practice; they were opened for collaboration and communication. During the GrEta part of the lesson, it was interesting to realize cultural, habital aspects of work organization. In our previous Hungarian experiences we concluded that the so called “general manager” usually owns the initial parts of assembling. Spanish participants usually preferred the finishing procedure and quality checking in this position. We intend to organize trainings in international groups. When the students made the Trudi part of the class, they discussed more. It was a great experience, than the operators concluded the importance of real-time communication during the process. The biggest problems were, that in the plotting board the boxes has fixed place, but they wanted to send the boxes also with the items. The visual guides gave them an inevitable help during the game.

Fig. 4 Measurement and paper-based administration

The observers measured the time, but the administration was not sufficient. First we just gave them a paper to register the times, but it was not in the manageable form for analysis. We made a documentation form and their task got easier, just fulfilling it - than discussion of results got faster. 893


6.1 Students Opinions The students enjoyed the trainings, they were interested about every aspects of it, and they made a huge effort to reach better result in the games. They communicated and worked together, so in this way they were able to optimize the processes. Generally the students said they had a good time, during and after lessons. They told us it was very interesting to utilize in practice what they learned in the courses about different logistics processes, and most of the times it’s better to see and experience theoretical things in practice. They also told that in this way, they can understand better the importance of communication and process optimization.

7 Conclusions The implementation of the LEGOstics method into the formal education was successful. Many students took part in the lessons, despite it was not compulsory. The students enjoyed the trainings; they had fun and study a lot at the same time. They could use most of their theoretical knowledge and use them during the games. They understood why it is so important to work as a team, why we put the emphasis on the communication. They were able to realize the problems and trough the discussions they tried to find the solutions. The students measured the times, and they could decide what worth to measure, what measurement points and data can be good for the further analysis, focusing on the performance. The LEGOstics in the formal education is a necessary practical part of the classes.

8 References Bajor P, Bódis T (2011) Quality thinking in LEGOstics laboratory innovations, in Quality 2011 Conference Proceedings, pp. 351-356, Neum-BIH 2011. Haapasalo H, Hyvönen J (2001) Simulating business and operations management – a learning environment for the electronics industry. International Journal of Production Economics, 73:261-272. Holweg M, Bicheno J (2002) Supply Chain Simulation – a tool for education, enhancement and endeavor. International Journal of Production Economics, 78:163-175. Lewis MA, Maylor HR (20007) Game playing and operations management education. International Journal of Production Economics, 105:134-149. Szander N, Makrai Z, Bajor P (2012) Development of Legostics environments in Szabó-Szoba laboratory, 2nd international Students Symposium, Bremen-DE, Dec 2012.

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Teaching Operation Management with GeoGebra. An example of Make-to-stock Problem Solving Calona Z1, Santos J2, Arcelus M 3 Abstract Improving classroom effectiveness is a major challenge for professors. Students’ abilities need to be nurtured, and integrating dynamic mathematics into teaching can enhance both professor and student performance. This paper presents GeoGebra as an alternative to solving make-to-stock problems in inventory management. This model has the advantage of being interactive and user-friendly, allowing students to experiment with different values and draw conclusions on their own.

Keywords: Teaching Innovation, Operation Management, Inventory Management, Geogebra, Make-to-stock

1 Introduction Professors are facing a major challenge when it comes to improving classroom effectiveness, such as creating situations that will foster students’ mental abilities and making students interact with the instructor and each other to solve a problem (McKeachie, 1999). The main tools developed to create these situations (puzzles, cognitive analogies, case studies, role-playing, problem-based learning) are called Active Learning Techniques (McCarthy and Anderson, 2000).

1

Zeyda Calona Tecnun – Universidad de Navarra. Pº Manuel Lardizábal 13, 20018 San Sebastián 2

Javier Santos García (e-mail: [email protected]) Tecnun – Universidad de Navarra. Pº Manuel Lardizábal 13, 20018 San Sebastián 3

Mikel Arcelus Alonso Tecnun – Universidad de Navarra. Pº Manuel Lardizábal 13, 20018 San Sebastián

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One of the new challenges in Active Learning Techniques consists of integrating the use of technology, especially when a technology allows students to dynamically interact in the proposing and solving of problems. Using these new techniques, which are usually based on computer software, students can understand topics better and learn faster, thereby improving their overall academic success. Active Learning Techniques are useful in recapturing students’ attention when dealing with topics where what-if scenarios can be used to analyze the impact of certain variables on the results of the problems under study or when the concept explained is complex, as is the case with mathematical concepts. At the university level, integrating dynamic mathematics into teaching can enhance the performance of both professors and students. Moreover, professors are encouraged to use and assess technology and interactive mathematics, which contributes to overall classroom effectiveness. Dynamic Mathematics Software (DMS), which supports constructions with points, lines and all conic sections, could be used as an Active Learning Technique (Hohenwarter and Preiner, 2007) that provides the typical features of a Computer Algebra System (CAS), such as function plotting, root finding, derivatives and integrals. The ability to represent functions dynamically is used by teachers of mathematics to propose a “bottom up” approach (Llobet, 2011). This approach does not use a formal and structured methodology; instead, it proposes a visual and interactive environment where students experiment before learning the concepts. Many DMS applications like Capri, Sketchpad, Microsoft Mathematics and GeoGebra are becoming popular among high school teachers, but they have not been deployed in management and engineering education (Soman, 2012) except for in the teaching of mathematics (Velichova, 2011), (Wurnig, 2008) or linear programming. Soman demonstrates the pedagogical use of GeoGebra in Operation Management, reporting that it helps students feel the implication of the decision they take. This paper presents a practical case that applies GeoGebra, a free software, to Operation Management (more specifically in production planning and scheduling problems), particularly to make-to-stock strategies. In make-to-stock problems, decisions regarding the manufacturing period affect the management total cost. GeoGebra contributes to the dynamic analysis of the effect and helps determine the optimum value for the manufacturing period.

2 GeoGebra GeoGebra emerged in 2001 as Markus Hohenwarter’s Master’s thesis (Hohenwarter and Borcherds, 2012), and since then it has become increasingly popular with teachers and researchers around the world because of its easy-to-use 896


dynamic mathematics software that combines many aspects of various mathematical packages. In addition, GeoGebra is free, and due to its open-source nature an extensive user community has developed around it. Designed specifically for educational purposes, GeoGebra can help students grasp experimental, problem-oriented and research-oriented learning in mathematics, both in the classroom and at home. Therefore, GeoGebra can be used as a tool to better explain concepts and to help students understand and learn faster.

2.1 GeoGebra Applications Although GeoGebra has been designed to solve algebraic and geometric problems, it offers a wide range of applications. For example, nowadays it is being used in various approaches to solving and explaining engineering problems such as Mohr’s Circle (Figure 1) and standard deviation (Figure 2).

Fig. 1 Example of the dynamic calculation of Mohr’s Cycle in GeoGebra (GeoGebra, 2013)

Fig. 2 Example of the dynamic study of standard deviation (GeoGebra, 2012)

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3 Make-to-stock Problems In the Make-to-stock (MTS) strategy, a family of products must be manufactured based on demand forecasts. It can be considered push-type production, and the main objective is to determine the lot size for each product and consequently the production period for the family. Traditional inventory management systems can be used to solve make-to-stock problems (Stevenson, 1998). According to inventory theory, the yearly demand for a product (D) can be produced in optimum batches (Q*), taking into account the resource production rate (P), production costs (p), setup costs (C) and inventory costs (H). Figure 3 summarizes the equations required to determine optimal cycle time (T*) and, consequently, optimal total cost (CT*).

I

Q

2CD H(1  )

Q* 

QM -D

T* 

P-D

D P

Q* 2C  D HD(1  )

CT*  D  p  C 

t

tp



T

D Q  H M Q* 2

Fig. 3 Optimum cycle time according to traditional inventory problem

The difference between the production cycle (T) and the production time for the product (tp) is known as idle time, and it must be minimized in order to increase resource effectiveness. Normally, more than one product is produced with the same set of resources, and according to the above formulas, T* will be different for each product. The challenge for Make-to-Stock strategies is to set the best cycle time for the family of products. One of the approaches to solving this problem is known as the Common Cycle Approach, where the same cycle time is set for the family (Figure 4). I

Qi  Di  T  tpi  Pi  Pi  i  T n

tp i

T

t

CT   Di  pi  i1

1 n T n Hi  Di1  i   Ci  2  T i1 i1

CT = 0  T*  T

t Fig. 4 Optimum cycle time according to the Common Cycle Approach

898

2C n

 H  D (1   ) i

i1

i

i


3.1 Make-to-Stock in Excel and GeoGebra This section describes how to implement the Common Cycle Approach using GeoGebra. For a better understanding, an example is explained and solved using Microsoft Excel and GeoGebra.

3.1.1 GeoGebra vs Microsoft Excel Microsoft Excel is the tool that is usually employed by professors to explain mathematics or operation management. It allows them to solve formulas, interact with cell values, and combine columns. In order to add some dynamism to the worksheet, it is necessary to program using Visual Basic. Furthermore, the dynamic graphical representation in Excel is limited to charts. GeoGebra has a reduced range of formulas and spreadsheets, a clearly limited number compared to Excel. In GeoGebra it is not simple to include new rows maintaining the formula structure and looses information when detecting or moving values. As a result is necessary to know in advance how to arrange tables, values and formulas in the template.

Fig. 5 GeoGebra’s Interface

However, GeoGebra offers a dynamic worksheet (Figure 5) that is more userfriendly and an easy-to-use interface. The combination of algebra, spreadsheets and graphics allows values, points and graphs to be changed dynamically. It’s as simple as dragging and dropping a variable and checking the behavior of its various values and its impact on spreadsheet cells. As a consequence it is easy to prepare a template to help student understanding and play dynamically with problem values and answer what-if questions in a simple way. 899


3.2 A practical example A company produces three different products in the same facility. The company works 250 days a year, 5 days a week. Currently, it produces yearly one cycle of each product to satisfy the demand shown below. The table also provides information about the production, set up and inventory cost. The task is to calculate the total cost based on the Common Cycle Approach. Table 1 Example data Product

Di (u/year)

pi(€/u)

Pi(u/day)

Hi(€/u year) Ci(€)

A

10000

10

200

5

1000

B

5000

40

200

20

150

C

20000

20

200

10

150

3.2.1 Microsoft Excel solution Figure 7 shows the solution using Microsoft Excel, where each cell includes a formula for solving the problem dynamically.

Fig. 7 Case study solution in Microsoft Excel

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Students can interact with the Excel model, but they are limited to changing numbers or formulas. In addition, it is not possible to plot inventory levels for the products.

3.2.2 GeoGebra solution With GeoGebra (Figure 8), the user can play with the results by changing values and analyzing how they affect the final solution, an approach that is clearly more dynamic.

Fig. 8 Case study solution in GeoGebra

The GeoGebra model allows interaction without programming by directly moving the variable to the graphics. It is also possible to combine a variable value with the value of a cell in the spreadsheet. However, the spreadsheet in GeoGebra is more limited compared to Microsoft Excel. Figures 7 and 8 show the formula for the calculation of the optimum cycle (T*) using Excel and GeoGebra, respectively. By using GeoGebra, different what-if scenarios can be easily analyzed without changing the model. Furthermore, it is possible to study the impact of an increase 901


in demand, a change in production rate, the economic impact of any change in working cycle, etc.

4 Conclusions In this paper, a new proposal for teaching Operation Management based on GeoGebra is presented. The suggested alternative for Make-to-Stock problems helps students learn more efficiently by allowing them to manipulate values via a dynamic interface. The paper’s main contributions are: (1) the integration of the new software GeoGebra in the field of operations management, not only for solving inventory problems but also for dealing with continuous improvements activities; (2) the presentation of a valuable free tool for professors, thereby improving classroom efficiency; and (3) the presentation of a valuable training methodology for students to better understand inventory concepts.

5 References GeoGebra (2012) http://www.geogebratube.org/student/m5983 GeoGebra (2013) http://www.geogebratube.org/material/show/id/26706 Hohenwarter M., Preiner J. (2007). Multiple Representations. The Journal of Online Mathematics and Its Applications, (7). Available online. Hohenwarter, M. & Borcherds, M. (2012). Geogebra software (version 4) [software]. Available from http://www.geogebra.org/cms/ Llobet, JC. (2011). Mathematization platform in a GeoGebra environment within a didactic approach “from bottom to top”. Enseñanza de las ciencias, Vol 29 (1). pp 101-114 McKeachie, W. J. (1999). Teaching tips: Strategies, research, and theory for college and university teachers. Boston: Houghton Mifflin. Patrick, J. Anderson, L. (2000). Active Learning Techniques Versus Traditional Teaching Styles: Two Experiments from History and Political Science. Innovative Higher Education, 24 (4) Soman, CA. (2012). GeoGebra: A tool for improving operations management teaching at MBA level. Proceedings of the 4th World Conference P&OM Stevenson, WJ. (1998). Production Operations Management. 6th edition. Irwin Professional Publishing Velichova, D. (2011). Dynamic Tool in Mathematical Education. 14th International Conference on Interactive Collaborative Learning (ICL). pp. 24-29 Wurnig O. (2008), Some Problem Solving examples of Multiple solutions using cas and dgs, Proceedings of the Discussing Group 9 : Promoting Creativity for All Students in Mathematics Education, The 11th International Congress on Mathematical Education, Monterrey, Mexico.

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Factors Involved in the University-industry Collaboration; a Final YearProject Approach Errasti N1, Ganzarain J, Markuerkiaga L, Martinez de Zuazo M Abstract There have been numerous calls for effective collaboration and more meaningful engagement between universities and industry. University-industry partnerships have long been realized as critical component for the successful development of a good university. This interaction between an academic institution and business and industry sector can occur through students, teachers and the administration itself. The concept "Final Year Project" (FYP) is a clear example of a relationship between the two aforementioned parties. Its main objective is to provide the opportunity for students to develop and demonstrate their abilities performing tasks individually in an efficient and well-organized way inside the industry sector. This research focuses on observations over the past 10 years’ experience of the Polytechnic School of Mondragon Unibertsitatea. The paper presents a general overview of the 4792 final projects developed during this period in all engineering specialties offered. The aim of this investigation is to analyze the main themes of the projects and check their evolution according to the needs of different organizations. Thus, the results of this analysis will help in managing the identification of the competences and skills that students need to develop, as well as choosing the tasks that must be carried out by the university researchers.

Keywords: Final Year Projects, University-industry Collaboration, Trends Analysis

1 Introduction Mondragon Goi Eskola Politeknikoa (henceforth MGEP) has a wide experience conducting final year projects, both in business and university. Therefore there is

1Nekane

Errasti Lozares ( e-mail: [email protected]) Dpto. de Mecánica y Producción Industrial. Escuela Politécnica Superior de Mondragon Unibertsitatea. Loramendi 4, 20500 Arrasate-Mondragron.

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enough information to conduct a detailed analysis of how these projects have evolved their themes, the applied technologies, etc. So far, MGEP has conducted an investigation of the evolution of the final year projects developed during the last 10 years (2000-2010) in the fields of Mechanical (Production Systems) and Industrial Organization Engineering. An article entitled "Final Year Projects as a means of University-Industry relationship measurement" (Errasti, 2012) shows the results of this analysis. Therefore, and taking into account the example of the aforementioned article, the objective of this article is to go one step further and complete the previous analysis by showing the evolution of the final year projects developed during the last 10 years, but in this case, all engineering specialities offered in MGEP will be considered.

2 University – industry Collaboration through FYPs In the last years, effective participation and collaboration between universities and industry has grown. The university-industry connection has been for a long time the key component for a successful development of a good university. Moreover, in the recent decades these interactions have steadily increased. This relationship allows effective communication with "customers," thereby promoting means for continuing improvements in university quality (Baharom et al., 2009, Zunaira, 2005) and creating benefits and profits for the nation, company and university. The objective of this work is to further analyse an important but previously poorly studied field between university-industry relations: students and their final year project (onwards FYPs) as a way of measuring university-industry interaction. For MGEP, the FYPs are viewed as the culmination of engineering studies (Ortiz-Marcos et al., 2010, Jawitz et al., 2002) where students develop a project according to their professional future, as well as it being a great opportunity to have their first experience as engineers (Martinez et al., 2010) under a professional tutor. They acquire knowledge in areas such as team working and management skills that are difficult to obtain in class (Bikfalvi et al., 2007, Bovea and Gallardo, 2006). The FYPs can be carried out both at university and in companies, always with the constant involvement of industry. The aim is to establish a student-company relationship according to the characteristics of the professional profile of the students(Vaezi-Nejad, 1993). In this way, students can see the real work of an engineer (Ortiz-Marcos et al., 2010). The aim of MGEP is that every student should have the experience of spending a year in a company or institution where they can develop their own project (Hasan, 2009). The proposed project is provided by the company, which clearly defines the objectives that must be achieved. During this year two people are 904


aware of its development: one belongs to the company itself and has direct contact with the student, as well as supervising his/her work thereby ensuring the correct implementation of the objectives defined; the other person belongs to the university and deals with the academic development and the academic issues of the FYP. Therefore, this document tries to gather the last 10 years’ experience of MGEP where 4792 projects have been carried out within 700 organizations.

3 Research Methodology The analysis has centred on all the engineering degrees taught at MGEP, that makes 14 different degrees in all. The time scope used for the analysis is 10 years, referring to FYPs developed from 2000 to 2010. During this period, a total amount of 4792 FYP have been developed in 700 organizations. Data for the analysis is contained in the data base used for FYP management. The percentage of FYPs that are carried out with involvement of industry is nearly 100%. This means that even if there is a percentage of projects that are developed at university, every project is developed within a research project where the customer is a company, so that even in those cases, there is a clear involvement of industry. Around 83% of the projects are developed outside university, and this percentage is even higher when referring to the titles of mechanical engineering (welding systems and production systems) or industrial management engineering degrees. In these cases, almost every student develops its FYP in a company (Table 1). Table 1 % of FYP developed outside the university (data correspond to period 2000-2010) Technical Engineering degrees First cycle

% 84,27

Engineering degrees Second cycle

TOTAL

% 81,74 83

In order to prepare the information for the analysis, both the projects and the companies have been categorized. The projects have been categorized according to the degree they belong to and the companies using the National Classification of Economic Activities. Once the information is ready, the statistical analysis begins. First a descriptive analysis using bar charts is carried out, and this is followed by a correlation analysis where the existence of relationships among the different variables is studied.

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4 Results At this point, the results obtained from the research are presented in graphic and table form. As has been stated before, two types of analysis have been done, a descriptive analysis first, and a correlation analysis afterwards.

4.1 General Descriptive Analysis The following figure shows the percentages of the projects developed in each specialty during the last 10 years. Most projects are carried out in the Organization Engineering specialty (with 14%) and this is directly related to the Production Systems (11%) because they share the same areas of knowledge.

14%

2% 1% 1%

9% 10%

11%

9%

1% 7% 9% 2%

12% 6%

8%

Automatic Industrial Design Electronics Fabrication Industrial Computing Computer Engineering Telecommunications Mechanics Polymers Production Organization Systems Welding Systems Telematics

Fig. 1 Percentages of each specialty projects developed during the past 10 years.

In the table below we can see the evolution of the number of projects undertaken by specialty and year.

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2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Automatic Ind. Design Electronics Fabrication Industrial Computing Computers Telecoms. Mechanics Polymers Production Organiz. Systems Welding Telematics

2000

Table 2 Projects evolution by specialty.

Total

29 10 58 26 0 32 0 0 45 0 76 67 0 0 0 343

57 39 45 53 33 28 24 0 42 0 84 88 0 0 0 493

32 31 48 27 42 31 11 0 45 0 78 51 0 0 0 396

32 44 54 37 41 25 24 0 51 0 58 60 0 0 0 426

52 46 45 36 65 34 32 0 39 0 44 98 6 9 3 509

30 55 33 43 64 32 31 0 38 4 35 67 13 11 8 464

30 36 34 25 64 35 23 16 30 5 33 48 5 17 8 409

33 68 30 39 76 50 29 19 34 12 34 58 9 17 6 514

39 47 29 21 41 34 29 16 37 3 32 52 3 19 3 405

40 53 29 20 58 34 49 26 33 0 29 39 3 13 4 430

36 49 39 13 70 35 29 22 33 1 18 37 4 12 5 403

410 478 444 340 554 370 281 99 427 25 521 665 43 98 37 4792

Figure 2 shows the percentages evolution of the different specialties proposed to the MGEP from 2000 to 2010. 100%

Telematics Welding Systems Systems Organization Production Polymers Mechanics Telecommunications Computer Engineering Computing Industrial Fabrication Electronics Industrial Design Automatic

90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Fig. 2 Percentages evolution of the different specialties.

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Looking at the graph you will notice that not all the degrees offered in 2010 were operative in 2000, and they have progressively been incorporated into the FYP process. Another point to take into account has been the type of company where FYPs have been developed, all of them classified by their size 2. The Table 3 shows the type of enterprises that have asked for FYPs in the last ten years. Table 3 Evolution of the number of FYPs by firm size and year. COMPANIES 2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Total

Micro

8

11

5

8

14

14

18

21

14

25

15

153

Small

65

102

75

84

102

67

81

107

73

75

74

905

5

3

2

1

1

0

0

0

0

0

1

13

244

355

285

305

351

310

248

323

259

224

204

3108

Medium Big N/A

21

22

29

30

41

73

60

63

59

106

109

614

Total

320

470

367

398

468

391

347

451

346

324

300

4792

As has been mentioned before, 700 different companies have collaborated with MGEP in the last 10 years, and as can be seen from Table 3, most of the FYPs are developed in big firms, namely those with more than 250 employees. And according to Figure 3, the kind of activities that are most common within these companies are those related to number 28 and 85 that belong to Manufacture of machinery and Education respectively. These are followed by Research and development (number 72) and Manufacture of electrical equipment (number 27) related activities.

Fig. 3 Percentage of FYPs related to the economic activity hold in the company (classification according to CNAE). 2

Micro enterprise . Journal of Technology Transfer, OCDE (2002). Manual de Frascati - Propuesta de Norma Práctica para Encuestas de Investigación y Desarrollo Experimental. Traducido por FECYT, 2002. OCDE (2006) y Eurostat. Manual de Oslo – Guía para la recogida e interpretación de datos sobre innovación. Traducido por Grupo Tragsa. Ortín, P.; Salas, V.; Trujillo, M. V.; Vendrell, F. (2008) La creación de Spin-off universitarios en España: Características, determinantes y resultados. Economía industrial, 2008, vol. 368, pp. 79-95. Siegel, D.S.; Waldman, D.A.; Atwater, L.E.; Link, A.N. (2004). Toward s model of the effective transfer of scientific knowledge from academicians to practitioners: qualitative evidence from

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. the commercialization of university technologies. Journal of Engineering and Technology Management, 2004, vol. 21, pp. 115-142. Santoro, M.; Gopalakrishnan, S (2000).; The institutionalization of knowledge transfer activities within industry-university collaborative ventures. Journal of Engineering and Technology Management, 2000, vol. 17, pp. 299-319. UPC. UPC el soci tecnológic de confiança (UPC el socio tecnológico de confianza), Abril 2011.

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SP-02 Investigación Operativa, Modelado y Simulación

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Comparativa de Heurísticas Multiobjetivo Voraces y Poblacionales Aplicadas a la Optimización Mono-objetivo en Entornos Industriales Flow Shop con Permutación Comparison between Multiobjective Greedy and Population Based Techniques Applied to Monoobjective Optimization in Permutation Flow Shop Environments Valledor P1, Gómez A2, Díaz D3, Priore P4, Rosillo R5 Abstract Nowadays multiple techniques can be applied to solve the permutation flow shop scheduling problem with single or multiple objectives. In real world multi-objective problems can be converted to single objective situations when sudden changes occur in the market or in the industrial processes modifying the priority of the objectives to reach. This work analyses the behaviour of a new population-based technique proposed (MA-NSGAII) and an existing greedy algorithm (RIPG), designed a priori for multi-objective problems, on flow shop monoobjective optimization with the target of minimizing the makespan.

1Pablo

Valledor Pellicer ( e-mail: [email protected]) Escuela Politécnica de Ingeniería de Gijón. Campus de Viesques, s/n. Universidad de Oviedo. 33204 Gijón. Asturias. 2Alberto

Gómez Gómez ( e-mail: [email protected]) Dpto. de Administración de Empresas. Escuela Politécnica de Ingeniería de Gijón. Campus de Viesques, s/n. Universidad de Oviedo. 33204 Gijón. Asturias. 3Diego

Díaz Fidalgo ( e-mail: [email protected]) Escuela Politécnica de Ingeniería de Gijón. Campus de Viesques, s/n. Universidad de Oviedo. 33204 Gijón. Asturias. 4Paolo

Priore ( e-mail: [email protected]) Dpto. de Administración de Empresas. Escuela Politécnica de Ingeniería de Gijón. Campus de Viesques, s/n. Universidad de Oviedo. 33204 Gijón. Asturias. 5Rafael

Rosillo Camblor ( e-mail: [email protected]) Dpto. de Administración de Empresas. Escuela Politécnica de Ingeniería de Gijón. Campus de Viesques, s/n. Universidad de Oviedo. 33204 Gijón. Asturias.

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Resumen Existen múltiples técnicas aplicadas a la resolución del problema de la planificación de trabajos en entornos flow shop con permutación con una o varias funciones objetivo. En el mundo real problemas multiobjetivo pueden pasar a ser mono-objetivo cuando se dan cambios de prioridades en los objetivos a alcanzar, en función de la situación del mercado o del proceso industrial. Este trabajo analiza el comportamiento de un nuevo algoritmo genético (MA-NSGAII) y de una técnica voraz existente (RIPG), desarrolladas a priori para solventar problemas multiobjetivo, aplicadas a un entorno de planificación flow shop con el único objetivo de minimizar el tiempo máximo de completitud de las tareas.

Keywords: Optimization, Flow Shop, Metaheuristics, Multiobjective Palabras clave: Optimización, Flow Shop, Meta-heurísticos, Multiobjetivo

1 Introducción La búsqueda de la mejor planificación de una secuencia de trabajos es una tarea muy compleja para ser realizada manualmente debido a su complejidad nopolinómica (Garey, 1976). Múltiples factores y combinaciones hacen imposible que todos los parámetros puedan ser tenidos en cuenta por una operador humano a la hora de buscar la mejor secuencia. Además de la existencia de múltiples combinaciones, existen distintas funciones objetivo, con diferentes unidades de medida, que podrían ser optimizadas simultáneamente, dando lugar al denominado problema multiobjetivo, o de forma independiente, tratándose como un problema monoobjetivo. Por nuestra experiencia, es interesante analizar si las técnicas multiobjetivo responden de forma adecuada a cambios puntuales en la función objetivo, al convertirse el problema a mono-objetivo, debido a una variación en las prioridades de los objetivos existentes. En este artículo proponemos una nueva técnica poblacional multiobjetivo, denominada MA-NSGAII, aplicada a la búsqueda de la secuencia óptima con el único objetivo de minimizar el tiempo máximo de completitud de las tareas en sistemas flow shop. Este trabajo está organizado de la siguiente manera: En la sección 2 hablamos de la estructura de los sistemas de planificación flow shop y hacemos una breve revisión de los estudios monoobjetivo y multiobjetivo existentes. La sección 3 describe el funcionamiento de la técnica voraz RIPG, sobre la que compararemos nuestra meta-heurística. La sección 4 presenta la estructura de la técnica MANSGAII. En la sección 5 mostramos los resultados experimentales. Finalmente, en la sección 6 comentamos las conclusiones del estudio.

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2 Sistemas de Planificación Flow Shop En un entorno de producción flow shop se disponen de n trabajos {j1, j2,…, j n} a ser procesador por m máquinas {m1, m2,…, mm}, donde el objetivo principal consiste en encontrar la secuencia óptima de dichos n trabajos a ser procesados por las m máquinas. Cada trabajo consiste en m operaciones, donde la jth operación debe ser procesador en la máquina j. Cada máquina únicamente puede procesar un trabajo en un determinado intervalo de tiempo. Por tanto, para que un trabajo pueda ejecutarse en la máquina j, debe haber completado su procesamiento en la máquina anterior (j-1) y además la máquina j tiene que estar disponible. Cuando la secuencia de trabajos a procesar es la misma para cada máquina, entonces nos encontramos ante la variante de flow shop con permutación (PFSP), descrita mediante la notación de Graham (Graham, 1979) F/permu/Cmax (en el caso de que la función objetivo sea la minimización del Makespan), variante de aplicación en este artículo.

2.1 Flow shop con Permutación Mono-objetivo Existen heurísticos sencillos para obtener una buen solución en función del objetivo a tratar. Siguiendo esta línea de investigación, Eric Taillard (1990) comparó las heurísticas clásicas CDS, RA (Rapid Access procedure) y NEH (Nawaz, 1983), aplicadas a la minimización del tiempo máximo de completitud de las tareas, mejorando la heurística NEH implementando un mecanismo más eficiente de inserción de trabajos. Rajendran y Ziegler (1997) propusieron una heurística eficiente con el objetivo de minimizar el TWFT (total weighted flowtime). Además de los heurísticos anteriormente citados, han surgido diversas metaheurísticas aplicadas a la optimización monoobjetivo del problema flow shop. Así, Stützle (1998) presentó un ACO (ant colony optimization) de tipo MAX-MIN para minimizar el makespan, Eliana (2006) presentó una adaptación de la técnica PSO (Particle Swarm Optimization) aplicada a la secuenciación de tareas o Ruiz (2007) presentó un algoritmo voraz (Iterated Greedy) dividido en 2 fases (destrucción y construcción basada en la inserción del NEH) aplicadas a cada secuencia.

2.2 Flow shop con Permutación Multi-objetivo En cuanto a técnicas multiobjetivo aplicadas al problema PFSP, Mohamed (2010) propuso una búsqueda Tabú con el objetivo de obtener el mejor compromiso entre los objetivos de minimización del makespan, total tardiness y total flowtime. Mi979


nella y Ruiz (2011) propusieron un algoritmo voraz, denominado RIPG, con el objetivo de minimizar el makespan (Cmax) y el total flowtime (TFT). Sha (2009) desarrolló un algoritmo PSO con el objetivo de minimizar el makespan, mean flowtime y el tiempo de inactividad de las máquinas. Pei-Chann (2008) propuso una adaptación del algoritmo genético NSGA-II, integrando la generación de cromosomas artificiales en función de conocimiento previo, denominado ACNSGA-II. En otros trabajos Tsung-Che (2011) propuso un algoritmo memético integrando la técnica NSGA-II con el heurístico NEH como algoritmo de mejora local de las soluciones obtenidas por el algoritmo genético, con el objetivo de minimizar el makespan y el total flow time.

3 Algoritmo RIPG (Restarted Iterated Pareto Greedy) Con el objetivo de evaluar la técnica MA-NSGAII propuesta en este artículo, hemos seleccionado e implementado el algoritmo RIPG, propuesto por Ruiz y Minella (2011), como técnica voraz multiobjetivo utilizada en la comparación de resultados. Dicha técnica consta de las siguientes fases (figura 1): 1. Inicialización del conjunto inicial de soluciones empleando los heurísticos NEH (Nawaz, 1983) y Rajendran (1997). 2. Selección de la solución a mejorar en función del procedimiento MCDA (Modified Crowding Distance Assignment), donde se asigna un valor de fitness a cada una de las soluciones en función del criterio de no-dominancia de soluciones. 3. Fase voraz: Se eliminan d trabajos consecutivos de la solución seleccionada en la fase anterior, para posteriormente insertar cada uno de esos d trabajos, uno a uno, en todos las posiciones posibles de la secuencia. Después se selecciona una solución a ser mejorada en la siguiente fase mediante el operador MCDA. 4. Búsqueda local sobre la solución seleccionada: Se selecciona de forma aleatoria un trabajo de la solución seleccionada y se inserta en las nneigh posiciones adyacentes a la izquierda y derecha de la posición original. Al finalizar la búsqueda únicamente se mantienen las soluciones no-dominadas encontradas. 5. En la última fase del algoritmo se chequea si es necesario reiniciar el conjunto de soluciones de forma aleatoria cuando el algoritmo se estanca en un óptimo local (detectado cuando el tamaño del conjunto de soluciones no ha variado en un número de iteraciones prefijado).

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Inicio RIPG

Inicialización

Selección (basado en MCDA)

Fase Greedy

Selección (basado en MCDA)

Búsqueda Local No

¿Terminar algoritmo?

No

¿Reiniciar?

Si

Fase de Reinicio

Si Retornar Soluciones no-dominadas

Fig. 1 Diagrama de flujos de la técnica RIPG

4 Algoritmo MA-NSGAII (Memetic Adaptation of NSGA-II) El algoritmo MA-NSGAII propuesto se basa en el algoritmo evolutivo multiobjetivo NSGA-II, desarrollado por Deb (2002) y considerado uno de los mejores algoritmos de este tipo. La técnica NSGA-II es un algoritmo genético, basado en el criterio de nodominancia a la hora de evaluar los individuos de la población y del empleo del operador crowding distance para asegurarse la exploración de nuevas zonas en el espacio de búsqueda del problema tratado. Al comienzo del algoritmo, el NSGA-II inicializa la población de forma aleatoria. En una primera fase en cada iteración, se combinan la población padre con la población de descendientes, uniéndolas. Seguidamente se ordenan los individuos de la población en base al criterio de no dominancia y se asigna un ranking a cada uno de ellos (a mayor número de individuos dominados menor ranking). Después se seleccionan los individuos que están en el último frente pareto de la población (individuos con mayor ranking), se ordenan mediante el método de crowding distance y se combinación con los individuos de menor ranking hasta alcanzar el tamaño de la población. Posteriormente se procede a seleccionar los individuos a cruzar y mutar mediante una selección binaria por torneo. Por último se une la nueva generación con la población padre y se comienza una nueva iteración. En el algoritmo propuesto en este artículo MA-NSGA-II (figura 2) hemos hecho las siguientes modificaciones al NSGA-II original:  La inicialización de la población inicial se realiza mediante un algoritmo GRASP (Greedy Randomized Adaptative Search Procedure). La mitad de la población se obtiene generando individuos con GRASP aplicado sobre la solución obtenida por NEH. La otra mitad se inicializa mediante un GRASP aplicado sobre la solución obtenida con Rajendran (1997).  El operador de cruce utilizado es el One Point Order (OP).

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 El operador de Mutación utilización es por Inversión, donde se seleccionan 2 posiciones aleatorias del individuo y se invierten los trabajos situados entre ellos.  Después de cruzar y mutar individuos se ejecuta una búsqueda local sobre los descendientes de la población, especializando y mejorando la nueva generación (incorporando una búsqueda memética iterada), basada en una búsqueda en nneigh posiciones adyacentes a partir de una posición aleatoria de la secuencia. Inicio MA-NSGAII

Inicialización de la Población

Fast Non Dominating Sorting

Crowding Distance Assignment

Binary Tournament Selection

Crossover (One Point Order)

No ¿Terminar algoritmo?

Reemplazo en la población

Búsqueda Local

Mutación (Inversión)

Si Retornar Soluciones no-dominadas

Fig. 2 Diagrama de flujos de la técnica MA-NSGAII

5 Resultados Experimentales Para demostrar el comportamiento de los algoritmos, se ha evaluado cada una de las técnicas sobre 100 instancias de la base de datos de Taillard (1993), incluyendo problemas desde 20 trabajos con 5 máquinas hasta 200 trabajos con 10 máquinas. Como métrica de rendimiento se calcula el error relativo del resultado de cada técnica con respecto a la mejor solución conocida para cada uno de los problemas con fecha de Abril 2005 (Taillard 2005). En la parametrización de los algoritmos hemos utilizado en el caso del MANSGAII, una población de tamaño 100 individuos, una probabilidad de cruce del 90% y un 10% de probabilidad de mutación. En el caso de la búsqueda local, aplicada a la población descendiente, utilizamos una búsqueda de 5-vecinos. En el caso de RIPG hemos utilizado la configuración indicada en el artículo de Ruiz (2011), donde se eliminan bloques de 5 trabajos consecutivos en la fase greedy y se utiliza una búsqueda 5-vecinos en la mejora local de las soluciones. El criterio de finalización de los algoritmos es temporal (criterio empleado en Minella y Ruiz, 2011): se detiene la ejecución cuando el tiempo de procesamiento es mayor que n*m/2*t milisegundos, siendo n el número de trabajos, m el número de máquinas y t una constante que en este trabajo hemos establecido a 100. Los resultados empíricos (figura 3) muestran la mejora de los meta-heurísticos (MA_NSGAII, RIPG) con respecto a las soluciones obtenidas mediante la heurística NEH. Ambas técnicas alcanzan incluso la mejor solución conocida para ins982


tancias de pequeño número de trabajos (ta001, ta002, ta008, ta010 o ta033), incrementándose el error respecto a la mejor solución a medida que se incrementa el tamaño de problema. El error medio relativo de la técnica MA-NSGAII es de 1.41%, mientras que el RIPG alcanza un error de 1.09%. Relative Error (%) Instance NEH MA-NSGA-II RIPG NEH MA-NSGA-II RIPG ta001 ta002 ta003 ta004 ta005 ta006 ta007 ta008 ta009 ta010 ta011 ta012 ta013 ta014 ta015 ta016 ta017 ta018 ta019 ta020 ta021 ta022 ta023 ta024 ta025 ta026 ta027 ta028 ta029 ta030 ta031 ta032 ta033 ta034 ta035 ta036 ta037 ta038 ta039 ta040 ta041 ta042 ta043 ta044 ta045 ta046 ta047 ta048 ta049 ta050

1286 1365 1159 1325 1305 1228 1278 1223 1291 1151 1680 1729 1557 1439 1502 1453 1562 1609 1647 1653 2410 2150 2411 2262 2397 2349 2362 2249 2320 2277 2733 2843 2640 2782 2868 2850 2758 2721 2576 2790 3135 3032 2986 3198 3160 3178 3277 3123 3002 3257

1278 1359 1091 1297 1235 1210 1251 1206 1255 1108 1585 1660 1500 1386 1433 1400 1486 1548 1608 1604 2305 2105 2338 2234 2298 2236 2293 2212 2242 2192 2724 2838 2621 2768 2864 2832 2732 2683 2564 2783 3064 2927 2935 3102 3046 3156 3188 3077 2940 3182

1278 1359 1089 1301 1236 1202 1239 1206 1233 1108 1586 1673 1508 1379 1420 1410 1489 1557 1604 1603 2300 2101 2328 2224 2296 2229 2280 2208 2237 2178 2724 2838 2621 2753 2863 2829 2728 2688 2561 2782 3061 2940 2918 3096 3054 3066 3156 3058 2948 3141

0.63 0.44 7.22 2.47 5.67 2.76 3.57 1.41 4.96 3.88 6.19 4.22 4.08 4.50 5.85 4.01 5.26 4.62 3.39 3.90 4.92 2.43 3.65 1.75 4.63 5.53 3.92 2.23 3.71 4.55 0.33 0.32 0.72 1.13 0.17 0.74 1.21 1.42 0.94 0.29 4.81 5.76 5.18 4.41 6.18 5.72 5.95 2.83 3.62 6.26

0.00 0.00 0.93 0.31 0.00 1.26 1.38 0.00 2.03 0.00 0.19 0.06 0.27 0.65 0.99 0.21 0.13 0.65 0.94 0.82 0.35 0.29 0.52 0.49 0.31 0.45 0.88 0.55 0.22 0.64 0.00 0.14 0.00 0.62 0.03 0.11 0.26 0.00 0.47 0.04 2.44 2.09 3.38 1.27 2.35 4.99 3.07 1.32 1.48 3.82

0.00 0.00 0.74 0.62 0.08 0.59 0.41 0.00 0.24 0.00 0.25 0.84 0.80 0.15 0.07 0.93 0.34 1.24 0.69 0.75 0.13 0.10 0.09 0.04 0.22 0.13 0.31 0.36 0.00 0.00 0.00 0.14 0.00 0.07 0.00 0.00 0.11 0.19 0.35 0.00 2.34 2.55 2.78 1.08 2.62 2.00 2.04 0.69 1.76 2.48

Relative Error (%) Best Known Solution 1278 1359 1081 1293 1235 1195 1234 1206 1230 1108 1582 1659 1496 1377 1419 1397 1484 1538 1593 1591 2297 2099 2326 2223 2291 2226 2273 2200 2237 2178 2724 2834 2621 2751 2863 2829 2725 2683 2552 2782 2991 2867 2839 3063 2976 3006 3093 3037 2897 3065

Instance NEH MA-NSGA-II RIPG ta051 ta052 ta053 ta054 ta055 ta056 ta057 ta058 ta059 ta060 ta061 ta062 ta063 ta064 ta065 ta066 ta067 ta068 ta069 ta070 ta071 ta072 ta073 ta074 ta075 ta076 ta077 ta078 ta079 ta080 ta081 ta082 ta083 ta084 ta085 ta086 ta087 ta088 ta089 ta090 ta091 ta092 ta093 ta094 ta095 ta096 ta097 ta098 ta099 ta100

4082 3921 3927 3969 3835 3914 3952 3938 3952 4079 5519 5348 5219 5023 5266 5139 5259 5120 5489 5341 5846 5453 5824 5929 5679 5375 5704 5760 6032 5918 6541 6523 6639 6557 6695 6664 6632 6739 6677 6677 10942 10716 11025 11057 10645 10458 10989 10829 10574 10807

3968 3820 3783 3896 3728 3802 3837 3811 3869 3889 5495 5290 5205 5018 5255 5139 5256 5098 5489 5328 5812 5414 5745 5867 5552 5325 5684 5709 5940 5903 6445 6448 6473 6444 6619 6614 6520 6682 6563 6599 10942 10674 11025 11010 10597 10430 10943 10828 10528 10773

3959 3806 3759 3813 3725 3785 3808 3817 3843 3868 5493 5268 5179 5018 5253 5135 5252 5108 5454 5328 5805 5403 5698 5873 5531 5327 5643 5693 5930 5903 6443 6394 6444 6409 6505 6558 6497 6658 6476 6571 10942 10571 11017 10939 10575 10387 10949 10828 10477 10727

NEH 6.03 5.86 7.88 6.61 6.20 6.33 6.70 6.69 5.58 8.60 0.47 1.52 0.85 0.18 0.30 0.08 0.25 0.51 0.75 0.36 1.32 1.94 2.61 2.56 3.88 1.36 1.95 2.55 2.74 1.25 5.47 5.50 5.87 4.59 6.03 4.71 5.81 5.28 6.41 3.78 0.74 2.25 0.94 1.54 1.15 1.25 1.24 0.92 1.30 1.24

MA-NSGA-II RIPG 3.06 3.13 3.93 4.65 3.24 3.29 3.59 3.25 3.37 3.54 0.04 0.42 0.58 0.08 0.10 0.08 0.19 0.08 0.75 0.11 0.73 1.22 1.22 1.49 1.55 0.41 1.59 1.64 1.18 0.99 3.92 4.29 3.22 2.79 4.83 3.93 4.02 4.39 4.59 2.56 0.74 1.85 0.94 1.11 0.69 0.98 0.82 0.91 0.86 0.92

2.83 2.75 3.27 2.42 3.16 2.83 2.81 3.41 2.67 2.98 0.00 0.00 0.08 0.08 0.06 0.00 0.11 0.27 0.11 0.11 0.61 1.01 0.39 1.59 1.17 0.45 0.86 1.35 1.00 0.99 3.89 3.41 2.76 2.23 3.03 3.05 3.65 4.01 3.20 2.13 0.74 0.87 0.87 0.46 0.48 0.56 0.88 0.91 0.37 0.49

Best Known Solution 3850 3704 3640 3723 3611 3681 3704 3691 3743 3756 5493 5268 5175 5014 5250 5135 5246 5094 5448 5322 5770 5349 5676 5781 5467 5303 5595 5617 5871 5845 6202 6183 6271 6269 6314 6364 6268 6401 6275 6434 10862 10480 10922 10889 10524 10329 10854 10730 10438 10675

Fig. 3 Resultados empíricos NEH, RIPG y MA-NSGAII

6 Conclusiones Un nuevo algoritmo memético basado en búsqueda poblacional y en la adaptación de la técnica multiobjetivo de referencia, NSGAII, se ha propuesto en esto trabajo, demostrando su efectividad en problemas mono-objetivo, a pesar de haber sido diseñado para problemas multiobjetivo. Basándonos en los resultados experimentales, la técnica voraz existente RIPG se comporta en promedio ligeramente mejor en un entorno mono-objetivo que el algoritmo MA-NSGAII desarrollado. En el futuro vamos a observar el comportamiento de MA-NSGAII en un entorno multiobjetivo y la mejora de la técnica con nuevos enfoques basados en la utilización de información extraída durante búsquedas en generaciones anteriores, co983


mo propone Yuh-Min en 2012 utilizando algoritmos de estimación de distribuciones (EDAs) combinados con genéticos.

7 Referencias Garey MR, Johnson DS, Sethi R (1976), The complexity of flowshop and job shop scheduling, Mathematical Operational Research 1(2):117–129, 1976. R. L. Graham, E. L. Lawler, J. K. Lenstra, and A.H.G. Rinnooy Kan (1979). Optimization and approximation in deterministic sequencing and scheduling: a survey. In Annals of Discrete Mathematics, volume 5, pages 287-326. 1979. Nawaz (1983). A heuristic algorithm for the m machine, n job flowshop sequencing problem. Omega-International Journal of Management Science, 11(1):91-95. 1983. E. Taillard (1990), Some efficient heuristic methods for the flow shop sequencing problem. European Journal Of Operational Research. Vol 47, no 1, pages 65-74. 1990. E. Taillard (1993), Benchmarks for Basic Scheduling Problems, European Journal of Operational Research, Volume 64, Issue 2, 22 January 1993, Pages 278–285. Chandrasekharan Rajendran (1997), Hans Ziegler, An efficient heuristic for scheduling in a flowshop to minimize total weighted flowtime of jobs, European Journal of Operational Research 103 (1997) 129-138. Thomas Stützle (1998), An Ant Approach to the Flow Shop Problem, In Proceedings of the 6th European Congress on Intelligent Techniques & Soft Computing (EUFIT'98). Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, and T Meyarivan (2002), A Fast Elitist NonDominated Sorting Genetic Algorithm for Multi-Objective Optimization NSGA-II, IEEE Transactions on Evolutionary Computation, Volume: 6, Issue: 2, Page(s): 182 - 197, April 2002. http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/flowshop.dir/best_lb_up.txt. Página Web de Eric Taillard (13 de Abril de 2005). Eliana M Toro (2006) Adaptación de la técnica de Particle Swarm al problema de secuenciamiento de tareas. Scientia et Technica Año XII, No 32, Diciembre de 2006. UTP. ISSN 01221701. Rubén Ruiz, Thomas Stützle (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033-2049. Pei-Chann Chang, Shih-Hsin Chen, Chin-Yuan Fan, Chien-Lung Chan (2008). Genetic algorithm integrated with artificial chromosomes for multi-objective flowshop scheduling problems. Applied Mathematics and Computation 205 (2008) 550–561. D. Y. Sha (2009) A particle swarm optimization for multiobjective flow-shop scheduling. The International Journal of Advanced Manufacturing Technology December 2009, Volume 45, Issue 7-8, pp 749-758. Bessem Kordoghli, Mohamed Jmali, Seifeddine Saadallah, Noureddine Liouene (2010), MultiObjective Scheduling of Flow-Shop Problems in Finishing Factories Using Genetic Algorithms, Journal of Textile and Apparel, Technology and Managemenet, Volume 6, Issue 3, Spring 2010. Mohamed Anis Allouche (2010), Manager’s Preferences Modeling within Multi-Criteria Flowshop Scheduling Problem: A Metaheuristic Approach, International Journal of Business Research and Management ISSN 2180-2165.Volume: 1; Issue: 2; Start page: 33; Date: 2010. Gerardo Minella, Rubén Ruiz, Michele Ciavotta (2011). Restarted Iterated Pareto Greedy algorithm for multi-objective flowshop scheduling problems. Computers & Operational Research Journal. 2011.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tsung-Che Chiang, Hsueh-Chien Cheng, Li-Chen Fu (2011). NNMA: An effective memetic algorithm for solving multiobjective permutation flow shop scheduling problems. Expert Systems with Applications Volume 38, Issue 5, May 2011, Pages 5986–5999. Yuh-Min Chen, Min-Chih Chen, Pei-Chann Chang, Shih-Hsin Chen (2012), Extended artificial chromosomes genetic algorithm for permutation flowshop scheduling problems, Computers & Industrial Engineering 62 (2012) 536–545.

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Estudio sobre el Efecto de la Complejidad e Incertidumbre en el ELSP On the Effect of Complexity and Uncertainty in the ELSP Cortés R1, García-Sabater J.P, Molina P Abstract The Economic Lot Scheduling Problem, ELSP, has been extensively studied in the literature since the early twentieth century. This work forms part of a research line that aims to describe the effect of two circumstances, which usually affect on costs under normal industrial working conditions: the level of uncertainty in the input parameters on the one hand and the particular complexity of an instance of the problem according to a different data set on the other hand. For this purpose, and by starting from the basic problem described by Bomberger in 1966, we simulate instances of the same problem, and we describe the relationship between theoretical and real costs based on the variation of the drivers described.

Resumen El problema ELSP (Economic Lot Scheduling Problem) ha sido ampliamente analizado en la literatura desde comienzos del siglo XX. El presente trabajo forma parte de una línea de investigación que pretende describir el efecto de dos circunstancias que se dan en condiciones normales en la industria y que tiene un efecto directo sobre el coste de gestión: La incertidumbre en los datos de entrada al problema por un lado, y la complejidad de un caso particular del problema en función de los datos de partida por otro. Para ello, partiendo del problema básico descrito por Bomerger en 1966, se han lanzado simulaciones de diferentes casos del mismo problema, y se analiza el comportamiento de los costes resultantes frente a los costes teóricos en función de los drivers descritos. 1Raúl

Cortés Fibla ( e-mail: [email protected]) Dpto. de Organización de Empresas. Universidad Politécnica de Valencia. Con. De Vera s/n, Valencia, Spain. * El presente trabajo se ha desarrollado gracias a la ayuda DPI2010-18243 del Ministerio de Ciencia e Innovación del Gobierno de España dentro del programa de Proyectos de Investigación Fundamental no orientada, con el título "COORDINACION DE OPERACIONES EN REDES DE SUMINISTRO/DEMANDA AJUSTADAS, RESILIENTES A LA INCERTIDUMBRE: MODELOS Y ALGORITMOS PARA LA GESTION DE LA INCERTIDUMBRE Y LA COMPLEJIDAD"

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Keywords: Scheduling, ELSP, Complexity, Uncertainty, Simulation Palabras clave: Secuenciación, ELSP, Complejidad, Incertidumbre, Simulación

1 Introducción El estudio del problema ELSP se ha centrado habitualmente en la generación de modelos matemáticos para su descripción y en la definición y análisis del comportamiento de procedimientos de resolución. En este trabajo se pretende analizar si existe una relación entre los costes totales obtenidos para la resolución del modelo teórico y los obtenidos mediante simulación. Nuestra hipótesis es que esa relación, de existir, depende del grado de complejidad y de la incertidumbre en la información de partida en cada caso concreto. Conocer dicha relación puede servir para introducir nuevos elementos de análisis al diseñar los algoritmos de control adecuados para cada versión particular del ELSP. Es importante destacar que en el presente trabajo utilizamos el término complejidad en relación con la dificultad para alcanzar e implementar una solución factible para una situación concreta del mismo problema marco, en función de los datos de partida, y no en lo relacionado con la complejidad algorítmica del problema matemático planteado, que es NP-Hard (Hsu 1989). En este sentido, hablaremos de complejidad estática o estructural del problema (Frizelle, 1996). Es evidente que trabajar con un mayor nº de ítems añade dificultad al problema marco, ante una situación estable del resto de parámetros del problema, que se refleja en un incremento de los costes totales. El nº de ítems es, en este sentido, un driver de complejidad, que tendrá un efecto directo sobre los costes para un mismo problema. Del mismo modo afecta a la complejidad del problema el nivel de homogeneidad de los productos respecto a algunas de sus características (niveles de demanda, tiempos de setup, ratios de producción, etc.). También, como ya analizó Bomberger 1966, el nivel de utilización o saturación tiene un efecto directo sobre la complejidad del problema, como se refleja en el incremento de costes totales. Otros drivers de complejidad que tiene efecto sobre los costes son, por ejemplo, la existencia de fechas de caducidad en los ítems o la existencia de marcada estacionalidad en la demanda. En cuanto a la incertidumbre, es habitual que en las situaciones reales en las que se da el ELSP en la industria, exista incertidumbre respecto al comportamiento de algunos de los datos a lo largo del horizonte de planificación. De hecho, es frecuente en la literatura la distinción entre el problema ELSP clásico (determinístico) y el problema ELSP estocástico (SELSP), (véase Sox et al.1999 y Winands 2011). Habitualmente se consideran sujetos a procesos estocásticos el comportamiento de la demanda, pero también los tiempos de proceso y de setup.

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En el presente trabajo, se han considerado como drivers de complejidad el nº de ítems y el nivel de utilización, mientras que como driver de incertidumbre del problema se ha considerado el efecto de la incertidumbre en la demanda.

2 Descripción del Problema El problema clásico ELSP consiste en la programación de varios ítems en una única máquina, en la que sólo un producto puede ser producido al mismo tiempo. Para ello, es preciso determinar el ciclo de producción para cada item tal que se minimicen simultáneamente costes de almacenamiento y de setup para el conjunto de ítems, además de definir una secuencia en la que van a ser producidos. Se considera para cada ítem, un tiempo de setup y un coste de setup, que en el problema clásico (Bomberger 1966, Madigan 1968) son independientes de la secuencia. Se conocen los ratios de producción y de demanda para cada ítem, que igualmente se consideran constantes durante el horizonte de planificación. A lo largo del texto se emplea la siguiente notación: Ínice para artículo i=1..g Tasa de demanda Tiempo de proceso Coste de setup Coste de almacenamiento Tiempo de setup Tiempo de ciclo Coste Total En la literatura se encuentran diferentes aproximaciones para resolver el problema de lotificación del ELSP. En el presente trabajo emplearemos los métodos de Solución Independiente (IS), (Harris 1913) y de Ciclo Común (CC) (Hanssmann, 1962). Otros métodos descritos son: Periodo Básico (PB), Periodo Básico Extendido (EPB) y Variación del Tamaño de Lote (TVL). Para la resolución al problema de la definición de una secuencia de producción en el ELSP, se han definido múltiples heuríticas (Delporte y Thomas, 1977, Gallego y Moon, 1992; Zipkin, 1991). En cualquier caso, la regla más comúnmente empleada es la planteada por (Segerstedt, 1999), que se basa en el ratio de cobertura o Run Out, definido como: (1) Con respecto al comportamiento de la demanda, Vergin y Lee, 1978, introducen políticas de programación dinámica ante un escenario de demanda estocástica estacionaria. El trabajo de Brander et al. 2005, analiza el comportamiento de un 988


modelo determinista ante una demanda estocástica estacionaria. Gascon et al. 1994, consideran demanda estocástica no estacionaria o dinámica, y analizan el comportamiento de heurísticas diseñadas para el problema determinista. En el presente trabajo, se emplean como métodos para la determinación del ciclo óptimo las técnicas de solución independiente (IS) y ciclo común (CC), y una heurística basada en ROI para la determinación de la secuencia. En las simulaciones, se introduce el comportamiento estocástico de la demanda.

3 Métodos Para el problema descrito, se han generado diferentes conjuntos de datos, construyendo diferentes casos para el mismo problema, y para los que, en cada uno de ellos, se han evaluado los costes totales, como costes de setup y costes de almacenamiento, correspondientes al modelo teórico, y por otro, los costes obtenidos tras el un proceso de simulación. En cada experimento, se ha ejecutado la simulación de 224 casos del problema. Para ello se ha trabajado con conjuntos de problemas con n=10, 20, 30, 40 ítems, y cuatro niveles de demanda con el correspondiente nivel de utilización 0.22;0.44;0.66;0.88. Como procedimiento de resolución para la determinación del ciclo económico se han empleado los procedimientos de ciclo común (CC) y solución independiente (IS). Además, en cada caso se ha empleado coeficientes de variación de la demanda desde 0 hasta 0.3 en intervalos de 0.05. Deliberadamente, para el conjunto de problemas generados, se ha tratado de mantener una estructura análoga al problema de Bomberger para 10 ítems. Se han utilizado los mismo ratios de demanda y de producción para cada ítem, los mismos tiempos de setup, así como los mismos costes de almacenamiento y setup. Para introducir el driver de complejidad nº de ítems, se ha optado por multiplicar por n=1, 2, 3 y 4 el nº de ítems respecto al problema con n=10 items, reduciendo la demanda de cada uno de ellos en función del mismo factor. De esta forma para un mismo nivel de utilización, en el problema de 20 ítems, la demanda de cada artículo es la mitad que la del mismo artículo en el problema de 10 items. Del mismo modo, para que exista una solución factible al problema es exigible la condición de factibilidad (2) Para evaluar la solución de los diferentes escenarios, se ha desarrollado un modelo de simulación de eventos discretos con el software SIMIO. La arquitectura del modelo está formada por la estructura más simple, Source – Server – Sink. Para la secuenciación de los trabajos en la simulación, se ha operado según dos procedimientos. Fija + tiempo de ciclo dinámico, mediante el cual los trabajos se 989


lanzan sólo cuando, siendo su turno en la secuencia, alcanzan su stock de reorden. Dinámica, por el que se lanza una orden de trabajo siempre que un artículo alcance su stock de reorden. En caso de que en un mismo periodo dos artículos se encuentren en esta situación, se lanza según la regla de menor ratio de cobertura, definida por Segersteed, 1999, descrita en el capitulo 2. En el caso de que ningún producto cumpla las dos condiciones iniciales, no se lanzará ninguna orden. Este algoritmo es evaluado una vez al inicio de la simulación, cada vez que finaliza la producción de una orden y al final de cada día. La técnica empleada para evaluar de los costes totales tras el proceso de simulación frente a los del problema teórico, es clave para la comprensión de los resultados del presente trabajo. Es evidente que el proceso de simulación arrojará costes diferentes a los teóricos, en función de los parámetros del problema, no considerados en el modelo, tales como stocks iniciales, reglas de secuenciación y lanzamiento, y costes de no entrega. En el presente trabajo, se ha empleado una técnica que elimina el efecto de los costes de no entrega, mediante el recálculo una vez terminada la simulación, del nivel de stock necesario para cada artículo que evita incurrir en rotura de stock. De esta forma, la simulación vuelca sobre los costes de almacenamiento, a través del “stock base” mínimo necesario que evita la eventual rotura de stock en el experimento, la diferencia entre situación teórica, y la situación simulada. En la diferencia de costes de almacenamiento queda por tanto reflejada exactamente el efecto de correr el experimento de simulación frente a la solución ideal. La tabla 1 muestra los conjuntos de experimentos lanzados, en las condiciones descritas anteriormente, en función de diferentes criterios para el Stock inicial, stock mínimo de reorden y secuencia: Tabla 1 Conjunto de experimentos

4 Resultados El experimento 1 consiste en el lanzamiento del conjunto de casos descrito en la sección 3, con el criterio de secuenciación Dinámica descrito. Como stock mínimo de reorden para cada artículo se ha definido el stock correspondiente a la demanda

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teórica consumida en el tiempo de fabricación de un lote típico, tal como muestra la tabla 1. Efecto del incremento de la utilización sobre los costes totales El incremento de la demanda tiene un efecto directo sobre los costes totales, que viene dado por la expresión: (3) para el caso de resolución mediante SI, siendo esta una cota inferior al problema y para la resolución mediante CC por la expresión: (4) Para el modelo teórico, en el caso concreto de 10 items, este comportamiento es el representado en la figura 1. En las condiciones descritas para el experimento 1, se han definido las condiciones de stock inicial para que los lanzamientos de los lotes de cada artículo dentro del ciclo común (CC) queden acompasados. En este caso, el stock inicial de un artículo viene dado por la demanda correspondiente al tiempo de proceso acumulado hasta alcanzar dicho artículo en la lista (incluyendo tiempos de proceso y setups), de manera que cada artículo alcance su stock de reorden exactamente en el instante en que existe un hueco en máquina (bajo condiciones de demanda determinista). Para esta situación, considerando este caso de 10 items, sin tener en cuenta incertidumbre en la demanda (Coef. Variación =0), se constata que, el crecimiento de los costes totales frente al nivel de utilización es exponencial. Incluso a saturaciones relativas bajas . Se comprueba que aparecen costes de almacenamiento (en forma de “stock base”), muy superiores a los teóricos, desde utilizaciones bajas, con un crecimiento exponencial que es función del índice de utilización (21%, para una saturación de 88,24%) para los experimentos en CC. Este efecto, como era de esperar, es mucho más acusado con este ajuste de los stocks iniciales para el procedimiento de resolución mediante SI. En conclusión, en los experimentos descritos, el incremento de la saturación provoca un incremento exponencial en los costes totales. El efecto se mantiene aún en el caso de emplear técnicas heurísticas de secuenciación ajustadas (como en el caso de CC), aunque en ese caso se reduce y retrasa su aparición en función del nivel de utilización.

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Coste ($)

Coste ($)

12000

12000

Coste Setup (IS) Coste Almacenamiento (IS) Coste Setup (Sim) Coste Almacenamiento (Sim)

10000

Coste Setup(CC) Coste Almacenamiento(CC) Coste Setup (Sim) Coste Almacenamiento (Sim)

10000

8000

8000

6000

6000

4000

4000

2000

2000 22,06

44,12

66,18

22,06

88,24

44,12

66,18

88,24

Fig. 1 Comportamiento de los costes frente a la demanda (Modelo y Exp2)

Efecto del incremento del nº de ítems sobre los costes totales El efecto del nº de ítems sobre los costes totales viene dado por la expresiones 3 y 4 en función del procedimiento empleado para la determinación del tiempo de ciclo. Tras lanzar la simulación en las condiciones del experimento 1, que mediante los stocks iniciales favorecen el de acompasamiento de los lanzamientos mediante ciclo común, se obtienen los resultados mostrados en la figura 2 (por simplicidad, se muestran únicamente valores para ). Setup cost (IS) Holding cost (IS) Setup cost (SIm) Holding cost (sim)

Costs ($) 12000

10000

Costs ($)

Setup cost (CC) Holding cost (CC) Setup cost (SIm) Holding cost (sim)

12000

10000

8000

8000

6000

6000

4000

4000

2000

2000 10

20

30

10

40 No. Items

20

30

40 No. Items

Fig. 2 Comportamiento de los costes ante el nº de ítems (Modelo y Exp 1)

Como se puede comprobar el comportamiento de los costes tras la simulación sigue una regla similar ante el incremento del nº de ítems, que no cambia ante incrementos en la utilización. Únicamente aparece un desfase en los costes de almacenamiento (de nuevo en forma de “stock base”) pero que es prácticamente constante en cada nivel de saturación, y por tanto decreciente en proporción al coste total. Este desfase, como se puede apreciar en la figura 2, es además función de la idoneidad de la regla de secuancición empleada. 992


Efecto del incremento del nivel de utilización sobre los costes unitarios Es evidente que en las condiciones de definición del problema ELSP, un incremento en la demanda implica un incremento de los costes totales, en relación con ., tal como se ha visto al considerar el efecto del nivel de utilización, en las expresiones (3) y (4). Sin embargo, si se considera el comportamiento de los costes totales por unidad de producto, ante incrementos de la demanda, tiene lógicamente el comportamiento inverso (según

). Así el comportamiento esperado

ante incrementos del nivel de saturación es el mostrado en la figura 3 (se muestran datos para 10 items).

Costs ($) 24000

Costs ($)

Total cost per demand unit (IS) Total cost per demand unit (Sim)

Total cost per demand unit (CC)

24000

Total cost per demand unit (Sim)

22000 22000 20000

20000

18000

18000

16000

16000 14000

14000

12000

12000

10000

10000 8000

8000 22,06

44,12

66,18

22,06

88,24

44,12

66,18

88,24

Fig. 3 Comportamiento del coste unitario frente a la demanda (Modelo y Exp1)

Este comportamiento, en teoría podría ser extensible hasta alcanzar la saturación máxima del sistema, que viene limitada por la condición de factibilidad definida en la sección 3. No obstante, se comprueba que al lanzar las simulaciones de los experimentos descritos, el sistema alcanza su saturación considerablemente antes de lo previsto, lo que se refleja en la aparición de un punto de inflexión en la curva de costes unitarios. Realmente, la aparición de este punto de inflexión, indica exactamente el nivel de utilización para el cual, en las condiciones de lanzamiento actuales, el sistema alcanza su saturación máxima. Este efecto se reduce con el empleo de técnicas para la secuenciación más ajustadas, como se ha descrito a lo largo de la presente sección y se puede apreciar por la diferencia de comportamiento entre la simulación de la resolución por SI y frente a CC. Efecto del nivel de incertidumbre en la demanda sobre los costes totales Para comprobar el comportamiento de los costes en condiciones de demanda estocástica, se han lanzado las simulaciones en las condiciones descritas para los experimentos 1, 2 y 3. En los experimentos 2 y 3 la secuencia se mantiene fija, aun993


que el tiempo de ciclo es dinámico en función del momento en el que cada ítem alcanza el stock de reorden. En el experimento 3, se ha aumentado el stock mínimo de reorden de todos los artículos excepto el primero, de manera que una vez que el primer artículo de la lista alcanza su stock de reorden, los demás lotes se lanzan en cadena, tan pronto como hay un hueco en máquina, independientemente de su nivel de stock, hasta alcanzar el último de la lista, tras el cual de nuevo la máquina queda en espera de que el artículo 1 alcance su stock mínimo de reorden. En estas condiciones, se comprueba que ante mayor incertidumbre en la demanda, el coste total crece tal como se muestra en la figura 4. Costs ($) Holding cost (CC) Holding cost (Sim Exp 1) Holding cost (Sim Exp 2) Holding cost (Sim Exp 3)

8000

7000

6000

5000

4000

3000 0

5

10

15

20

25

30

Demand Coeff. Var.

Fig. 4 Comportamiento de los costes frente incertidumbre en la demanda

En particular, tras lanzar las simulaciones de los experimentos descritos no es posible confirmar que, en condiciones con considerable incertidumbre en la demanda, un programa de producción con secuencia fija presente necesariamente un peor comportamiento respecto a costes.

4 Conclusiones En el presente trabajo se presenta una metodolgía para el análisis del comportamiento de los costes totales en la simulación de diferentes casos de una versión concreta del problema ELSP, ante variaciones de diferentes drivers de complejidad e incertidumbre que afectan al problema. En concreto, mediante el empleo de esta técnica, se describen los resultados obtenidos respecto al comportamiento del problema ante variaciones en los niveles de utilización, nº de ítems e incertidumbre en la demanda. Por otro lado, se introduce el análisis del comportamiento de los costes por unidad de demanda, como herramienta para identificar el nivel de utilización real del sistema ante incrementos de la demanda. Mediante este análisis es posible identificar el nivel de utiliza994


ción límite para unas determinadas condiciones de trabajo (heurística de secuenciación, stocks de reorden, etc.) ante incrementos de la demanda. En la línea de este trabajo se pretende profundizar en el empleo de la metodología descrita, para el análisis de otros drivers de complejidad e incertidumbre, ante diferentes variantes del problema y diferentes procedimientos de resolución.

5 Referencias Bomberger, E. E. (1966) A dynamic programming approach to a lot size scheduling problem. Management Science, Vol. 12, nº. 11, p. 778. Brander, P.; Leven, E.; Segerstedt, A. (2005). Lot sizes in a capacity constrained facility - a simulation study of stationary stochastic demand. International Journal of Production Economics, Vol. 93-94, pp. 375-386. Delporte, C. M.; Thomas, L. J. (1977).Lot Sizing and Sequencing for N-Products on One Facility. Management Science, Vol. 23, nº. 10, pp. 1070-1079. Frizelle, G.D.M.. (1996) Getting the measure of complexity. Manufacturing Engineer, 75, (6) 268-270 Gallego, G.; Moon, I. (1992).The Effect of Externalizing Setups in the Economic Lot Scheduling Problem. Operations Research, Vol. 40, nº. 3, pp. 614-619. Gascon, A.; Leachman, R. C.; Lefrancois, F. (1994).Multi-item, single-machine scheduling problem with stochastic demands: a comparison of heuristics.International Journal of Production Research, Vol. 32, nº. 3, pp. 583-596. Hanssmann, F. (1962).Operations-Research in Production and Inventory Control. J. Wiley. Harris, F. W. (1913).How many parts to make an once. Factory, The Magazine of Management, Vol. 10, nº. 2, pp. 135-6-152. Hsu, W. L. (1983).On the General Feasibility Test of Scheduling Lot Sizes for Several Products on One Machine, Management Science, Vol. 29, pp. 93-105 Madigan, J. G. (1968).Scheduling A Multi-Product Single Machine System for An Infinite Planning Period. Management Science, Vol. 14, nº. 11, pp. 713-719. Segerstedt, A. (1999).Lot sizes in a capacity constrained facility with available initial inventories. International Journal of Production Economics, Vol. 59, nº. 1-3, pp. 469-475. Sox, C. R.; Jackson, P. L.; Bowman, A.; Muckstadt, J. A. (1999). A review of the stochastic lot scheduling problem. International Journal of Production Economics,Vol. 62, nº. 3, pp. 181200. Vergin, R. C.; Lee, T. N. (1978).Scheduling Rules for Multiple Product SingleMachine System with Stochastic Demand. Infor, Vol. 16, nº. 1, pp. 64-73. Winands E.M.M., Adan I.J.B.F., Van Houtum G.J., (2011) The stochastic economic lot scheduling problem: A survey, European Journal of Operational Research, Vol. 210, pp 1-9, Zipkin, P. H. (1991).Computing Optimal Lot Sizes in the Economic Lot Scheduling Problem. Operations Research, Vol. 39, nº. 1, pp. 56-63.

995


SP-03 Logística, Producción y Sistemas de Información

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Mejora del Sistema Productivo mediante Value Stream Mapping. Aplicación a una Empresa de Diseño Manufacturing performance improvement using Value Stream Mapping, application to a design company. De la Fuente MV1, Alonso M, Hontoria E, Ros L Abstract The objective of this paper is to apply the technique Value Stream Mapping in a manufacturer of logos. This sector demands high innovation in its products and manufacturing processes, forcing companies to concentrate large human and financial efforts to improve those areas. The application of this technique in the company has achieved the reorganization of the processes, reducing cycle times (25%) and lead times (46%).

Resumen El objetivo de este trabajo es la aplicación de la técnica Value Stream Mapping en un fabricante de logos. Se trata de un sector que demanda gran innovación en sus productos y procesos productivos, obligando a que se concentren grandes esfuerzos humanos y económicos en mejorar dichas áreas. La aplicación del VSM en la empresa bajo estudio ha logrado la reorganización del proceso productivo, reduciendo los tiempos de proceso (25%) y de servicio al cliente (46%).

Keywords: Value Stream Mapping, Process Improvement, Cycle-time, Lead-time Palabras clave: Value Stream Mapping, Mejora de procesos, Tiempo de Ciclo, Tiempo de Proceso

1Mª

Victoria de la Fuente Aragón ( e-mail: [email protected]) Grupo GIO. ETSII. Universidad Politécnica de Cartagena. C/Dr. Fleming, s/n, 30202 Cartagena (SPAIN)

999


1 Introducción Actualmente uno de los principales problemas de las empresas europeas son sus altos costes productivos, lo que supone una desventaja a la hora de competir en el actual mercado global. Por ello, las empresas deben centrar sus esfuerzos en optimizar sus procesos productivos y eliminar todos aquellos desperdicios que no añadan valor al producto. Las herramientas que engloba la filosofía Lean Manufacturing son muy adecuadas para este tipo de problemas. En concreto, la técnica Value Stream Mapping ayuda a la identificación de despilfarros y a la reorganización de los procesos. En este trabajo se presenta como una empresa fabricante de logos publicitarios aplica la técnica Value Stream Mapping con el objetivo de descubrir los desperdicios y proponer mejoras en la organización de los procesos, analizando el estado productivo actual y presentando unas propuestas de rediseño de sus procesos.

2 Value Stream Mapping. Metodología Value Stream Mapping (VSM) es una herramienta Lean que ayuda a visualizar los procesos y a representar los flujos de material e información que existen en el proceso actual y que podrían ser mejorados mediante esta herramienta (Rother y Shook, 1998; LERC, 2004). La aplicación del VSM se realiza con el fin de apoyar a las empresas manufactureras en el proceso de rediseño de sus entornos productivos, buscando mejorar la agilidad y capacidad de respuesta de las empresas, de cara a desarrollar cadenas de valor más competitivas, eficientes y flexibles con las que afrontar las dificultades de la economía actual (Womack y Jones, 1994; Sullivan et al., 2002; Shah y Ward, 2007; Mo, 2009). La metodología para una correcta utilización del VSM es la siguiente:  Seleccionar la familia de productos. Se elige un grupo de productos que pasan a través de procesos similares y equipos comunes durante su producción.  Dibujar el estado actual del sistema de producción. En esta fase se recoge toda la información necesaria de la planta. Además de los procesos se debe recoger información sobre las siguientes variables: Tiempo de Ciclo, Tiempo de Preparación, Tiempo Disponible, y Lead Time.  Dibujar el sistema futuro de producción. En base a los defectos detectados en la representación de la fase anterior se plantean acciones para la mejora del sistema productivo actual.  Plan de trabajo e implementación. En esta fase se empieza a preparar un plan de implementaciones que describa de un modo breve como debe ser alcanzado el estado futuro.

1000


3 Aplicación de la Herramienta Value Stream Mapping a una Empresa Fabricante de Logos Kibsgaard es una compañía danesa con más de 50 años de experiencia en el desarrollo de logos y rótulos para equipos de televisión, de música, ordenadores y telefonía. Actualmente la producción de esta empresa se divide en dos grandes familias, los logos y los rótulos, con procesos productivos totalmente diferentes según el material a utilizar, aluminio o plástico. La fabricación de los logos de plástico posee una tecnología pionera y única lo que hace que su producción sea muy rentable. Los logos de aluminio tienen una tecnología de fabricación mucho más convencional y extendida, de forma que la única manera de conseguir alguna ventaja competitiva es mediante la mejora de esta parte del sistema productivo.

3.1 Análisis del Estado Actual de la Producción Las etapas del sistema productivo actual para los logos de aluminio son: 1. REDUCIDO. La materia prima inicial son planchas de aluminio de 2x1m 2 que deben ser cortadas en chapas de un tamaño 10x20 cm2 para su procesado. 2. ESTAMPADO. Las chapas cortadas son estampadas en prensas hidráulicas 3. CORTE. Las chapas estampadas son colocadas en un bastidor para que con la prensa se corte la chapa en los artículos estampados con anterioridad. 4. LIMPIEZA. Mediante una serie de tratamientos químicos y mecánicos se consigue que los logos, ya divididos individualmente, queden limpios de aceite. 5. PREPARACION PARA PINTADO. Los logos, ya limpios, son montados en tiras adhesivas. Este proceso lo hacen los empleados en sus propias casas, por lo que no añaden tiempo al proceso, pero se verá reflejado en el stock intermedio. Los logos con sus tiras adhesivas son colocados sobre las bandejas. 6. PINTADO de los logos con el color correspondiente en cada caso. 7. REDUCIDO CON DIAMANTE. En este proceso los logos son colocados por los operarios en bases metálicas para ponerlos sobre el bastidor de las máquinas que realizan el proceso de pulido de la superficie del logo mediante diamante. 8. INSPECCION DE LA CALIDAD. Es el último paso del proceso productivo, en el que el operario realiza la inspección visual de los logos terminados. En el proceso productivo se diferencia entre logos pequeños y logos grandes. Para el análisis de procesos y toma de datos, se ha determinado “la bandeja” como unidad de producción a utilizar en el estudio de productividad, debido a su tamaño fijo, y permite referenciar los tiempos medidos en cualquier proceso a dicha medida establecida. La capacidad de las bandejas depende del tamaño de los logos, siendo de 340 logos pequeños y de 108 logos grandes. 1001


En la figura 1 se muestra el flujo de producción que siguen los productos desde que entran en fábrica hasta que son entregados al cliente. Se puede observar que las etapas descritas son realizadas de forma secuencial. En la figura también se recogen los flujos de información, centralizados por el control de producción, ya que es aquí donde se reciben todas los pedidos de los clientes. En base a estas órdenes se realizan los pedidos a los proveedores. Además, el control de la producción es el encargado de la supervisión de todos los trabajos en los diferentes procesos mediante un programa de control semanal así como del control del programa diario de inspección. Tras el análisis del proceso productivo se calculó el tiempo de ciclo de los logos grades y pequeños, así como el lead time de ambos casos (ver tabla 1). En el escenario actual se han descubierto los siguientes desperdicios:  Sobreproducción, como resultado de cumplir los programas de producción tradicionales teóricos, a partir de datos basados en previsiones.  Inventario en curso, como consecuencia de un layout funcional.  Sobreprocesamiento, originado por actividades que no añaden valor al producto (p.e. control de calidad final).  Unidades defectuosas, originadas por la no responsabilidad de los operarios sobre la calidad de los productos.

Fig. 1 Mapa del Estado actual del proceso productivo de los logos de aluminio

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3.2 Estado Futuro de la Producción. Propuestas La sobreproducción es la fuente de desperdicio mas importante, no sólo por el exceso de inventario en curso sino también por la cantidad de producto acabado almacenado, por los trabajos dobles realizados y por la necesidad de personal y de maquinaria. Para que la empresa implante el concepto Lean mediante la técnica VSM se han adoptado las siguientes políticas de actuación:

1. Producir según el Takt-time de cada producto, (o frecuencia con la que debe ser producido un determinado producto, basándose en su índice de ventas). 2. Desarrollar un flujo de producción continuo donde sea posible . 3. Usar Supermarkets para controlar la producción donde el flujo no se pueda extender. (El concepto de supermarket se basa en la técnica de producción y retirada de Kanban – sistema pull). 4. Enviar el programa de producción a un único proceso –Proceso regulador-, que controlará la producción en todos los procesos anteriores a él. 5. Distribuir la producción de los diferentes productos equitativamente en el tiempo desde el proceso regulador. 6. Desarrollar la habilidad de hacer “every part every day” en los procesos de fabricación anteriores al proceso regulador. En base a estas directrices, se plantean dos propuestas de mejora para el sistema productivo. Las mejoras introducidas en la Propuesta de Mejora 1 son:  Se sitúa un Supermarket a la salida del proceso de reducido, ya que se ha detectado que esta etapa es un cuello de botella. De este modo, el proceso siguiente (estampado) retirará la cantidad que necesite cuando la necesite.  Los procesos de estampado y corte pueden ser combinados debido a que ambos poseen tiempos de ciclos muy parecidos. Esta configuración permitirá tener flujo continuo en esta zona.  En la etapa de montaje de adhesivo y pintado se han planteado dos posibles soluciones de mejora: – Método 1. Involucrar a los trabajadores que montan los logos sobre el adhesivo para que simultáneamente realicen el control de calidad de los mismos, ya que la inspección no supone un esfuerzo adicional. Después, el pintado de los logos se realizará de forma automatizada. – Método 2. En esta opción se apuesta por la automatización de los tres procesos: montaje del adhesivo, preparación para la pintura, y pintado.  Las etapas de reducido con diamante y empaquetamiento también se han combinado, ya que los operarios del proceso de reducido con diamante pueden ir formando paquetes con los logos que son acabados. Además, de este modo se elimina el control de calidad final, ya que los empleados son los responsables de detectar los defectos de los productos. 1003


Otro posible estado futuro de la producción actual de la compañía es planteado en la Propuesta de Mejora 2. Esta nueva propuesta sólo supone un cambio frente a la Propuesta de Mejora 1: la eliminación del sistema inicial de Supermarket, (ya que es el único punto de todo el proceso productivo en el que existe una discontinuidad de flujo), e implantar un proceso conjunto de reducido, estampado y corte.

4 Análisis de los Resultados La implantación de cualquiera de las propuestas de mejora planteadas supondría una reducción considerable del lead time del proceso productivo, pasando de 15 días (actualidad) a 8 días. Tabla 1 Análisis de tiempos para la situación actual y la propuestas planteadas. FASES DEL PROCESO

(s/bandeja)

REDUCIDO

Logos grandes

ESTAMPADO

Estado actual

Propuesta 1

T ciclo T prep

T ciclo1 T ciclo 2 T prep T ciclo 1 T ciclo 2 T prep

36

36

900

900

85

85

600

Logos pequeños 42,5 900

42,5 42,5

900

72

72

600

Logos grandes

108 108

600

144 1800

Logos pequeños 170 1800 CORTE

Logos grandes

36

Propuesta 2

127,5 127,5 600

108 1800

Logos pequeños 128 1800 LIMPIEZA

Logos grandes

48

48

48

40

48

40

Logos pequeños 48

48

PREPARADO PARA PINTADO

Logos grandes

900

2020 1860 300

2002 1860 300

Logos pequeños 900

2350 1860 300

2350 1860 300

PINTADO

Logos grandes

540 540 900

540

540

900

450

450

450

1850

Logos pequeños 1850 REDUCIDO CON Logos grandes 540 3600 DIAMANTE Logos pequeños 450 3600 Logos grandes

600

INSPECCION DE Logos pequeños 540 LA CALIDAD 15 LEAD TIME (días)

8

8

TIEMPO DE PROCESO

Logos grandes

6518

5086 4944

5027 4885

TIEMPO DE PROCESO

Logos pequeños 6540

5370 4880

5272 4782

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El tiempo de procesado también se ve reducido con cualquiera de las propuestas. Analizando los tiempos de ciclo de ambas propuestas (y los dos posibles métodos que incluyen), los mejores resultados se obtienen con la propuesta de mejora 2 y el método 2 (Tciclo 2), tanto para logos pequeños como grandes, tal como se muestra en la tabla 1. Se ha reducido el tiempo del proceso de los logos grandes de 6518 a 4885 s/bandeja, y de 6540 a 4.782 s/bandeja para los logos pequeños. Consiguiendo reducciones de un 25% para los logos grandes y un 27% para los logos pequeños. En la figura 2 se muestra la propuesta optima para el sistema productivo de los logos de aluminio.

Fig. 2 Propuesta de mejora 2.

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5 Conclusiones Existen diferentes posibilidades de mejorar el proceso productivo actual de la empresa. Según el mapa de situación actual de la compañía se han identificado cuatro de los siete tipos de desperdicios posibles; sobreproducción, inventario, sobreprocesamiento y artículos defectuosos. El éxito o el fracaso de la organización para alcanzar estas mejoras dependerá de la necesaria cooperación entre los directores y los trabajadores de la compañía, para lo cual será esencial formar una cultura de compañía que abarque a todos los trabajadores. Además una mejora del proceso productivo no proporcionará por si misma un aumento de los beneficios, sino que se necesitará un trabajo de liderazgo por parte de los directores de la compañía y un compromiso de los empleados para que todo lo que se reorganice funcione adecuadamente y se alcancen los resultados previstos. La intención de la dirección de la empresa es llevar a cabo la implantación de la propuesta 2 a lo larga del año 2013.

6 Referencias LERC (2004) Lean Enterprise Research Centre. Cardiff Business School. www.cf.ac.uk/carbs/lom/lerc , consultada en diciembre 2012 Mo JPT (2009) The role of lean in the application of information technology to manufacturing. Comput Ind, 60:266–276 Rother M, Shook J (1998) Learning to see: value stream mapping to add value and eliminate muda. Lean Enterprise Institute Shah R, Ward PT (2003) Lean manufacturing: context, practice bundles, and performance. J Oper Manag, 21:129–149 Shah R, Ward PT (2007) Defining and developing measures of lean production. J Oper Manag, 25:785–805. Womack JP, Jones DT (1994) From lean production to the lean enterprise. Harvard Bus rev, 72:93-103

1006


Sistema Integrado de Planificación de la Producción y Distribución para la Gestión de Excepciones An Integrated Production and Distribution Planning System for Exceptions Handling 1

2

3

Álvarez E , Villalón L , Osaba E , Díaz F4 Abstract In an international competitive environment, where companies can sell their products all over the world, communication and information exchange with other companies is of utmost importance. Nevertheless, most businesses are reluctant to share demand information or future plans with others. This paper describes an integrated production and distribution planning system in a supply chain with three stages: a manufacturer, its suppliers and customers. This system tries to provide solutions to improve the performance of the supply chain by identifying the information that must be exchanged between nodes and developing methodologies for production and distribution planning and scheduling in a coordinated manner. Moreover, a number of exceptions have been considered to make the model as realistic as possible.

Resumen En un entorno internacional tan competitivo, donde las empresas pueden vender sus productos por todo el mundo, la comunicación y el intercambio de 1Esther Álvarez de los Mozos ( e-mail: [email protected]) Deustotech. Grupo de Organización industrial y logística. Universidad de Deusto. Avenida de las Universidades, 24, 48007, Bilbao. 2Luis

Villalón de las Heras ( e-mail: [email protected]) Deustotech. Grupo de Organización industrial y logística. Universidad de Deusto. Avenida de las Universidades, 24, 48007, Bilbao.

3Eneko

Osaba Icedo ( e-mail: [email protected]) Deustotech. Grupo de Organización industrial y logística. Universidad de Deusto. Avenida de las Universidades, 24, 48007, Bilbao. 4

Fernando Díaz Martín ( e-mail:[email protected]) Deustotech. Grupo de Organización industrial y logística. Universidad de Deusto. Avenida de las Universidades, 24, 48007, Bilbao.

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información con otras empresas adquiere la máxima importancia. Sin embargo, la mayoría de las empresas son reacias a compartir informaciones sobre su demanda o sus planes futuros con otras empresas. Este artículo describe un sistema integrado de planificación de la producción y de la distribución para una cadena de suministro con tres etapas: un fabricante, sus proveedores y sus clientes. Este sistema trata de proporcionar soluciones para mejorar la gestión de la cadena de suministro mediante la identificación de la información a intercambiar entre los nodos y mediante metodologías de planificación de producción y distribución que operan de forma coordinada. Además, se han considerado una serie de excepciones para hacer el modelo lo más realista posible.

Keywords: Exceptions Handling, Supply Chain Management, Coordination in the Supply Chain Palabras clave: Gestión de Excepciones, Integración de la Cadena de Suministro; Coordinación en la Cadena de Suministro

1 Introducción Hasta hace poco tiempo, las empresas solían centrar sus esfuerzos en mejorar las tareas propias de su negocio, buscando una ventaja competitiva en el mercado al margen de otras empresas con las que trabajaban. Hoy en día, debido a factores como la gran competitividad entre empresas de todos los sectores y la globalización de los mercados, es preciso buscar fuentes de diferenciación y reducciones de coste no sólo en los procesos propios, sino también en los de los proveedores y clientes. Sin embargo, en la práctica, las empresas no suelen ser muy proclives a trabajar conjuntamente con otros miembros de las cadenas de suministro a las que pertenecen por miedo a revelar y compartir sus datos con otras empresas.

2 Alcance del Problema Este artículo describe la arquitectura de un sistema integrado de planificación de la producción y distribución de una cadena de suministro integrada por tres niveles: suministradores, fabricante y clientes. Este sistema trata de ofrecer soluciones que beneficien a la cadena de suministro en su conjunto mediante la identificación de información que a intercambiar entre los diferentes nodos y mediante el desarrollo de metodologías para la programación de la producción y la planificación de la distribución de forma coordinada. A este respecto, este artículo estudia en profundidad las implicaciones que un cambio en la cadena de suministro tiene en otras 1008


entidades relacionadas. Así, el objetivo es conectar la programación de la producción y la planificación de la distribución de las diferentes entidades de la cadena de suministro para lograr una mejor solución global. Esta investigación forma parte del proyecto PRODIS (Referencia PI2011-58, financiado por el Gobierno Vasco). Por lo que a la programación de la producción se refiere, tradicionalmente cada compañía ha generado su propio plan de producción de forma estática e independiente. Igualmente, con respecto a la distribución de pedidos a clientes, se ha analizado en profundidad el problema de asignación de rutas a vehículos, del inglés Vehicle Routing Problem, VRP. No obstante, los problemas de producción y distribución de forma dinámica atraen cada vez más interés por su cercanía con las situaciones reales y sus potenciales beneficios para las empresas. La integración de los problemas de producción-distribución apenas se ha analizado en la literatura (Park y Hong, 2009), (Safei et al., 2010 ), (Bilgen y Günther, 2010). En general, estos modelos usan supuestos simplistas y trabajan únicamente de forma estática, lo que significa que no son fácilmente aplicables en las empresas. Esta investigación propone un sistema para la programación de la producción y la planificación de la distribución integrada, con los siguientes objetivos:  Identificación de la información a transmitir entre los distintos eslabones de la cadena.  Coordinación con los proveedores y los clientes para asegurar tanto la disponibilidad de las materias primas como para ajustar la producción y la distribución a las necesidades no planificadas.  Manejo de excepciones en tiempo real.

3 Marco General del Sistema La empresa fabricante consta de múltiples plantas de producción funcionando de forma autónoma e independiente, pero capaces de compartir información y trabajar de forma conjunta si algún evento imprevisto así lo requiere. A su vez, la empresa dispone de múltiples almacenes autónomos e independientes entre sí, que también comparten información entre ellos y pueden trabajar conjuntamente con otros almacenes si fuera necesario. Los subsistemas de comunicación que se han definido en este marco son:  El subsistema de comunicación intra-planta, en el que se gestionan los eventos imprevistos que pueden ocasionar una reprogramación parcial o total del plan de producción. De la misma forma, el subsistema de comunicación intra-almacén, en el que se gestionan los eventos imprevistos que pueden ocasionar una replanificación parcial o total del plan de distribución.

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 El subsistema de comunicación inter-planta, en el que se gestionan los eventos producidos en una planta que pueden afectar a otra u otras plantas. Paralelamente, el subsistema de comunicación inter-almacén, en el que se gestionan los eventos producidos en un almacén que pueden afectar a otro u otros almacenes.  El subsistema de comunicación producción-distribución, en el que se gestionan los eventos imprevistos ocurridos en las plantas que pueden afectar a los almacenes, o los eventos imprevistos en los almacenes que puedan afectar a las plantas.  El subsistema de comunicación con la cadena de suministro, en el que se gestionan los eventos producidos en una planta que pueden afectar a proveedores y/o clientes. El marco general de comunicación del sistema se muestra a continuación (ver fig. 1).

Fig. 1 Esquema de una empresa multi-planta con múltiples almacenes

4 Excepciones Uno de los puntos más importantes que aporta este sistema es el tratamiento de excepciones en tiempo real, dando respuesta prácticamente inmediata a cualquier evento imprevisto que ocurra. Concretamente, las excepciones se han clasificado 1010


en dos grupos: internas, que son las relacionadas con la propia empresa y pueden tener su origen en la producción o en la distribución, y externas, las cuales hacen referencia a eventos que tienen su origen en los proveedores o en los clientes. Tabla 1. Tipos de excepciones Excepciones internas

Excepciones externas

Relacionadas con la Producción

Relacionadas con la Distribución

Relacionadas con los Proveedores

Relacionadas con los Clientes

Máquina averiada

Vehículo averiado

Devolución de material

Adelanto de fecha de pedido

Operario Ausente

Conductor ausente

Entrega parcial

Retraso de fecha de pedido

Orden suspendida

Retrasos por tráfico

Entrega defectuosa

Repetición de piezas defectuosas

Pedido entregado por error

Entrega cancelada

Nuevo pedido urgente

4.1 Tratamiento de Excepciones En este punto, se va a proporcionar una breve explicación sobre cómo un evento inesperado o excepción es tratado por el sistema. En particular, se va a explicar una excepción interna relacionada con la distribución, concretamente la que hemos denominado Pedido Entregado por Error. Esta excepción se produce cuando se entrega al cliente un pedido que no se corresponde con el suyo, bien debido a un error del conductor del vehículo o del etiquetado del pedido. Dependiendo del acuerdo que se alcance con el cliente para tratar este error pueden darse tres casos: 1. Dejar el pedido pendiente e incluirlo en los planes futuros. 2. Entregar el pedido de forma urgente. 3. Cancelar el pedido, por deseo del cliente. En cualquier caso, habrá que recoger el pedido entregado por error. Para ello, el pedido a recoger se considerará como uno más dentro de la ruta de reparto, con la peculiaridad de que este se recogerá una vez se terminen de entregar los pedidos al resto de los clientes.

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5 El Problema de la Distribución Como se ha explicado anteriormente, en este proyecto existen dos fases: producción y distribución. La etapa de producción es la encargada de poner a disposición de la etapa de distribución los materiales necesarios para abastecer a los clientes que solicitan la entrega de pedidos. En este problema contaremos con múltiples almacenes de distribución, a los cuales se asignan pedidos de clientes en función, entre otros, de criterios de proximidad. Esto quiere decir que se trabajará con el supuesto de que un cliente tan solo podrá ser abastecido por los vehículos asignados a un solo almacén.

5.1 Especificaciones del Problema El problema de distribución que se va a tratar es el denominado Dynamic Vehicle Routing Problem with Backhauls y Time Windows, el cual es un hibrido entre tres problemas distintos de asignación de rutas a vehículos. A continuación se explicarán por separado las tres características del problema: Dinamismo, Backhauls y Ventanas de Tiempo. Dinamismo: El dinamismo en problemas de asignación de rutas a vehículos es un campo relativamente nuevo en el que muchos investigadores están haciendo hincapié en los últimos años (Pillac et al., 2011). El dinamismo supone que las rutas previamente planificadas requieran una replanificación. En este caso, el dinamismo se va a producir debido a la aparición de ciertas incidencias o excepciones, varias de las cuales están recogidas en la tabla 1. Una vez se produzca alguna de estas incidencias, será preciso decidir si conviene replanificar alguna de las rutas (para evitar en la mayor medida posible el incumplimiento de la ruta afectada), o dejar que los clientes implicados se queden sin servicio. Para ello, se calcularán los posibles costes en que la empresa incurrirá para cada una de las opciones y se elegirá la decisión menos cara. Backhauls: Estos hacen referencia al retorno de mercancías, lo cual supone que los clientes podrán demandar la entrega o la recogida de mercancías (Toth y Vigo, 2000). En este problema, la capacidad de los vehículos se convierte en un factor de extrema importancia. La Interstate Commerce Commission estimó que, gracias al backhauling, en Estados Unidos el ahorro dentro de la industria de comestibles había alcanzado los 160 millones de dólares (Golden et al., 1985). En este proyecto, los clientes podrán solicitar la recogida o la entrega de mercancías, pero nunca las dos de forma simultánea. Además, de forma obligatoria, se realizarán primero las entregas de los materiales para dar paso después a las recogidas. La razón de trabajar de esta manera es que, de lo contrario, a menudo sería necesario reacondicionar los materiales dentro de la unidad móvil, lo cual podría ser contraproducente. En este caso, el retorno de mercancías se produce cuando algún cliente no queda satisfecho con el pedido recibido y decide devolverlo a la empresa 1012


Ventanas de tiempo: Esta característica permite que cada cliente tenga una ventana temporal asociada . Este rango temporal posee un límite inferior y un límite superior que las unidades móviles tienen que respetar, es decir, que tienen que atender la demanda del cliente dentro de esa ventana. De esta forma, una ruta no será factible si un vehículo llega a un cliente después del límite superior del intervalo. Este problema ha sido ampliamente estudiado a lo largo de la historia (Condeau et al., 1999). Una de las razones por las que ha suscitado tanto interés ha sido su doble naturaleza, ya que puede considerarse como un problema de dos fases, una fase referente a la planificación de cargas y otra relativa a la programación de rutas. Otra razón aparte es la fácil adaptación al mundo real, ya que en la gran mayoría de las empresas los clientes presentan fuertes restricciones temporales que han de ser cumplidas.

5.2 Función Objetivo Teniendo en cuenta las características del problema mencionadas en el apartado anterior, los clientes pueden demandar la entrega o la recogida de mercancías, dentro de unas ventanas temporales. Aparte de esto, el problema cuenta con el dinamismo que ofrece el tratamiento de eventos imprevistos. La función objetivo a minimizar que se ha planteado para este D-VRPBTW (Dynamic Vehicle Routing Problem with Backhauls and Time Windows) es la siguiente:

Tabla 2 Términos de la función objetivo Coste de utilización por vehículo: Por cada vehículo que se haya utilizado se suma a la función su coste fijo. La variable es el coste fijo de cada vehículo, los cuales vienen agrupados en es una variable binaria que indica si el vehículo ha pasado por el arco Todos los nodos vienen agrupados en Coste de distancia recorrida: El coste es igual a la distancia total recorrida por cada una de las rutas multiplicado por el coste variable del vehículo. La variable indica el coste variable de un vehiculo mientras que es la distancia que hay entre los clientes y . Penalización por desocupación: Por cada vehículo se examinará la carga que lleva y se añadirá cierta penalización en caso de que esté poco ocupado. Esta penalización se aplicará a los vehículos que vayan cargados por debajo del 75% de su capacidad y aumentará a medida que la desocupación crezca.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 2 (continued) Términos de la función objetivo Penalización por cliente no servido: En caso de que debido a alguna incidencia algún cliente quede desabastecido, se impondrá una penalización a la función objetivo, la cual variará en función de la importancia del cliente y de la cantidad de mercancía que demande entregar o devolver. Coste de exceso de tiempo: Este coste se produce si la duración de la ruta supera las horas totales de trabajo que puede realizar el conductor. Para ello, se multiplica el exceso de horas por el coste de cada hora extra.

5.3 Técnicas de Resolución Propuestas Para el tratamiento del problema se ha propuesto la utilización de dos diferentes meta-heurísticas, que corresponden con algunas de las más utilizadas para problemas de optimización combinatoria a lo largo de la historia. En concreto, se trata de la búsqueda tabú (Basu y Ghosh, 2008) y el algoritmo genético (Holland, 1975).

6 Conclusiones La sincronización de la información entre los distintos eslabones que constituyen la cadena de suministro y su reacción ante posibles eventos imprevistos resulta una potente ayuda para que las empresas puedan ser más competitivas. En este artículo, se ha propuesto un sistema de planificación de producción y distribución de forma integrada. Este sistema trata de proporcionar soluciones para gestionar los eventos imprevistos aportando beneficios a la cadena de suministro gracias a la identificación de la información que debe ser intercambiada entre los diferentes nodos y al desarrollo de metodologías para la planificación de la producción y la distribución de manera coordinada.

7 Referencias Basu S, Ghosh D (2008) A review of the tabu search literature on traveling salesman problem. IIMA Working Papers. Indian Institute of Management Ahmedabad. 1-16.2008. Bilgen B, Günther HO (2010) Integrated production and distribution planning in the fast moving consumer goods industry: a block planning application, OR Spectrum, 2010. Flexible Automation and Intelligent Manufacturing, FAIM2013

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Condeau F, Desaulniers G, Desrosiers J, Solomon M, Soumis F (1999) The VRP with time windows. Technical Report Cahiers du GERAD G-99-13, École des Hautes Études Commerciales de Montréal. Golden BL, Baker E, Alfaro J, Schaffer J (1985) The vehicle routing problem with backhauling: two approaches. In R. Hammesfahr, Proceedings of the XXI Annual Meeting of S.F. TIMS, Myrtle Beach, SC. 90-92. Holland JH (1975) Adaptation in natural and artificial systems: an introductory analiysis with applications to biology, control, and artificial intelligence. Oxford, England: University of Michigan Press. Park Y, Hong S (2009) Integrated production and distribution planning for single-period inventory products. International Journal of Computer, Integrated Manufacturing, Vol. 22, No. 5, 443–457. Pillac V, Gendreau M, Guéret C, Medaglia AL (2011) A review of Dynamic Vehicle Routing Problem. Industrial Engineering: 0-28. Safaei AS, Moattar Husseini SM, Farahani RZ, Jolai F, Ghodsypour SH (2010) Integrated multisite production-distribution chain by hybridmodeling. International Journal of Production Research, Vol.48, No. 14, 4043–4069, 2010. Toth P, Vigo D (2000) VRP with backhauls. Monographs on Discrete Mathematics and Applications. In Toth P. and Vigo D. The Vehicle Routing Problem. SIAM: 195-224. 2000.

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Técnicas de Predicción Cuantitativas Aplicadas a la Cadena de Suministro. Un Caso de Estudio Quantitative Models for Supply Chain Forecasting. A Case Study Trapero Arenas J.R 1, García Márquez F.P2 Abstract Demand forecasting is a complex topic due to different factors like promotions. Generally, promotions may be forecast by using an univariate statistical approach (system forecast) that is judgmentally adjusted by company experts. The present work reports an analysis of the managerial adjustments accuracy when promotions are taking place. Additionally, quantitative models will be assessed as an alternative to judgmental adjustments when referring to forecast promotions. The results show that judgmentally adjusted forecasts on promotion periods may enhance system forecasts, but not systematically and more importantly, multivariate models based on past promotions information might achieve lower forecasting errors than system and judgmentally adjusted forecasts.

Resumen Las ventas sujetas a promociones se pueden pronosticar mediante una técnica estadística univariante (predicción del sistema), que posteriormente se modifica de acuerdo a la opinión de los expertos de la compañía. Este trabajo tiene dos objetivos: en primer lugar, se pretende analizar la precisión de los expertos cuando predicen las ventas y en segundo lugar, se investigan modelos cuantitativos que puedan reducir o sustituir el ajuste realizado por los expertos. Los resultados muestran que bajo ciertas condiciones los expertos consiguen mejorar las predicciones automáticas del sistema. No obstante, la utilización de modelos

1Juan Ramón Trapero Arenas ( e-mail: [email protected]) Grupo INGENIUM. Dpto. de Administración de Empresas. Facultad de Ciencias y Tecnologías Químicas. Universidad de Castilla-La Mancha. 13071 Ciudad Real. 2Fausto Pedro García Márquez ( e-mail: [email protected]) Grupo INGENIUM. Dpto. de Administración de Empresas. ETSI Industriales. Universidad de Castilla-La Mancha. 13071 Ciudad Real.

* Los autores agradecen el apoyo proporcionado por la Unión Europea mediante el proyecto FP7-ENERGY-2012-2: 322430.

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cuantitativos estimados en base al histórico de promociones consigue mejorar tanto los resultados de los ajustes de los expertos como las predicciones del sistema.

Keywords: Forecasting, Transfer Functions, Judgmental Forecasting, Marketing, Promotions. Palabras Clave: Predicción, Funciones de Transferencia, Predicción experta, Marketing, Promociones.

1 Introducción La predicción de demanda es un tema clave a la hora de reducir los gastos de inventario, mejorar la satisfacción del cliente y optimizar las operaciones de distribución. Normalmente, la predicción de demanda utiliza un Sistema de Apoyo a la Predicción (SAP) (Fildes et al, 2009), que integra una técnica estadística univariante junto con los ajustes manuales de los expertos de la organización. En principio, la predicción finalmente utilizada por la compañía es el resultado de dos fuentes de información. Por un lado, el SAP proporciona un predicción de índole estadística que se le conoce como predicción del sistema. Por otro lado, se organizan varias reuniones entre los responsables de las predicciones y el personal de ventas, marketing y producción para incorporar aquella información que no está incluída en el modelo estadístico. Por tanto, la predicción del sistema se modifica de acuerdo con las decisiones del grupo para así obtener una predicción final. Un ejemplo de estas técnicas univariantes es la familia de métodos de suavizado exponencial (Gardner, 1985). Esta técnica es adecuada para compañías que necesitan predecir la demanda de cada producto de una forma automática. No en vano, estos métodos no son aptos para predecir las ventas cuando hay promociones y por tanto, se espera un aumento de las mismas. Para mejorar las predicciones, los expertos basados en sus experiencias y en el histórico de promociones anteriores modifican las predicciones automáticas proporcionadas por el SAP. Dada la relación entre estas modificaciones de los expertos y las promociones, el primer objetivo de este trabajo es analizar la precisión de dichas modificaciones cuando hay una campaña promocional. Este análisis es útil de cara a formar a los expertos para que mejores sus ajustes. Hay que destacar que en el presente caso de estudio, el software utilizado por esta compañía ofrece la posibilidad de modificar las previsiones automáticas pero no analiza la precisión de las mismas. El problema de predecir las ventas promocionales también se puede estudiar mediante el uso de modelos econométricos que utilizan la información almacenada acerca de las promociones anteriores para formular modelos causales 1017


en forma de regresión lineal múltiple. En este tipo de modelos las variables exógenas o independendientes suélen estar relacionadas con las características de la promoción (descuento del precio, posición en las estanterías, tipo de publicidad, etc.). En este sentido se han desarrollado varios tipos de software, por ejemplo TM

SCAN*PRO (Leeflang et al, 2002), PromoCast (Cooper et al, 1999) y CHAN4CAST (Divakar et al, 2005). Sin embargo, llama la atención que dichas metodologías no se hayan comparado con su competencia natural: las predicciones realizadas por los expertos. Esta pregunta es esencial para una compañía que se plantee invertir en uno de estos sistemas, es decir, lo primero que se preguntaría es si dichos programas son capaces de mejorar las predicciones que hacen sus expertos. Cabe destacar que los autores no han encontrado ninguna referencia donde se compare los modelos econométricos a las predicciones de los expertos en presencia de promociones. Por tanto, el segundo objetivo de este trabajo es desarrollar un modelo econométrico para determinar el grado en el que los modelos cuantitativos pueden mejorar las predicciones proporcionadas por los expertos. Se propone un modelo de predicción a nivel de SKU (Stock Keeping Unit) con las siguientes características: i) El número de variables independientes se reduce mediante el uso de Análisis de Componentes Principales. De esta forma también se evita un posible problema de multicolinealidad; ii) Para aquellos productos que no dispongan de suficientes observaciones sujetas a promociones, el modelo utiliza la información de otros productos (Pool regression) para realizar las estimaciones de los parámetros; iii) La dinámica de las promociones se modela mediante la introducción de retardos en las variables explicativas; iv) El término de error se modela mediante modelos ARIMA automáticamente identificados mediante la minimización del Criterio de Información de Schwartz. Para elaborar este trabajo se han recopilado datos muestreados semanalmente acerca de las ventas y promociones de una empresa perteneciente a la industria química localizada en el Reino Unido. Los resultados muestran que los expertos pueden llegar a mejorar las predicciones proporcionadas por el SAP, no obstante cuando los ajustes son relativamente grandes, dichos ajustes pueden ser contraproducentes. Además, se muestra que el modelo econométrico propuesto, basado en la identificación de patrones utilizando promociones anteriores, mejora las predicciones del SAP y de los expertos cuando hay alguna campaña promocional.

2 Análisis de la Precisión de los Expertos Los datos se han obtenido de una empresa fabricante de detergentes y otros productos de limpieza. Los datos están compuestos por: i) Ventas; ii) predicciones proporcionadas por el SAP una semana hacia delante, las cuales las llamaremos Predicciones del Sistema (SF); iii) predicciones proporcionadas por los expertos 1018


una semana hacia delante. Citaremos estas predicciones como Predicciones de los Expertos (FF). Los datos previamente descritos contienen 145 SKUs. En total, se dipone de unos 10,000 registros desde Octubre del 2008 hasta Junio del 2010. La literatura que estudia los ajustes de los expertos señala que dichos ajustes suelen estar sesgados. En (Trapero et al, 2010) se apunta al tamaño y signo de los ajustes como variables explicativas, de forma que pequeños ajustes se espera que sean menos efectivos y que los ajustes positivos, es decir aquellos que aumentan el valor de predicción proporcionado por el sistema, suelen ser menos precisos que los negativos. En esta sección, se lleva a cabo un análisis descriptivo de los datos para averiguar la precisión obtenida por el sistema de predicción (SF) o por los expertos (FF). Siguiendo las publicaciones hasta la fecha se investigará el efecto del tamaño y signo de los ajustes, pero además este trabajo añade como aspecto novedoso el análisis del efecto de las promociones. Dado que la base de datos analizada posee productos con diferentes propiedades estadísticas (media y varianza) es conveniente normalizar los datos. Para ello se ha elegido normalizar las variables con respecto a la desviación típica de las ventas. Se ha procedido de esta manera de acuerdo a publicaciones anteriores, (Fildes et al, 2009) y (Trapero et al, 2010). La normalización nos permite tratar a las observaciones como conjunto de datos de sección cruzada. Esto implica que se puede reordenar los datos en función del tamaño y del signo. Si definimos el error absoluto medio tal que: (1) Donde

representa el error normalizado en el tiempo t, tal que: (2)

Donde, es el valor real de ventas normalizado y es la predicción. N son las observaciones disponibles en total. La Fig 1 muestra el MAE ordenado de acuerdo al signo y al tamaño de los ajustes. Con respecto a los ajustes positivos (ajustes normalizados mayores que cero), los expertos (FF) consiguen errores de predicción menores cuando el tamaño del ajuste normalizado es inferior a 4 aproximadamente, para ajustes más grandes el SF funciona mejor.

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0.85

MAE

0.8

0.75 SF FF

0.7

0.65 -2

0

2 4 6 Ajustes normalizados

8

10

Fig. 1 MAE vs. ajustes normalizados

En relación a los ajustes negativos en la Fig. 1 se pueden extraer las siguientes conclusiones: i) el MAE es inferior al obtenido con los ajustes positivos; ii) el tamaño de los ajustes también es menor; y iii) FF obtiene menores errores de predicción que SF. Este mejor comportamiento del FF para ajustes positivos se debe a que los expertos conocen de antemano cuando va a haber una determinada promoción y por tanto elevan el valor proporcionado por el SF. Para analizar dicha hipótesis, la Fig. 2 representa los errores de predicción sólo cuando hay activa alguna promoción. En este gráfico se observa claramente como los expertos mejoran las predicciones del sistema cuando los ajustes son positivos, que son la mayoría cuando hay promociones. No obstante, si los ajustes normalizados son muy grandes, los expertos cometen errores mayores que el SF. Es importante destacar la importancia de este tipo de gráficos porque si no se hubiera analizado el tamaño del ajuste lo único que se observaría serían los valores promedios finales, cuya conclusión sería que el SF es más preciso que el FF y dicha conclusión es incompleta. 1.4 1.3 1.2

MAE

1.1 1 0.9 0.8 SF FF

0.7 0.6 0

2

4 6 Ajustes normalizados

8

Fig.2 MAE del SF y FF frente a los ajustes normalizados cuando hay algún tipo de promoción.

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El gráfico en la Fig. 3 muestra el MAE frente a los ajustes normalizados cuando no hay promociones. Se puede observar que los ajustes positivos no mejoran significativamente con respecto el SF. No obstante, hay que señalar la precisión alcanzada por los ajustes negativos que mejoran considerablemente a las predicciones del sistema (SF). Una posible explicación a esta notable mejoría es el hecho de que una vez acabada la promoción el SAP seguirá produciendo unas previsiones más altas de lo normal ya que sus modelos no incluyen información acerca de cuándo empieza o acaba una promoción. Este defecto del SAP es conocido por los expertos, los cuales reajustan a la baja esas previsiones.

3 Modelado de los Efectos de las Promociones sobre las Ventas En la sección anterior se mostró que los expertos pueden incorporar información en sus predicciones que el sistema no es capaz de procesar. Esta conclusión abre la puerta a la siguiente cuestión: ¿se basaron los expertos en los resultados de promociones anteriores para realizar los ajustes? En otras palabras, los expertos pudieron haber analizado los efectos que tuvieron promociones parecidas en el pasado e intentar proyectar esos patrones para las promociones futuras. En tal caso, modelos multivariantes como una regresión lineal múltiple es posible que mejoren los resultados obtenidos por los expertos ya que las mentes humanas son buenas para identificar patrones pero no lo son tanto para trabajar con grandes cantidades de información como la que manejamos en este caso de estudio. 0.8 0.78 0.76 0.74 0.72 0.7

SF FF

0.68 0.66 0.64 -2

0

2 4 Ajustes normalizados

6

8

Fig. 3 MAE del SF y FF frente a los ajustes normalizados cuando no hay promociones.

Además de las variables definidas en la sección anterior, se han incluido las siguientes variables que dan información particular sobre las promociones: i) Descuento; ii) Tipo de publicidad; iii) Lugar de exposición y iv) Categoría. 1021


Con el fin de comprobar si las técnicas cuantitativos pueden mejorar las predicciones de los expertos, se propone la siguiente Regresión Dinámica (RD):

(3) Donde las variables son los componentes principales que resumen la información sobre la promoción. N es el número de componentes principales que incluimos en el modelo. En general, una o dos componentes principales han sido suficiente para estimar los modelos. El efecto dinámico de las promociones se ha incluido en el modelo mediante la incorporación de diferentes retrasos en las variables originales utilizadas antes de realizar el análisis de componentes principales. Ft+1 son las predicciones de ventas un paso hacia delante que corresponden al SKU i. Para poder utilizar el modelo (3) es necesario conocer de antemano cuándo la empresa va a realizar las promociones. En nuestro caso de estudio las promociones son negociadas con antelación entre el fabricante y el distribuidor. En el caso que no haya suficientes promociones para el SKU sujeto a estudio, se utiliza la información sobre promociones procedentes de otros SKUs en la muestra. Por último el término de error , no se supone ruido blanco sino que se modela utilizando la metodología ARIMA, cuyos órdenes se identifican minimizando el Criterio de Información de Schwartz. Para analizar el modelo propuesto, vamos a reducir la muestra a aquellos SKUs con demanda continua, y que dispongan de 20 semanas de observaciones con al menos una promoción en la muestra. En total, de los 145 SKUs pasamos a 60 SKUs con un tamaño cada uno que varía entre 53 y 148 observaciones, resultando una muestra de 7,790 casos. El modelo descrito en (3) se va a comparar con otros modelos de predicción típicamente utilizados en este contexto como son el suavizado exponencial simple (SES), el método ingenuo (Naïve) y el last like promotion (LL). Este último se aplica comúnmente cuando hay que realizar previsiones de demanda sujetas a promociones. Generalmente consiste en aumentar las previsiones obtenidas por un suavizado exponencial simple de acuerdo al último aumento que se obtuvo en la última promoción con características similares. El ejercicio de predicción propuesto va a consistir en un experimento rolling origin, donde una vez que la predicción se ha realizado, el origen se mueve una semana hacia delante hasta completar la muestra de validación. En este caso la muestra de validación se fija en las últimas 30 semanas, de forma que el 21% de las promociones se encuentran en dicha muestra de validación.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 1 MAE calculado en la muestra de validación por las diferentes técnicas consideradas. SF

FF

Naïve

SES

LL

RD

1.069

1.327

1.092

0.904

1.122

0.868

En la Tabla 1 se muestra el error de predicción (MAE) obtenido por cada uno de los métodos de predicción considerados en la muestra de validación. En dicha tabla se puede observar como la regresión dinámica propuesta (RD) consigue obtener los menores errores de predicción en ventas en comparación con el resto de técnicas e incluse consigue una reducción del 19% con respecto a la precisión de los expertos. El MAE se ha calculado solamente sobre las ventas en las que hay algún tipo de promoción activada. Estos resultados sugieren que los ajustes que los expertos realizan para modelar las promociones pueden ser sustituidos por modelos multivariantes estadísticos, los cuales consiguen mejorar las predicciones y a su vez reducir la carga de trabajo de los expertos.

4 Conclusiones Los modificación de las predicciones por parte de los expertos es un método commúnmente empleado para modelar las promociones. Sin embargo, los autores no han encontrado casos de estudio en la literatura que analice la eficiencia de dichas modificaciones. Este trabajo investiga la precisión alcanzada por los expertos para predecir la demanda de los clientes cuando hay activa una campaña promocional. El primer resultado encontrado muestra que efectivamente los expertos pueden mejorar las predicciones pero no sistemáticamente, ya que si los ajustes son relativamente grandes, estos ajustes pueden no ser aconsejables. En base a que los expertos ajustan las predicciones analizando los resultados obtenidos en promociones anteriores, este trabajo plantea otra alternativa que utiliza un modelo cuantitativo para predecir las ventas promocionales. Los resultados indican que este modelo mejora en promedio las predicciones realizadas tanto por el sistema como por los expertos para nuestro caso de estudio.

5 Referencias Cooper LG, Baron P, Levy W et al (1999) PROMOCAST Trademark: A New Forecasting Method for Promotion Planning. Marketing Science, 18(3):301. Divakar S, Rachford BT, Shankar V (2005) CHAN4CAST: A multichannel, multiregion sales forecasting model and decision suppor system for consumer packaged goods. Marketing Science, 24:334-350.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Fildes R, Goodwin P, Lawrence M et al (2009). Effective forecasting and jugdmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting, 25:3-23. Gardner ES (1985) Exponential smooothing: The state of the art. Journal of Forecasting, 4:1-28. Leeflang PSH, van Heerde HJ, Wittink D (2002) How promotions work: SCAN*PRO-Based evolutionay Model Building. Schmalenbach Business Review, 54:198-220. Pedregal DJ, Contreras J, Sanchez A (2010) Handbook of Networks in Power Systems, chapter ECOTOOL: A general MATLAB forecasting toolbox with applications to electricity markets, pages 69-104. Springer Verlag. Trapero JR, Fildes R, Davydenko A (2010) Nonlinear identification of judgmental forecasts effects at SKU level. Journal of Forecasting, 30:490-508.

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Decisiones en el Diseño de Redes de Logística Inversa: Propuesta de un Modelo de Decisión. Decisions on the Design of Reverse Logistics Networks: a Proposal for a Decision Model. Ribas I1, Rubio S2 Abstract A configuration of reverse logistics network for end-of-use products is considered in order to establish a decision model that can help to design the network according to the characteristics of the product to be recovered. The proposed model comes from an extensive review of the literature, which proposes to consider the combination of product residual value and marginal value time of the product with the type of recovery option to design the structure.

Resumen Se considera el problema del diseño de las redes de suministro inversa para la recuperación de productos usados, con el objetivo de establecer un modelo que permita configurar la red en función las características del producto a recuperar. El modelo propuesto es el resultado de una extensa revisión de la literatura y propone el diseño de la red en función del valor residual del producto, de su “depreciación” durante el periodo de recuperación y del proceso de recuperación económica requerida (reutilización, reciclaje, refabricación).

1Imma Ribas Vila ( e-mail: [email protected]) Dpto. de Organización de Empresas. Escola Tècnica Superior d’Enginyers Industrials de Barcelona. Universitat Politècnica de Catalunya. BarcelonaTech. Avda. Diagonal, 647, ed. H, P.7 08028 Barcelona. 2

Sergio Rubio Lacoba ( e-mail: [email protected]) Escuela de Ingenierías Industriales. Universidad de Extremadura. Avda. de Elvas S/N, 06006 Badajoz. * Esta investigación se ha desarrollado con la financiación del proyecto PLACYRES DPI201015614 financiado por el Ministerio de Economía y Competitividad. S. Rubio agradece la financiación de la Consejería de Empleo, Empresa e Innovación del Gobierno de Extremadura a través de la ayuda ref. GR10070

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Keywords: Reverse Logistics, Product Recovery Value, Marginal Value Time, EOL Product. Palabras clave: Logística Inversa, Valor de Recuperación, Tiempo de Recuperación, Producto Fuera de Uso.

1 Introducción El objetivo de este trabajo es proponer un sistema de apoyo a la decisión que permita identificar el tipo de sistema o red que resultaría más adecuado para la recuperación económica del valor de los productos fuera de uso (End-Of-Life products, EOL) en el ámbito de la gestión de la cadena de suministro. Con este propósito, se ha realizado una amplia revisión de la literatura sobre diseño de redes inversas de suministro (redes de logística inversa) intentando encontrar elementos comunes que permitan identificar características esenciales de estas redes relativas al proceso de toma de decisiones sobre su diseño e implantación. No se trata de una cuestión sencilla ya que además de la abundante cantidad de aportaciones a la literatura sobre el diseño de redes de logística inversa o redes de distribución inversa (reverse logistics network, RLN), se une la propia complejidad inherente al proceso de diseño de las mismas debido, entre otras cuestiones, a que “no todas las redes de logística inversa son idénticas, ni tienen por qué serlo”(Daniel, Guide & Van Wassenhove 2002). Parece existir cierto consenso entre la comunidad académica acerca de la relevancia que tiene el diseño de redes de logística inversa en el ámbito de la gestión de la cadena de suministro, y así, por ejemplo, (Fleischmann et al. 2001) afirman que “en las cadenas de suministro tradicionales, el diseño de la red logística tiene el reconocimiento de aspecto estratégico de máxima importancia, y de manera análoga, desarrollar una adecuada red logística tienen un impacto fundamental sobre la viabilidad económica de la cadena de suministro inversa”. Por su parte, (Akçalı, Çetinkaya & Üster 2009) también destacan la relevancia del tema, subrayando que dos de los retos más interesantes y relevantes en el diseño estratégico de las redes de logística inversa son “(i) ¿Cómo diseñar una red de logística inversa partiendo de cero? y (ii) ¿Cómo diseñar una red de logística inversa cuando ya existe una red logística tradicional (forward)?”. Se trata, por tanto, de una cuestión relevante tanto en el ámbito académico, como desde el punto de vista de las empresas interesadas en promover y desarrollar sistemas para la recuperación de productos fuera de uso, para las cuales las decisiones sobre el diseño de estos sistemas adquieren un carácter estratégico. En este trabajo tratamos de describir los aspectos más relevantes a considerar en el diseño de redes de logística inversa, poniendo de relieve las decisiones a tomar. Para ello, a continuación se revisan algunas de las principales aportaciones académicas realizadas en los últimos años y que sirven de referencia para este tra1026


bajo. En el apartado 3 se describen las decisiones que caracterizan los sistemas de logística inversa, sobre las que realizamos nuestra propuesta de modelo de decisión para su diseño. Seguidamente, en el apartado 4, presentamos la estructura propuesta y finalizamos este trabajo con las conclusiones más relevantes.

2 Revisión de la Literatura Nuestro interés al revisar los trabajos previos sobre el diseño de RLN persigue caracterizar, de una manera genérica, los elementos básicos de dichas redes, más allá de examinar qué técnicas de análisis o metodologías se han empleado para resolver una determinada propuesta de RLN específica para una empresa, mercado o producto en particular, las cuales no siempre resultan generalizables a otros entornos. Trabajos como los de (Thierry et al. 1995), (Fleischmann et al. 2000), (Fleischmann et al. 2001) y (Flapper, Van Nunen & Van Wassenhove 2005) han contribuido de manera significativa en este campo, proporcionando una descripción básica de redes de logística inversa, identificando aspectos comunes entre las mismas, y señalando elementos críticos en el diseño e implantación de estos sistemas. Así (Thierry et al. 1995) clasifican las RLN en función de la opción de recuperación que se le da al producto fuera de uso: 1) uso directo y reventa, 2) reparación, refabricación, restauración, canibalización y reciclaje, y 3) eliminación de residuos. (Fleischmann et al. 2000) emplean una clasificación de acuerdo a las características observadas en distintos casos de estudio, clasificando las RLN en 1) redes para la reutilización, 2) redes para la refabricación, y 3) redes para el reciclaje. Por su parte, (Flapper, Van Nunen & Van Wassenhove 2005), también describen distintas redes de logística inversa a través de business cases, en los que además se aportan otros elementos referidos a aspectos organizativos, medioambientales, técnicos y económicos. En el ámbito concreto de la refabricación, (Savaskan, Bhattacharya & Wassenhove 2004) estudian cuatro configuraciones para redes inversas de suministro, clasificándolas en función de su grado de centralización, y en las que el objetivo es detectar ineficiencias en el proceso de toma de decisiones descentralizadas en la red de suministro. Se entiende por redes descentralizadas las que dedican varias ubicaciones (nodos de la red) a una misma actividad, frente a las redes centralizadas en las que una misma actividad suele desarrollarse en una única instalación. Todos estos trabajos, sin embargo, aun siendo fundamentales para el estudio del diseño de las RLN, se centran principalmente en la descripción de las características de dichas redes pero no proponen métodos o procedimientos para el diseño de tales redes. Es en este ámbito en el que se desarrolla nuestro trabajo y donde cabe señalar alguna contribución como (Barker, Zabinski 2011) quienes

1027


proponen un modelo AHP de toma de decisiones para el diseño de redes de logística inversa a partir del análisis de diferentes casos de estudio. En esta comunicación se propone un sistema que permita identificar el tipo de sistema o red que resultaría más adecuado para la recuperación económica del valor de los productos fuera de uso (EOL) y tomas las decisiones oportunas sobre el diseño de la red.

3 Decisiones en el Diseño de Redes de Logística Inversa Probablemente, la primera cuestión que cabe plantearse a la hora de afrontar el diseño de una red de logística inversa sea la decisión de integrar esta red con la red de suministro existente constituyendo así una red de suministro cerrada (ClosedLoop Supply Chain, CLSC), o diseñar una red independiente para la recuperación de los productos fuera de uso. (Flapper, Van Nunen & Van Wassenhove 2005) afirman que “integrar los flujos directos e inversos de la cadena de suministro puede tener consecuencias para la estructura interna de la organización, en cuanto a su diseño, ventas, compras, sistema de producción, distribución, servicios postventa, contabilidad, etc., así como en sus relaciones con proveedores, distribuidores y clientes”. Igualmente, (Akçalı, Çetinkaya & Üster 2009) analizan también estas dos posibilidades en el diseño de redes para la recuperación de productos, señalando que “el diseño de RLN se relaciona con el establecimiento de una infraestructura para gestionar únicamente el canal inverso, mientras que el diseño de la CLSC considera la transformación de la cadena de suministro para la gestión coordinada de los canales directo e inverso”. Otros trabajos (por ejemplo, (Fleischmann et al. 1997); (Verter, Aras 2008)) también identifican como un aspecto básico del diseño de RLN la decisión relativa a si la red debe ser una estructura independiente de la red existente (forward) o bien debe integrarse en ella, por lo que podemos considerar este aspecto como un elemento crucial en el proceso de decisión. En cualquier caso, tanto una RLN como una CLSC se configuran en torno a tres actividades críticas, a saber: 1) la recogida de EOL, 2) inspección y clasificación, 3) recuperación del valor (refabricación, reutilización, reciclaje). Trabajos como el de (Aras, Boyaci & Verter 2010) señalan tres decisiones estratégicas que deberán tomarse en el diseño de RLN relativas a su estructura (integrada o independiente), la estrategia de recogida más adecuada (pick-up, drop-off), y el establecimiento de incentivos financieros o subsidios para la recogida de los productos EOL. En este sentido, (Boyacı et al. 2008) señalan que el establecimiento de incentivos para incrementar el acopio de EOL se relaciona directamente con el sistema empleado para su recogida, de manera que un régimen de incentivos para los clientes implicaría, en una estrategia drop-off, una red más centralizada, con pocos centros de recogida que abarquen zonas más amplias de clientes, ya que estos es1028


tarán dispuestos a desplazarse a una distancia mayor para retornar el EOL; por su parte, bajo una estrategia pick-up, mayores incentivos a los clientes para el retorno de EOL requieren el establecimiento de un mayor número de centros de recogida, con un área de clientes menor, con el fin de minimizar el coste de transporte; es decir, una estructura más descentralizada. Como ya hemos apuntado, y como también remarcan (Alumur et al. 2012) “la configuración de una RLN es un problema complejo que requiere la determinación de la localización óptima y la capacidad de centros de recogida, centros de inspección, instalaciones de refabricación, y/o plantas de reciclaje”. En (Aras, Boyaci & Verter 2010) se pueden observar múltiples configuraciones de redes de logística inversa, aunque la naturaleza del producto fuera de uso y el tipo de recuperación que se le aplica tienen una relación muy importante con el diseño de la red, y ese será el punto de partida para desarrollar nuestra propuesta.

4 Una Propuesta de Modelo de Decisión para el Diseño de Redes de Logística Inversa Como hemos venido señalando, el diseño de sistemas de logística inversa guarda una relación muy estrecha con el tipo de producto retornado y con el proceso a través del cual se recuperará el valor que dicho producto aún incorpora tras finalizar su vida útil o cuando éste deja de satisfacer las necesidades del consumidor. Para el desarrollo de nuestra propuesta, consideramos muy relevante el trabajo de (Blackburn et al. 2004) en el que se propone un modelo de diseño de RLN basado en el concepto de “Marginal Value of Time, MVT”, que los autores identifican con la existencia de un valor del producto retornado asociado al tiempo requerido para recuperar su valor. Así, por ejemplo, productos electrónicos como los ordenadores tienen un alto MVT porque su valor económico es muy sensible al tiempo que se tarda en recuperarlo (cuanto mayor es el tiempo de recuperación, menor valor tendrá) mientras que productos como las cámaras fotográficas desechables o las “máquinas-herramienta” tienen un MVT inferior ya que el paso del tiempo no afecta significativamente a su valor de recuperación. Esta distinción entre productos con alto y bajo MVT lo relacionan con el esquema de diseño de redes de suministro propuesto por (Fisher 1997) en el que se identifican redes “Responsive” frente a redes “Efficient”. En el caso de RLN, las redes responsive son las que permitirían una recuperación del valor del producto rápida mientras que las redes efficient serían las que se diseñarían en función de criterios de coste, lo que a la práctica lleva a redes más centralizadas en las que el plazo de recuperación del producto es mucho más largo. Estos autores emplean esta clasificación para considerar que, en el caso de productos con un alto MVT, la red más apropiada sería una red “responsive” de diseño descentralizado, mientras que para productos con bajo MVT la red inversa tendría un enfoque “efficient” de carácter centralizado. 1029


Recientemente, (Gobbi 2011) ha analizado a través de distintos casos de estudio el diseño de la red de logística inversa, utilizando para ello los conceptos de MVT y de PRV (Product Residual Value), y el esquema de redes efficient vs responsive, concluyendo que las redes efficient son adecuadas para productos con bajo PRV, mientras que las efficient lo son para productos con bajo PRV. Sin embargo, este trabajo no permite concluir acerca de las ventajas de la centralización de operaciones en este tipo de redes, independientemente del nivel de PRV y de MVT del producto en cuestión. Integrando el esquema de (Fisher 1997) con los trabajos de (Fleischmann et al. 2000) , (Blackburn et al. 2004, Fleischmann et al. 2000) y (Gobbi 2011) podríamos señalar elementos básicos en el proceso de toma de decisiones relativas al diseño de RLN, de acuerdo a tres niveles. En el primer nivel se clasifica el producto fuera de uso de acuerdo con su PRV (alto o bajo), mientras que en el segundo nivel se considera su tiempo de recuperación (MVT). Las diferentes configuraciones de estos dos niveles (PRV-MVT) se relacionan con el tipo de red de suministro (responsive o efficient). Así, productos con altos niveles de PRV y MVT suelen requerir una configuración de red que permita recuperar el producto en un plazo de tiempo corto (responsive), mientras que si el valor del producto no es tan sensible al tiempo (bajo MVT), la agilidad de la red no será una característica tan crítica (efficient). El tercer nivel clasifica el producto en función de la opción de recuperación económica que se le aplicará al producto (reutilización, refabricación, reciclaje), de acuerdo con la tipología propuesta por (Fleischmann et al. 2000). Un producto con altos niveles de PRV y MVT suelen estar sujetos a operaciones de refabricación para la recuperación de su valor; en cambio, las operaciones de reutilización y reciclaje para la recuperación económica de los productos fuera de uso suelen corresponder con productos con bajo PRV, independientemente de su nivel de MVT (Tabla 1). Tabla 1 Características de las RLN Valor PRV

Alto

Valor MVT

Alto

Bajo

Bajo Alto / Bajo

Tipo de red

Responsive

Efficient

Efficient

Estructura de red

Descentralizada

Centralizada

Centralizada

recogida

Pick-up

Drop-off

Drop-off

Claificación- inspección

Centralizada

Centralizada

Centralizada

Proceso

Refabricación

Refabricación

Reuso – Reciclaje

Objetivo de la red

Economic0

Economic0

Legislación

Ejemplos

Laptops

Electrodomésticos

Papel, cristal,

Los productos con bajo valor residual no quedan diferenciados por su MTV, ya que si el producto tiene bajo PRV no parece tener demasiada importancia lo rápido o lento que se deprecie, siendo su característica esencial la de responder a un 1030


modelo efficient, de estructura centralizada, cuyo objetivo es alcanzar economías de escala con el fin de minimizar costes.

5 Conclusiones El objetivo principal de esta comunicación ha sido describir las características básicas de las redes de logística inversa para la recuperación de productos fuera de uso, con el propósito de mejorar el proceso de toma de decisiones en cuanto al diseño de las mismas, ya que éste, el diseño de las RLN, se viene señalando en la literatura como una cuestión estratégica en los procesos de recuperación de productos fuera de uso, y por tanto un aspecto clave para en el éxito de las mismos. Con este fin hemos revisado las principales aportaciones en este sentido, identificando un conjunto de trabajos que aunque necesarios para conocer y delimitar el alcance del problema, en general, no dejan de ser trabajos que fundamentalmente describen las características de la red pero que no permiten tomar decisiones acerca de cómo diseñar e implantar este tipo de redes de distribución inversa. Este trabajo se presenta como trabajo en curso, que se encuadra dentro de un proyecto de mayor dimensión sobre el diseño de redes de suministro, por lo que algunas cuestiones no se han considerado en esta ponencia y otras se encuentran en desarrollo en estos momentos. No obstante, de la revisión bibliográfica realizada hemos podido obtener varias ideas relativas al diseño de las RLN que nos permiten señalar las siguientes conclusiones al respecto:  Probablemente, la primera decisión relativa al diseño de RLN hace referencia a su integración o no dentro de la cadena de suministro ya existente (forward).  Las decisiones relativas al diseño de la RLN pueden analizarse a través de conceptos como el PRV y el MTV, y en todo caso, la opción de recuperación del valor económico del producto fuera de uso suele quedar definida por la combinación de estos valores. De esta forma, podemos considerar tres niveles (PRV, MVT, Opción 3-R) que describen la estructura de la red y las decisiones a tomar en su diseño.  La recuperación de productos con altos niveles de PRV y MVT suelen requerir redes responsive de carácter descentralizado, en las que prima la rapidez en la recuperación del valor que aún incorpora el EOL; mientras que los productos con bajo PRV suelen responder a configuraciones centralizadas de tipo efficient, con el objetivo de minimizar los costes de recogida, maximizando las cantidad de producto retornado.  Las decisiones relativas a las actividades básicas en las RLN comprenden la recogida de productos fuera de uso, su inspección y clasificación y las operaciones de recuperación del valor económico de estos productos (refabricación, reutilización, reciclaje). Así, en las redes para productos con altos PRV y MVT las operaciones de recogida suelen ser realizadas a través de sistemas pick-up, 1031


su clasificación se realiza de manera centralizada, recuperando su valor a través de operaciones de refabricación. Por su parte, las redes para recuperar productos con bajo PRV suelen utilizar sistemas drop-off para su recogida, los cuales se clasifican de manera centralizada para su posterior reciclaje o reutilización. Naturalmente, quedan cuestiones que aún deben desarrollarse para completar el modelo de decisión que debe incorporar aspectos relativos a las tareas que apoyan el desarrollo de las actividades básicas de estas RLN como, por ejemplo, decisiones relativas al transporte de los productos a través de la red, la eliminación de productos no recuperables, así como cuestiones organizativas, de relaciones con los distintos agentes de la cadena, medioambientales, comerciales, etc, que se iremos incluyendo en posteriores trabajos.

6 Referencias Akçalı, E., Çetinkaya, S. & Üster, H. 2009, "Network Design for Reverse and Closed-Loop Supply Chains:An Annotated Bibliography of Models and Solution Approaches", Networks, vol. 53, no. 3, pp. 231-248. Alumur, S.A., Nickel, S., Saldanha-da-Gama, F. & Verter, V. 2012, "Multi-period reverse logistics network design", European Journal of Operational Research, vol. 220, pp. 67-78. Aras, N., Boyaci, T. & Verter, V. 2010, "Designing the Reverse Logistics Network" in ClosedLoop Supply Chain: New Developments to Improve the Sustainability of Business Practices, eds. M.E. Ferguson & G.C. Souza, Auerbach Publications CRC Press, , pp. 67-97. Barker, T. & Zabinski, Z.B. 2011, "A multicriteria decision making model for reverse logistics using analytical
hierarchy process", Omega, vol. 39, pp. 558-573. Blackburn, J.D., Guide, J.V.D.R., Souza, G.C. & Van Wassenhove, L.N. 2004, "Reverse Supply Chains for Commercial Returns", . California Management Review, vol. 46, no. 2, pp. 6-22. Boyacı, T., Verter, V., Toyasaki, F. & Wojanowski, R. 2008, "Collection System Design, Strategy Choice and Financial Incentives for Product Recovery", working paper. Desautels Faculty of Management, McGill University, Montreal, Canada., . Daniel, V., Guide, J. & Van Wassenhove, L.N. 2002, "The reverse supply chain", Harvard Business Review, vol. 80, no. 2, pp. 25-26. Fisher, M.L. 1997, "What is the Right Supply Chain for your Product?", Harvard Business Review, vol. 75, pp. 105-116. Flapper, S.D.P., Van Nunen, J.A.E.E. & Van Wassenhove, L.N. (eds) 2005, Managing ClosedLoop Supply Chains, Springer Berlin-Heidelberg, Germany. Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J.M. & Wassenhohve, L.N. 2001, "The impact of product recovery on logidstics network design", . Production and operations Management, vol. 10, no. 2, pp. 156-176. Fleischmann, M., Bloemhof-Ruwaard, J.M., Dekker, R., van der Laan, E., van Nunen, J.A.E.E. & Van Wassenhove, L.N. 1997, "Quantitative Models for Reverse Logistics: A Review", European Journla of Operational Research, vol. 103, pp. 1-17. Fleischmann, M., Krikke, H.R., Dekker, R. & Flapper, S.D.P. 2000, "A characterization of logistics network for product recovery", Omega, vol. 28, pp. 653-666.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Gobbi, C. 2011, "Designing the Reverse Supply Chain: The impact of the product residual value", . International Journal of Physical Distribution & Logistics Management, vol. 41, no. 8, pp. 768-796. Savaskan, R.C., Bhattacharya, S. & Wassenhove, L.N. 2004, "Closed-Loop Supply Models with Product Remanufacturing", Management Science, vol. 50, no. 2, pp. 239-252. Thierry, M., Salomon, M., Van Nunen, J. & Van Wassenhove, L.N. 1995, "Strategic Issues in Product Recovery Management", California Management review, vol. 37, no. 2, pp. 114-135. Verter, V. & Aras, N. 2008, "Designing Distribution Systems with Reverse Flows", Desautels Faculty of Management, McGill University, Montreal, Canadar, vol. working pape.

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La Mejora Dinámica del Rutado de Vehículos: Eventos de Reoptimización The Dynamic Improvement of Vehicle Routing: Reoptimization Events Escudero A1, Muñuzuri J, Cortés P, Aparicio P Abstract The static environments of optimization are not efficient when there is Uncertainty. The vehicle routing is a common case of it. For example, there usually is uncertainty in the transit time due to the congestion, traffic jam, etc. Dynamic optimization has been more efficient in these environments. To determinate when a reoptimization have to be run is fundamental.

Resumen Los entornos estáticos de optimización no son todo lo eficientes que se esperaría en situaciones donde existe incertidumbre. El rutado de vehículos es una caso común donde existe incertidumbre, por ejemplo en el tiempo de tránsito, motivado principalmente por los diferentes niveles de congestión existentes. La reoptimización dinámica se ha mostrado más eficaz en este tipo de sistemas. Determinar en que momentos realizar la reoptimización es fundamental en la eficiencia de este tipo de sistemas.

Keywords: Uncertainty, VRP, Drayage, Dynamism Palabras clave: Incertidumbre, VRP, Acarreo, Dinamismo

1 Introducción En trabajos previos (Escudero et al. 2011a, Escudero et al. 2011b, Escudero et al. 2013) se demostró que las metodologías tradicionales de optimización de rutas de

1Alejandro Escudero Santana ( e-mail: [email protected]) Grupo Ingeniería de Organización. Dpto. de Organización Industrial y Gestión de Empresas II. Escuela Técnica Superior de Ingeniería. Universidad de Sevilla. Camino de los Descubrimientos S/N, 41092 Sevilla.

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vehículos no son todo lo eficientes que se desearía cuando se desarrollan en entornos reales, donde diferentes elementos de incertidumbre aparecen. La forma clásica de optimizar estos procesos se ha desarrollado desde una perspectiva estática; al principio de la jornada, el decisor presenta las rutas que los diferentes vehículos deberán desarrollar durante la jornada. Si se presenta algún tipo de incidente en el tráfico de los vehículos puede que las rutas planteadas al principio de la jornada no puedan llevarse a cabo según las restricciones temporales comprometidas. Múltiples estudios ponen de manifiesto el valor de la información a la hora de elegir rutas por los usuarios (Levinson, 2003; Chorus et al., 2006). Sin embargo esa obviedad no había sido llevada a la forma de optimización de las rutas. Adbdel-Aty et al. (1997) señalan que esta información puede ahorrar tiempo, estudiar la forma y el momento en el que esta información es suministrada es importante para que esta sea realmente útil (Koutsopoulos y Xu, 1993). Este trabajo propone la optimización de la jornada, del problema del acarreo terrestre (Escudero et al. 2012), desde una perspectiva dinámica, de manera que la solución va evolucionando a lo largo del día, adaptándose a las circunstancias que vayan aconteciendo. Esto proceso se realiza ayudado por el conocimiento en tiempo real de la posición de los vehículos. Numerosos estudios sobre problemas de rutado dinámico pueden encontrarse en la literatura (Psaraftis, 1995; Pillac et al., 2013), aunque estos suelen estar centrados en la incertidumbre que presentan que un determinado cliente requiera el servicio, y no en la incertidumbre en el tiempo de tránsito. El siguiente epígrafe, sección 2, comienza presentando la estructura del sistema planteado. Seguidamente, sección 3, se enumeran posibles eventos que pueden llevar al lanzamiento de una reoptimización. Por último, sección 4, se mostrarán algunos resultados alcanzados y se enunciaran una serie de conclusiones, sección 5.

2 El Sistema Dinámico La arquitectura del sistema dinámico diseñado se muestra de modo esquemático en la Figura 1. Este sistema recibiría diversos tipos de informaciones, que serían posteriormente utilizadas como datos para la ejecución del algoritmo dinámico de asignación (Escudero et al. 2011a, Escudero et al. 2011b, Escudero et al. 2013):  Solicitudes de tareas, que podrían ser directamente incorporadas al sistema por parte de los clientes del mismo.  Información sobre la posición de los vehículos en el viario. Esta posición puede ser determinada según diferentes tecnologías existentes. En la Figura 1 se ejemplifica a través de dos posibles sistemas: GPS o Galileo. 1035


 Información sobre la compleción de tareas, proporcionada por los conductores de los vehículos al sistema a través del correspondiente interfaz de comunicaciones.  Por último, y de manera opcional, el sistema podría contar con información actualizada sobre el estado del viario (fundamentalmente el grado de congestión y la velocidad media en los diferentes tramos del mismo), en caso de que esta información estuviera disponible. De esta manera, el sistema, además de reorganizar las rutas asociadas a las tareas basándose en estimaciones de las velocidades medias en el viario, podría recalcular las rutas atendiendo a valores mucho más cercanos a la realidad.

Fig. 1 Sistema global de optimización dinámica

La metodología dinámica que se plantea va mejorando la solución iterativamente. Al principio de la jornada, se lanza una optimización inicial al problema, que permitiría poseer una solución de partida. Sin embargo, dado que el tiempo de tránsito es incierto, se hace imposible conocer a priori el tiempo exacto requerido para completar una tarea; y por lo tanto, aparecen desajustes entre la realidad y lo esperado según la solución planteada al principio. 1036


Para corregir dichos desajustes se ha planteado una metodología dinámica de optimización. En ciertos momentos se lanzan reoptimizaciones en búsqueda de Cap´ıt ulo 6 Asignaci´ din´ a las circunstancias reales existentes, y que pueuna solución que se adapteonmejor 96 amica a t ravés del conocimient o en t iempo real de la den corregir los previsibles retrasos, o incluso adelantos, en la ejecución de las taposici´ reas. Esta reoptimización habrá tenido en cuenta las circunstancias reales on de la flotque a acontecen y sólo considerará las tareas pendientes de ejecutar. La nueva solución previsibles ret rasos, o incluso adelant os, en la ejecuci´ podrá cambiar la asignación de tareas a vehículos, teniendo en cuenta que los on de las t areas. Est a reopt imizavehículos que se encuentran ejecutando tareas en ese momento deberán terminarci´ lasonantes habr´de poder empezar con una nueva. a t enido en cuent a las circunst ancias reales que acont ecen y s´ Un esquema de todo este proceso es representado en la Figura 2, donde se olo considerar´ a las aprecia que el sistema siempre está informado de la posición en la que se encuent areas es de ejecut ar. La nueva soluci´ tran lospendient vehículos. on podr´ eh´ıculos y sobre las posibles t areas que est ar´ıan ejecut ando. a cambiar la asignaci´ on de t areas

a veh´POSICIÓN ıculos, t eniendo en cuent ıculos que se encuent ran ejecut ando t areas en Estado de los vehículosa que los veh´ DE LOS VEHÍCULOS

Localización

FREE | ASSIGNED | BUSY ese moment o deber´ DEPOTVEH | NOMDEPOTVEH USEDVEH NONUSEDVEH an t |erminarlas ant es de poder empezar con una nueva. Para ayudar

a solvent ar t oda la casu´ıst ica en la que pueden encont rarse los veh´ıculos se han definido SOLICITUD DE

ALGORITMO

TAREAS Estado tareas unas tareas ficticias, verde las ep´ ıgrafe 6.4, queSEGUIMIENTO cont ienen informaci´DE SOLUCIÓN PENDING | IN PROCESS | FINISHED DINÁMICO on sobre la posici´ OPTIMIZACIÓN on de los

v

INFORMACIÓN DE LA RED VIARIA

Estado de la red Distribución de la velocidad por áreas

Fig. 2 Esquema de seguimiento Figur a dinámico 6.2: Esquema del seguimient o dinámico

Un esquema de t odo est e proceso es represent ado en la Figura 6.2, donde se que el sist siempre est ´ 3aprecia Eventos deema Reoptimización eh´ıculos.

a informado de la posici´ on en la que se encuent ran los

v reoptimizaciones comentadas se lanzan cuando ocurren algunas circunstancias Las Como ejemplo se puede considerar un caso con dos veh´ıculos y seis t areas; destacables, llamadas eventos de reoptimización. Cuatro eventos distintos han sido cuat ro de dichas t areas se t rat an de t areas de export aci´ propuestos: on y dos de ellas son t areas de import aci´

 Un tiempo fijo. on. Los veh´ıculos comienzan la jornada en el dep´ osit o y deben complet ar t odas  Al terminar una tarea. las t areas, ret ornando nuevament e al dep´  Cuando un vehículo se desvía de su posición deseable un determinado factor. osit o. Con la informaci´ on disponible al principio  En un instante crítico. de la jornada, el sistde ema considera como mejor soluci´ erse los enlaces la Figura 6.3.mejora El en procedimiento iterativo de no tiene por quémost tener todos los on la radaena cuenta cont inuaci´ on yde eventos de reoptimización señalados; será necesario establecer una solución t ambi´VEH en en 1: laentre Figura 6.3a; encuent raelatnúmero endiendo a las rest ricciones t empocompromiso capacidad reoptimizaciones. Ini(Depot ) →la1 misma →de2 adaptación →se 4→ 6→y End(Depot ) de rales most en la Tabla 6.1 yson los sencillos t iempos dede desplazamient os En esperados, que pueden Los dosradas primeros eventos comprender. el primero la reopVEH 2: ) →cierto 3 → 5tiempo, → End(Depot ) ha transcurrido un tiempo desde la v timización se Ini(Depot lanza cada cuando En el caso que los t iempos de desplazamient o a lo largo de la rut a coincidieran

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con los t iempos esperados1, las dist int as t areas ser´ıan at endidas en los inst ant es que se muest ran en la Tabla 6.2. 1

Se ha considerado t iempos de servicio nulos


anterior reoptimización. Este tiempo es fijado a priori, por ejemplo 15 minutos. En el segundo tipo de evento la reoptimización se lanza al concluir la ejecución de una tarea; de ese modo, antes que el conductor que acaba de terminar la tarea se dirija a la siguiente tarea, se examina si las condiciones del entorno han cambiado, y por tanto pueden existir mejores alternativas. El tercer evento de reoptimización lanza la misma cuando los vehículos se retrasan de las posiciones esperadas, intentando buscar soluciones que no tengan dificultades en alcanzar determinadas tareas. Una explicación del lanzamiento puede verse en la Figura 3. La Figura 3a muestra la asignación inmediata de un determinado vehículo, las tareas 1 y 2 en el ejemplo; y la Figura 3b muestra el esquema espacio-temporal para el cumplimiento de las ventanas temporales de las dos tareas que el vehículo tiene asignadas a priori. Si un vehículo se encuentra dentro de las franjas marcadas por líneas discontinuas para una determinada ventana temporal, entonces se encuentra dentro de una posición esperada para completar la tarea a tiempo; si el mismo se encuentra por encima de la línea discontinua superior y por debajo de la línea continua entonces el vehículo se encuentra retrasado respecto a su situación esperada, pero su desviación respecto a la posición esperada está dentro de un factor de tolerancia; si el vehículo se encuentra por encima de dicha línea continua, se hace necesaria una reoptimización, en búsqueda de soluciones más fiables. Las tareas que se analizarán de las asignadas al vehículo serán las que se encuentran dentro de una distancia de análisis. Siguiendo con el ejemplo de la Figura 3b un vehículo en la situación de a se encuentra dentro de su posición esperada para cumplir a tiempo la tarea 1 y la tarea 2; si el mismo se encontrara en la situación de b podría cumplir las restricciones temporales de la tarea 1, sin embargo es previsible que tenga dificultades para cumplir las restricciones temporales de la tarea 2, por lo que atendiendo a la distancia de análisis se lanzaría una reoptimización; en la situación c el vehículo se encuentra en una situación esperada para desarrollar la tarea 2; un vehículo en d se habría desviado y estaría algo retrasado, pero se encontraría dentro la ventana de tolerancia; por último, un vehículo en la situación e estaría retrasado para poder completar a tiempo la tarea 2, y se produciría una reoptimización, con la espera de poder encontrar una solución mejor del problema. El último de los eventos indicados lanza una reoptimización cuando se alcanza el instante crítico de una determinada tarea. Este instante se define como el momento en el que un vehículo necesitaría salir del depósito para poder realizar a tiempo la tarea correspondiente. Este tipo de evento de reoptimización será siempre un complemento de los anteriores, y nunca el algoritmo dinámico funcionará con él sólo.

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Fig. 3 Reoptimización por desviación de la posición esperada.

4 Test y Resultados Este epígrafe va a intentar comparar los eventos de reoptimización mostrados anteriormente. La reoptimización al terminar la tarea y la reoptimización en un instante crítico se realizarán siempre. Testeándose las otras dos reoptimizaciones como complemento de las anteriores. Este planteamiento se sustenta en el hecho de que la reoptimización no puede perder la oportunidad de cambiar la asignación de tareas sin necesidad de que el vehículo se vea afectado en mitad de la ruta; por tanto no se ha considerado oportuno dejar de usar la reoptimización en el momento que una tarea es finalizada. En el caso de reoptimizaciones cada cierto intervalo de tiempo, una importante cuestión sería determinar dicho intervalo temporal. Se diseño para tal fin un experimento que, sobre un mismo problema (instancia R1.1 para 25 tareas), iba variando dicho intervalo de reoptimización, ReOptTime. De este modo se pretendía ver cómo se comportaba la solución (ver Figura 4a) y cuánto tiempo de ejecución en la CPU consumía (ver Figura 4b). Los resultados muestran cómo por norma al disminuir el intervalo de reoptimización aumenta la calidad de la solución (ver Figura 4a), aunque aumenta el tiem1039


po de computación consumido (ver Figura 4b). A la vista de los resultados, un intervalo de reoptimización de unos 10 minutos se ha considerado el más apropiado, dado que aumenta la calidad de la solución sin aumentar excesivamente el tiempo de computación.

Fig. 4 (a) Coste total de la solución y (b) tiempo computacional consumido dependiendo del intervalo de reoptimización.

La Tabla 1 muestran una comparativa de los diferentes eventos de reoptimización testeado para diferentes tamaños de problemas. En la misma se muestra el porcentaje de mejora respecto al caso de no aplicar reoptimización. FinT significa que existe reoptimización al finalizar una tarea, FixT significa que se han añadido reoptimizaciones cuando pasa un cierto tiempo fijo, y por último DEP significa que se han añadido reoptimizaciones cuando existe desviación de los vehículos sobre la posición esperada. Las tablas muestra varios detalles a destacar. El primero que, por norma general, añadir nuevos eventos de reoptimizaciones mejora la calidad de las soluciones; de media la opción de reoptimizar cada cierto tiempo y cuando termina una tarea es la que mejores prestaciones presenta. Cuando se habla de casos particulares el comportamiento no es siempre así; reoptimizar más veces no tiene necesariamente que implicar mayor mejora. Este hecho es lógico; dado que las reoptimizaciones cambian asignaciones de tareas a vehículos ante circunstancias adversas, los vehículos cambian sus rutas; sin embargo estos cambios no garantizan que el tráfico vaya a ser fluido en la nueva ruta. Otra consideración a tener en cuenta es el tiempo de computación que ocupa cada una de las alternativas mostradas; los tiempos para todos los tipos de reoptimizaciones por número de tareas se presentan en la Tabla 2.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 1 Comparación de diferentes eventos de reoptimización – Mejora Número Tareas 25

Clase FinT 5,88 1,76 4,38 4,18 4,96 3,96 4,30 4,47 8,05 7,66 5,66 7,27

R1 C1 RC1 Total R1 C1 RC1 Total R1 C1 RC1 Total

50

100

Mejora (%) FixT 6,41 1,92 4,97 4,62 5,25 3,74 4,66 4,62 8,61 7,34 5,75 7,43

DEP 6,19 1,83 4,97 4,50 5,07 3,97 4,46 4,56 8,37 7,44 5,76 7,36

Tabla 2 Comparación diferentes eventos de reoptimización – Tiempo computacional (seg.) Evento FinT DEP FixT

25 0,63 1,27 2,12

Número de tareas 50 2,05 3,82 6,92

100 12,97 21,24 35,15

5 Conclusión La reoptimización como búsqueda dinámica de mejores soluciones se ha presentado como un proceso eficaz para la mejora de procedimientos donde existe incertidumbre. Sin embargo, es necesario se cuidadoso en que momentos se realizan dichas reoptimizaciones, para de este modo conseguir además un proceso eficiente. Un aumento del número de reoptimizaciones trae consecuentemente ligado una mejora media en las soluciones encontradas, pero esta mejoría no se comporta de modo proporcional al aumento del tiempo computacional. Este trabajo a testeado diferentes eventos de reoptimización, para demostrar que no sólo es necesario realizar este proceso iterativo de mejora, sino que además es conveniente elegir adecuadamente el momento en el cual realizarlo.

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6 Referencias Adbdel-Aty MA, Kitamura R y Jovanis PP (1997). Using stated preference data for studying the effect of advanced traffic information on drivers’ route choice. Transportation Research Part C - Emerging Technologies, 5(1), pp. 39–50. Chorus CG, Arentze TA, Molin EJE, Timmermans HJP y van Wee B (2006). The value of travel information: Decision strategy-specific conceptualizations and numerical examples. Transportation Research Part B - Methodological, 40(6), pp. 504–519. Escudero A, Muñuzuri J, Arango C y Onieva L (2011). A satellite navigation system to improve the management of intermodal drayage. Advanced Engineering Informatics, 25(3), pp. 427– 434. Escudero A, Muñuzuri J, Guadix J y Arango C (2011) Heurística de asignación en tiempo real de vehículos a tareas de acarreo intermodal. Dirección y Organización, Revista de Ingeniería de Organización, 45, 32-37. Escudero A, Muñuzuri J, Guadix J y Arango C (2013). Dynamic approach to solve the daily drayage problem with transit time uncertainty. Computers in Industry. doi: 10.1016/j.compind.2012.11.006. Escudero A, Muñuzuri J, Onieva L, Arango C (2012) Oportunidades del daily drayage problem en la optimización del transporte de mercancías europeo. 6th International Conference on Industrial Engineering and Industrial Management. XVI Congreso de Ingeniería de Organización (CIO 2012), Vigo. Koutsopoulos HN y Xu H (1993). An information discounting routing strategy for advanced traveler information systems. Transportation Research Part C - Emerging Technologies, 1(3), pp. 249–264. Levinson D (2003). The value of advanced traveler information systems for route choice. Transportation Research Part C - Emerging Technologies, 11(1), pp. 75–87. Pillac V, Gendreau M, Guéret C y Medaglia AL (2013). A review of dynamic vehicle routing problems. European Journal of Operational Research, 225(1), pp. 1–11. Psaraftis HN (1995). Dynamic vehicle routing: Status and prospects. Annals of Operations Research, 61(1), pp. 143–164.

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Sistemas de Ayuda a la Toma de Decisiones para la gestión de Incidencias Decision Support Systems for Incident Management. Valero R, Boza A1, Vicens E Abstract This article talks about how the DSS (Decision Support Systems), working in support of decision making when these incidents are given by the company. The incidence is an event not expected by the company, which may have a negative impact in the company. So, it is necessary developing methods to act on its resolution quickly and efficiently. The main thing is to define the types of decisions by way of resolution, both being guided by the policies and rules of the company, as the decision maker, creating a hierarchy in decision-making in the company, and giving importance a good collection of information and the most effective treatment of this for use in the company.

Resumen Este artículo aborda los DSS, sistemas de ayuda a la toma de decisiones, cuando estas deben tomarse por incidencias en la empresa. La incidencia no es más que un evento no programado por la empresa, que puede repercutirnos negativamente en la empresa. Con lo que tenemos que crear métodos para actuar en su resolución de forma rápida y eficaz. Lo principal es definir los tipos de decisión por su forma de resolución, tanto por estar guiadas por las políticas y las normas de la empresa, como por quien toma las decisiones, creando una jerarquía en la toma de decisiones en la empresa, y dando importancia a una adecuada recogida de información y un tratamiento efectivo de la misma por la organización.

1Andrés Boza ( e-mail: [email protected]) Centro de Investigación Gestión e Ingeniería de la Producción (CIGIP). Universitat Politècnica de València. Camino de Vera s/n, 46022 Valencia. Spain

* Esta investigación se ha llevado a cabo en el marco del proyecto financiado por el Vicerrectorado de Investigación de la Universitat Politècnica de València titulado “Sistema de ayuda a la toma de decisiones ante decisiones no programadas en la planificación jerárquica de la producción (ADENPRO-PJP)” Ref. SP20120703.

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Keywords: Decision Support Systems, Incident Management Palabras clave: Sistemas de Ayuda a la Toma de Decisiones, Gestión de Incidencias.

1 Introducción La toma de decisiones en un entorno empresarial implica decidir qué hacer frente a un problema que tenga la empresa o simplemente elegir una opción en algún tema en el que tengamos esa capacidad. Esto nos lleva a plantearnos, que decisión es la buena y cual la mala, aunque quizás sería más correcto hablar sobre qué decisión es la mejor de todas las posibles que tenemos o las más adecuada según sus circunstancias. ¿Y cómo lo sabemos? Los DSS son herramientas de TI (Tecnologías de la Información) que ayudan aportando información y dando posibles soluciones, según sea el caso, a la toma de decisiones. Esto aplicado a la gestión de incidencias produce beneficios, al mejorar los tiempos de repuesta y evitar sobrecostes. Para intentar explicar esto mejor tenemos que hablar de los distintos niveles de la empresa y el tipo de decisiones que toman. Las decisiones que se toman en los distintos niveles de la organización no son siempre estructuradas, y en ocasiones se requieren tomar decisiones semi-estructuradas, donde se tiene información parcial y donde el decisor participa introduciendo sus propios criterios. Según subimos en la cadena de mando las decisiones se van haciendo cada vez más difíciles porque son cada vez más abstractas. Esto lleva a diseñar programas especializados en la toma de decisiones, los cuales tienen como función principal la de mejorar el proceso de toma de decisiones intentando obtener toda la información que necesita el decisor para tomar la decisión, de forma rápida, y de exponer esta información de manera que sea fácil y rápida de entender. Pero este tipo de programas se han especializado según el tipo de decisor, porque la información necesaria en cada caso es distinta y lo que afecta la decisión a la empresa también. Una decisión operativa tiene una importancia menor y causa un daño menor en la empresa si se toma mal, que una decisión estratégica. Según los distintos tipos de decisiones posibles existen distintos programas de ayuda a la toma de decisiones como son MIS (Management Information SystemsSistema de Ayuda Gerencial), DSS (Decision Support Systems-Sistema de Apoyo a las Decisiones) y EIS (Executive Information Systems-Sistema de Información Ejecutiva). Cada uno de los cuales está diseñado para dar servicio a un nivel de la empresa distinto, con lo que tratan la información de forma distinta y las decisiones que se toman en cada uno de ellos afectan en distinto nivel a la empresa. La gestión de incidencias es un sistema para el que los DSS tienen mucha importancia, porque hay que decidir cómo actuar ante un evento no programado en la 1044


empresa. Esto puede ser un evento bueno o malo, aunque siempre se hace hincapié en lo malo, porque causa perjuicio económico, aunque no actuar en el momento adecuado en un evento bueno puede hacer que este se convierta en malo. Pero lo importante aquí es la importancia del evento, un pequeño problema en producción, puede ser solucionado en un momento sin afectar a nada ni a nadie, con lo que la incidencia se ha resuelto sin producir perjuicio. Pero puede ser, que un problema de producción no se pueda resolver a su nivel y tengamos que subir al nivel siguiente (mandos intermedios) o incluso llegar hasta la dirección de la empresa. Es en este punto donde los DSS ganan importancia.

2 Análisis de la Literatura Ahora se verá como tratan este tema otros autores, donde dan una visión de la aplica la gestión de incidencias en los sistemas de ayuda a la toma de decisiones. Los DSS son importantes en producción porque son efectivos en los problemas de producción, tanto en la programación como en el balanceo. En la programación solucionan problemas de programación o de flexibilidad de horarios y en balanceo equilibran el trabajo por línea (Guo et al., 2009). Para Boza et al. (2009), es muy importante que la jerarquía de la empresa y del DSS se integren la una en la otra para mejorar y flexibilizar la toma de decisiones dentro de la empresa. Entrando ya en el tema de las incidencias, Barash et al. (2007) nos comenta que es una ayuda muy importante la utilización de TI en la gestión de incidentes, es bueno para dar un servicio normal y minimizar los efectos de estos. Las incidencias tienen distinta importancia dentro de la empresa y hay que analizar su complejidad y a qué grupo de personas es conveniente asignarlas para su buena resolución. Para Asghar et al. (2008), el DSS hay que adaptarlo a las necesidades que tenemos, lo cual tiene una gran importancia, porque esto nos dará una ventaja competitiva. Así, Ibrahim and Allen (2012) indican que existe un sistema de roles en la cadena de mando y cada miembro de esta tiene que realizar la función que tiene asignada, y que la información a compartir tiene que ser la última conseguida para poder actuar con mayor eficacia sobre el incidente. El problema en la toma de decisiones es conseguir buena información (Allen, 2011; Kim et al., 2007), pero en situaciones donde el tiempo es crítico la intuición es la primera recogida de datos, y después se puede tomar las decisiones de forma racional, casi racional o intuitiva, según sean las necesidades. Esto hace que las experiencias, elementos cognitivos, objetivos, valores y prioridades de cada persona sean fundamentales en la recogida de información inicial (intuición) y en la toma de decisiones.

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Según Pavanasam et al. (2010), la toma de decisiones requiere tener conocimiento de múltiples contextos o dimensiones, y para ello es bueno crear una base de conocimiento, políticas y requerimientos necesarios para una buena toma de decisiones. Para la gestión de incidencias Bartolini et al. (2010), explican que se requiere para el buen funcionamiento del proceso de toma de decisión, crear un modelo realista, lo que necesita una gran cantidad de parámetros, lo cual genera unos problemas que no se pueden optimizar analíticamente y que generan una gran complejidad computacional. Por último Bartolini et al. (2009) argumenta que hay que reducir el impacto de la incidencia crítica, porque reducir tiempo de respuesta reduce los costes, lo cual es muy beneficioso y una ventaja competitiva. En la figura 2 podemos apreciar cuales serían los pasos que tendríamos en un DSS para tomar una decisión y como funciona cada uno.

Fig. 1 Flujo de un DSS (Bartolini et al., 2009)

En la figura 3 se puede apreciar como es el ciclo de vida de un incidente, como una vez creado entra en un bucle que se realimenta hasta que se resuelve, pudiendo estar un tiempo en espera para su futura reactivación y nueva búsqueda de solución.

Fig. 2 Ciclo de Vida de un Incidente (Bartolini et al., 2010)

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3 Análisis Después de todo lo expuesto, lo que se puede deducir como fundamental en el proceso de toma de decisiones para la gestión de incidencias es:  El tiempo de respuesta es fundamental para evitar sobrecostes.  Que la información con la que trabajamos en una incidencia no es la misma que tenemos del trabajo normal de la empresa, sino que tiene que ser relevante para esa incidencia.  Que tenemos que conseguir trabajar con la información más reciente posible y de mejor calidad, con todos los problemas que eso aporta.  Que el DSS tiene que estar adaptado a nuestras necesidades. Debe ser un sistema amigable y que aporte toda la información que necesitamos y que nos de las posibles soluciones o nos permita en todo caso realizar previsiones de posibles soluciones.  Que existe un importante factor humano en la toma de decisiones, sobre todo como subimos jerárquicamente en la empresa. Definido esto nos encontramos que con un ordenador de gran capacidad de cálculo), y un DSS que se adapte perfectamente a nuestra empresa, con un modelo lo más exacto posible a la realidad, podemos tener una gran ventaja competitiva, porque la resolución de problemas será rápida y eficaz de forma que nos permitirá ahorrar en la empresa. Pero podemos decir que el punto más importante de todos es que hay que definir correctamente la jerarquía de la empresa e integrarla con la jerarquía del DSS, y definir como se toman las decisiones dentro de esta, quién toma las decisiones estructuradas, que suelen estar automatizadas. Quién toma las decisiones semiestructuradas, que se están automatizando cada vez más y que necesitan dentro del DSS un tipo de información más concreta que global. Y por último quién toma las decisiones no estructuradas que son manuales y tienden a ser semiautomáticas, y que necesitan una información más global. El impacto que tiene la incidencia sobre un nivel de decisión debe ser abordado desde una perspectiva amplia de la jerarquía de decisión, ya que una adecuada decisión para una nivel puede generar problemas en otros niveles debido a la existencia de dicha incidencia. En resumen una buena recogida de datos, una base de datos con la que trabajar alineada con los objetivos de la empresa, y en el caso de las incidencias con información relevante para la resolución de la incidencia, y un DSS que sepa gestionar la información de la base de datos de forma amigable, rápida y económica para ayudar a la toma de decisiones dentro de la empresa permiten mejorar el presente y el futuro de la empresa.

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4 Líneas Futuras El futuro en este campo se puede decir que ya se está aplicando en las empresas más punteras, y lo siguiente que vendrá solo se puede prever por la evolución que tenga la informática, la cual cambia a una velocidad impresionante, y la gestión que realice la empresa sobre la misma. DSS que trabajen vía web son ya una realidad, por ejemplo Bartolini et al. (2010, 2009) trabajan sobre un sistema apoyo a la toma de decisión gestionado por grupos y que funciona vía web. Otras nuevas propuestas y herramientas nos abren nuevas posibilidades, Brynielsson (2007) indica que el ejército utiliza también este tipo de técnicas, pero las lleva más allá, hasta el punto de utilizar en un juego de guerra Teorías de Juego e Inteligencia Artificial. Por último, Trappey et al. (2007) trata la gestión de incidencias en las distintas partes del proceso productivo donde, por ejemplo, la utilidad de los DSS en el desarrollo de nuevos productos genera una gran ventaja competitiva, al reducir los tiempos en la solución de problemas que tenemos en el diseño de estos nuevos productos, lo cual genera un ahorro económico. El trabajo en el campo de la automatización de la toma de decisiones y del procesado de información más potentes está permitiendo crear métodos en los que los ordenadores cada vez tienen más peso en las decisiones o facilitan en mayor medida la labor del decisor, lo cual, en el caso de gestión de incidencias alcanza a múltiples ámbitos de la organización.

5 Conclusión Un DSS es un sistema que ayuda a la toma de decisiones y es una herramienta fundamental para la gestión de incidencias en la organización. La gestión de incidencias puede requerir de la toma de decisiones en diferentes niveles de toma de decisión de la organización. Para ello, se debe definir 1) el proceso de toma de decisión para gestionar la incidencia y las etapas en las que participa el DSS. 2) la información relevante para buscar la solución de esa incidencia, la cual debe ser lo más reciente posible, 3) un interfaz amigable y fácil de usar por el decisor de la incidencia y 4) el modelo de resolución de la incidencia. Un DSS capaz de facilitar la gestión de incidencias puede mejorar el proceso productivo, por ejemplo reduciendo tiempos de inactividad, reduciendo los daños físicos, mejorando la calidad del producto o la flexibilidad del proceso, lo que al final es una ventaja competitiva.

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6 Referencias Allen, D., 2011. Information Behavior and Decision Making in Time-Constrained Practice: A Dual-Processing Perspective. J. Am. Soc. Inf. Sci. Technol. 62, 2165–2181. Asghar, S., Alahakoon, D., Churilov, L., 2008. Categorization of disaster decision support needs for the development of an integrated model for DMDSS. Int. J. Inf. Technol. Decis. Mak. 7, 115–145. Barash, G., Bartolilli, C., Wu, L., 2007. Measuring and improving the performance of an IT support organization in managing service incidents. Ieee, New York. Bartolini, C., Stefanelli, C., Tortonesi, M., 2009. Business-impact analysis and simulation of critical incidents in IT service management. Ieee, New York. Bartolini, C., Stefanelli, C., Tortonesi, M., 2010. SYMIAN: Analysis and performance improvement of the IT incident management process. IEEE Transactions on Network and Service Management 7, 132 –144. Boza, A., Ortiz, A., Vicens, E., Poler, R., 2009. A Framework for a Decision Support System in a hierarchical extended enterprise decision context. Enterprise Interoperability 113–124. Brynielsson, J., 2007. Using AI and games for decision support in command and control. Decis. Support Syst. 43, 1454–1463. Guo, Z.X., Wong, W.K., Leung, S.Y.S., Fan, J.T., 2009. Intelligent production control decision support system for flexible assembly lines. Expert Syst. Appl. 36, 4268–4277. Ibrahim, N.H., Allen, D., 2012. Information sharing and trust during major incidents: Findings from the oil industry. J. Am. Soc. Inf. Sci. Technol. 63, 1916–1928. Kim, J.K., Sharman, R., Rao, H.R., Upadhyaya, S., 2007. Efficiency of critical incident management systems: Instrument development and validation. Decis. Support Syst. 44, 235– 250. Pavanasam, V., Subramaniam, C., Mulchandani, M., Parthasarathy, A., 2010. Knowledge Based Requirement Engineering Framework for Emergency Management System. Ieee Computer Soc, Los Alamitos. Trappey, A.J.C., Chiang, T.-A., Chen, W.-C., Kuo, J.-Y., Yu, C.-W., 2007. A DEA benchmarking methodology for new product development process optimization. Springer-Verlag London Ltd, Godalming.

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Sistema de Control y Reprogramación de la Producción basado en Captura Inalámbrica de Datos en Planta Control System and Rescheduling of Production Based on Wireless Data Capture at Floor Eguizábal L1, Lago A2, Fernández A3 Abstract This paper presents a manufacturing control system that allows combine information from the planning of the production, generated from the ERP, with real-time information collected from the manufacturing plant situation. Thus, the control system can reprogram the production based on the current state of production workshop and new events that occur day by day (rush orders, machine breakdown, and so on.). This application of production control is based on an innovative data capture system in workshop, based radio frequency identification (RFID). To increase the versatility of the capture system, have combined the use of RFID readers, with the implementation of a wireless data network based on the ZigBee protocol. The use both technologies enables the development of an easy implantation systems and low cost. The solution developed is useful for companies with low degree of automation, which require reliable data in real time, to perform tasks such as: asset management, queue management of manufacture, real calculations of costs and manufacturing time measurement. Throughout this work will be described in detail, the data capture system and the application to control the production developed.

1

Luis Eguizábal Gándara ( e-mail: [email protected]) Dpto. de Tecnoloxía Electrónica. Escola de Enxeñería Industrial. Universidade de Vigo. C/ Torrecedeira 86, 36208 Vigo. 2

Alfonso Lago Ferreiro ( e-mail: [email protected]) Dpto. de Tecnoloxía Electrónica. Escola de Enxeñería Industrial. Universidade de Vigo. Campus Universitario Lagoas-Marcosende, 36310 Vigo. 3

Arturo Fernández Gónzalez ( e-mail: [email protected]) Dpto. de Organización de Empresas y Marketing. Escola de Enxeñería Industrial. Universida de de Vigo. Campus Universitario Lagoas-Marcosende, 36310 Vigo.

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Resumen Este artículo presenta un sistema de control de la producción que permite combinar la información procedente de los planes de fabricación, generada desde el sistema de gestión empresarial (ERP), con la información recogida en tiempo real de la situación de la planta de producción. De esta manera el sistema de control permite reprogramar la producción basándose en el estado actual de los talleres de producción y nuevos eventos que se producen en el día a día (pedidos urgentes, avería en máquinas, etc.). Esta aplicación de control de la producción está basada en un innovador sistema de captura de datos en planta, que emplea la identificación por radio frecuencia (RFID). Para incrementar la versatilidad del sistema de captura se ha combinado el uso de lectores RFID, con la implementación de una red de datos inalámbrica basada en el protocolo ZigBee. El uso de ambas tecnologías permite el desarrollo de un sistema de fácil implementación y bajo coste. La solución desarrollada es útil para empresas con bajo grado de automatización, que requieran datos fiables en tiempo real, para realizar tareas como: gestión de activos, gestión de colas de fabricación, cálculos reales de coste y tiempos de fabricación. A lo largo de este trabajo se describirán en detalle, el sistema de captura de datos y la aplicación para el control de la producción desarrollada.

Keywords: Production Management, Production Scheduling and Rescheduling, Enterprise Resource Planning, Asset Management, Workshop Data Capture, RadioFrequency IDentification (RFID). Palabras clave: Gestión de la Producción, Programación y Reprogramación de la Producción, ERP, Gestión de Activos, Captura de Datos en Planta, Identificación por Radio Frecuencia.

1 Introducción El sistema de control de la producción que se presenta en este artículo está pensado para empresas organizadas en talleres funcionales (Job-Shop) con bajo grado de automatización. Este tipo de centros de producción se caracterizan por atender una fabricación bajo pedido, con poco grado de estandarización en sus productos y con lotes pequeños de fabricación. Otro aspecto que destaca en este tipo de empresas es la dificultad de elaborar la programación de la producción (Scheduling) dejando la complicada tarea de gestionar las Órdenes de Trabajo (OT) al encargado del taller. Como resultado de esta situación los talleres con distribución por proceso, tienen la gran ventaja de ser muy versátiles a la hora de abordar distintos tipos de tareas y productos, pero presentan el inconveniente de ser difíciles de gestionar. Blazewicz J (1996) analiza en detalle la problemática de realizar la planificación de la producción en talleres de tipo Job Shop. Con la finalidad de obtener me1051


joras en la productividad en talleres de fabricación con distribución de este tipo y bajo grado de automatización, se pensó desarrollar un Sistema de Captura de Datos en Planta (SCDP), que ofrezca al departamento de producción, datos fiables y en tiempo real de la situación del taller. Esta información permitirá la reprogramación de la producción y, en general, la toma de decisiones para incrementar su eficiencia de los procesos de fabricación. Hasta la fecha, la toma de datos en la mayoría de las empresas de tipo Job Shop se realiza, en el mejor de los casos, mediante terminales táctiles de comunicación hombre-máquina o con PCs. Este método tiene el inconveniente que los operarios tienen que introducir la información de las tareas realizadas manualmente, aspecto que provoca la baja fiabilidad de los datos recogidos, tanto por los posibles errores como por la posibilidad de alterar los datos a conveniencia del trabajador. La aparición de la tecnología RFID, ha permitido implementar SCDP semiautomáticos, aspecto que incrementa la calidad de la información aportada y reduce los tiempos improductivos de los operarios. En este trabajo se presenta tanto la parte hardware con el software para implementar un Sistema de Control de la Producción (SCP) basado en un SCDP con tecnología RFID. Con este objetivo se ha organizado este artículo de la siguiente forma. En la sección 2 se analizan las dos tecnologías principales que se emplean para implementar el SCDP: el RFID y las redes de datos inalámbricas. En la sección 3 se explica en detalle el SCDP desarrollado, describiendo la configuración de los lectores y la estructura de la red desarrollada. En la sección 4 se presenta el software realizado para implementar el sistema de control de la producción propuesto, se presentarán la distintas aplicaciones software desarrolladas. Por último, En la sección 5 se dedicará al análisis de las conclusiones y las líneas de investigación futuras.

2 Tecnologías Utilizadas para la Implementación del Sistema de Captura de Datos en Planta Con la finalidad de implementar un sistema de control y reprogramación de la producción adecuado para empresas de tipo Job-shop, se ha desarrollado un novedoso SCDP que proporcionase datos fiables y de la forma automática. Para ello se seleccionaron dos tecnologías: el RFID y las redes de datos inalámbricas.

2.1 Identificación por Radio Frecuencia El RFID permite identificar artículos, sin contacto óptico entre el lector y la etiqueta, mediante radiofrecuencia. Presenta otra gran ventaja respecto a otros méto1052


dos de identificación como los códigos de barras, y es que permite la lectura simultánea de múltiples etiquetas. Estas dos características hacen al RFID de una herramienta idónea para la recogida de datos en planta. Existe numerosa literatura donde se analizan la aportación del RFID a la gestión empresarial, en aspectos desde la cadena de suministro Xiaowei A (2012), hasta los procesos de producción Duncan M (2003) y Kurt H (2008). En toda aplicación RFID existen tres componentes básicos: las etiquetas, los lectores-escritores de etiquetas y el software de gestión de datos. En la figura 1, se muestra la estructura más habitual de los sistemas RFID.

Fig. 1 Estructura sistema RFID

Los parámetros más importantes que se debe de analizar a la hora de abordar una implantación RFID son:  Elección de la frecuencia de funcionamiento del sistema RFID. La frecuencia marcará la distancia de lectura entre el lector y la etiqueta. Otro aspecto a seleccionar es el tipo de etiquetas. Se pueden clasificar: en pasivas (muy sencillas, baratas y sin batería) y las activas (más complicadas, con baterías, pero cuya distancia de lectura es mucho mayor). Entre ambas existe la variante de las semiactivas. Otro parámetro importante a considerar es el tipo de productos que se van a etiquetar en la aplicación: artículos, herramientas o simplemente los papeles. Para la implementación de nuestro SCDP, se emplearán etiquetas HF de bajo coste e imprimibles con impresoras RFID convencionales, que se pegarán en las Órdenes de Fabricación (OF) para controlar la evolución de los procesos de producción. Los lectores serán también de bajo coste de tipo embebidos (Embedded RFID Readers). 1053


2.2 Redes de Datos Inalámbrica. Red ZibBee A la hora de implementar la red de datos se buscó una opción que permitiese su fácil implementación y un coste reducido. Además el sistema de captura no va a generar un grado volumen de datos. Después de analizar distintas posibilidades se decidió emplear la red ZigBee, basada en el estándar IEEE 802.15.4. Este estándar define dos tipos de dispositivos: Dispositivos de funcionalidad completa (Full Function Device, FFD). Dispositivos de Funcionalidad Reducida (Reduced Function Device, RFD). Un FFD puede funcionar como coordinador PAN (Personal Área Network), como router o como dispositivo final (End device). Los FFD´s pueden comunicarse con cualquiera de estos tres tipos de dispositivos. Sin embargo un RFD suele ser un dispositivo más simple, con menor capacidad para realizar tareas complejas o de larga duración. En la figura 2, se indica la estructura de tres posibles configuraciones de las redes ZigBee.

Fig. 2 Estructuras más habituales de redes ZigBee

El rango máximo entre nodos de la red depende de la potencia de los mismos, pero la distancia está comprendida entre 100m y 1Km. La utilización de los Router permite ampliar el tamaño de la red. Este tipo de comunicación ofrece caminos redundantes por toda la red, de modo que si falla un camino, otro se hará cargo del tráfico. En Callawy E (2002) se presenta una descripción detallada de las redes bajo la norma IEEE 802.15.4. Actualmente existen cerca de una veintena de compañías dedicadas a la fabricación de chips para el protocolo ZigBee, entre las más importantes están: Texas Instruments, Microchip Technology, Digi International. En este trabajo después de 1054


estudiar, el hardware y el entorno de desarrollo de estos tres fabricantes, se ha optado por la solución planteada por Digi International, debido a la cantidad de información disponible, a su robustez y su amigable entorno de trabajo.

3 Implementación de la Red de Captura de Datos en Planta Tal como se indicó en las secciones anteriores, el SCDP que se presenta en este trabajo está basado en dos tecnologías novedosas: las redes ZigBee y el RFID. La primera de ellas se ha empleado para la implementación de la infraestructura de la red de captura de datos, y la segunda, como elemento de lectura de información. A continuación, se describe el desarrollo del sistema de captura de datos. Para este trabajo se ha desarrollado una red ZigBee en configuración en estrella; es decir, con un coordinador de red Access Point (AP) y un total de cinco de dispositivos finales (Router/End Device) uno por máquina. En estos dispositivos finales es donde se implementarán los lectores RFID. Por lo tanto, serán los puntos donde se recogerá la información de las etiquetas. El AP se conectará directamente al puerto USB del PC y se encargará de recopilar la información de toda la red. A continuación, se describe la estructura de los elementos de la red y cuál es su configuración.  Access Point. Para el envío de información a los Router/End Device se ha seleccionado una comunicación de tipo Broadcast, de tal manera que los paquetes de datos enviados por el AP serán recibidos por todos los elementos de la red. En las peticiones de información enviada a los Router se enviará el número de nodo (nº de máquina) al que se le realiza la petición, de tal manera que solo responderá al que pertenezca el identificador enviado.  Estructura de los Router/EndDevice. Este tipo de nodos son los elementos de captura de datos. En este apartado se describirá cuál es el hardware y software desarrollado para implementar los dispositivos finales de la red, basados en lectores RFID. Para la implementación de los End Device son necesarios tres elementos: 1. El lector RFID. Lo primero que se hizo fue seleccionar un lector adecuado que tuviera posibilidad de comunicación, además de un precio asequible. Después de analizar distintos lectores de varios fabricantes, se optó por los lectores embebidos del fabricante Skyetek. Éstos, además de tener varias salidas de comunicación (UART, SPI, USB) tienen un robusto protocolo anticolisión, que permite leer varias etiquetas simultáneamente, aspecto este último necesario para esta aplicación. El lector empleado dispone de una antena integrada.

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2. El modem ZigBee. Se seleccionó el mismo modelo que para el AP, del fabricante Digi. Éstos, se programaron en modo AT, y con dirección de destino la del AP. 3. Un microcontrolador. Para comunicar el lector RFID con el modem ZigBee es necesario implementar un circuito interface entre ambos. Para la realización de las primeras pruebas se seleccionó la plataforma de hardware libre Arduino, basados en los microcontroladores de Atmel AVR. Este entorno permite desarrollar aplicaciones, bajo lenguaje C++, de forma rápida y a bajo coste. Una vez depurada el hardware se desarrolló la placa lectora que se muestra en la figura 3.

Fig. 3 Detalle del Router/EndDevice con todos sus componentes

4 La Aplicación para Control de la Producción El sistema de control de la producción desarrollado está basado en tres aplicaciones software: 1. El programa para la gestión del SCDP. Esta aplicación ha sido desarrollada en C# y tiene por misión la exploración de sistema de captura, para determinar que etiquetas RFID se encuentran en cada uno de los lectores. El SCDP está basado en la colocación en las OF, de unas etiquetas RFID pasivas de HF. Estas etiquetas se pueden imprimir con impresoras RFID, para ser pegadas con las OFs. En empresas de tipo Job-Shop estudiadas, las órdenes de fabricación se mueven por el taller con sus materiales. El SCDP que se presenta en este artículo está pensado para una planta en la cual se disponen de cinco máquinas, en cada una de éstas se colocarán dos bandejas archivadoras, con sus respectivos lectores de RFID. En la primera de las bandejas se colocará la OF que está en ejecución, junto con la etiqueta que identifica al operario que va a realizar la tarea, y en la segunda, se ubicarán las OFs, que se encuentran en espera para ser procesadas en la máquina. La información recogida se grabará en una BBDD. 1056


Fig. 4 Consola de gestión del SCDP

2. Una aplicación realizada en Access que permite tratar los datos suministrados por el SCDP. Este software actúa como Middleware, filtrando la cantidad de datos que se recogen del SCDP. Para ello se han definido varias tablas donde se almacenarán las OFs que se encuentran en ejecución y en espera en cada una de las máquinas, que forman el taller de producción. Estas OFs una vez ejecutadas se pasan a otras tablas, donde se almacenan históricos de los tiempos de ejecución y de espera de las mismas. Esta base de datos permite realizar:  Gestión de activos. Conociendo en todo momento qué OF se está ejecutando en cada máquina, que materiales se están y qué operario está trabajando con dicha OF. También informa sobre que OFs están en espera en cada máquina, cuándo se recepcionan las materias primas, o cuándo llegan materiales de operaciones externas, etc.  Medición de tiempos, cálculo de indicadores y costes de fabricación. Con el sistema de captura de datos basado en tecnología RFID, se podrá medir de forma automática e inmediata tiempos de inactividad y actividad de una OF, en su totalidad o en un centro de trabajo determinado, y/o un tiempo de referencia (p.ej. un turno, una semana, etc). Estos datos permitirán calcular asimismo indicadores de productividad como, la disponibilidad (relación entre tiempo productivo real –descontando paradas por setups, esperas o averías- y tiempo total destinado a producción), la eficiencia o rendimiento (relación entre tiempo teórico para la producción obtenida y tiempo real invertido). Los indicadores anteriores servirán para la determinación de la OEE (Overall Equipment Efficiency). En la figura 5, se puede observar un sinóptico de la planta estudiada, en la que se pueden apreciar las máquinas que están en marcha (color verde, se detecta OF y 1057


operario), en espera (color amarillo, sólo se detecta OF) y paradas (color rojo, no se detecta ni OF, ni operario).

Fig. 5 Sinóptico de la planta de producción

3. Software planificador de recursos empresariales (Enterprise Resource Planning ERP). Con la finalidad de realizar un reprogramación en tiempo real de la producción del taller, se ha unificado la información proveniente de la planta, con el programa de producción elaborado con ayuda de un sistema ERP. Para la implantación del ERP se ha seleccionado la aplicación integrada de código abierto OpenERP. Tomando como base el programa de producción obtenido de una empresa del sector del metal del área de Vigo y de los lectores ubicados en sus cinco talleres de producción, se optimiza la gestión de colas de producción en cada una de las máquinas. Esta optimización se consigue analizando parámetros como: fechas de entrega, prioridad de clientes, disponibilidad de materiales para la ejecución de una orden. En la figura 5, se puede observar las OF en espera y la secuencia de ejecución propuesta por el sistema.

5 Conclusiones y Líneas Futuras de Investigación En este artículo se ha presentado un novedoso sistema de control de la producción para empresas con grado bajo de automatización, que necesiten información en tiempo real con la finalidad de mejorar la gestión de sus talleres de fabricación. El sistema que se muestra en este trabajo presenta como novedad la utilización de un SCDP basado en lectores RFID inalámbricos, que permite que la recogida 1058


de información se realice con una mínima intervención por parte de los operarios, los cuales se limitan a ubicar las OFs en los lugares predeterminados para ello, sin necesidad de teclear datos ni tan siquiera utilizar pantallas táctiles. Esta característica hace que los datos recogidos sean inmediatos y más fiables. Partiendo de la información adquirida, se ha desarrollado una aplicación software que permite mejorar la gestión de los talleres de tipo Job-Shop, proporcionando información para: 1. Gestionar los activos 2. Conocer en tiempo real la situación de la planta de fabricación. 3. Medir los tiempos de ejecución y de parada, espera, avería, etc. 4. Realizar cálculos reales de indicadores y costes de fabricación 5. Optimizar la gestión de colas de fabricación. Después de la realización de este trabajo se ha observado la posibilidad de integrar todas las aplicaciones software desarrolladas en una única. Para ello se pretende desarrollar todo el sistema, como un módulo integrado en el OpenERP, lo cuál facilitaría el manejo del sistema de control de la producción. Otra línea de trabajo futuro es la definición de un algoritmo que automatice la reprogramación en tiempo real de la producción de la planta. Finalmente, también se estudia la posibilidad de mejorar el SCDP, de tal manera que éste aporte información sobre los tipos de paradas producidas, con la finalidad de poner en marcha un sistema de mejora para obtener mayores índices de OEE.

6 Referencias Błazewicz, J., Domschke, W., and Pesch, E. (1996). The job shop scheduling problem: Conventional and new solution techniques. European Journal of Operational Research, 93:1–30. Duncan McFarlanea, Sanjay Sarmab, Jin Lung Chirna, C.Y. Wonga (2003) Auto ID systems andintelligent manufacturing control. Pergamon, Engineering Applications of Artificial Intelligence 16 365–376. Ed Callaway, Paul Gorday, and Lance Hester (August 2002) Home Networking with IEEE 802.15.4: A Developing Standard for Low-Rate Wireless Personal Area Networks. IEEE Communications Magazine. Kurt Hozak, David A. Collier (2008) RFID as an Enabler of Improved Manufacturing Performance. Decision Sciences, Volume 39 Number 4 November 2008. Xiaowei Zhu a, Samar K. Mukhopadhyay b, Hisashi Kurata (2012) A review of RFID technology and its managerial applications in different industries. Journal of Engineering and Technology Management, 29 (2012) 152–167.

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Planificación y Control de la Producción en la Mejora del Proceso de Producción de Fabricación de Juegos Mesas: un Estudio de Caso Planning and Control of Production in the Improvement Manufacturing Process of Production Tables Games: A Case Study RaposoJ1, Costa-de MatosAN2, NunesA3 Abstract This study aimed to identify and implement the planning and control of production (PCP) in a manufacturing company of board games in order to describe and analyze the phases of PCP. To achieve the above objective, it became a literature on the chosen topic, and parallel to this was done to collect data for the development of the case study. This collection was mainly based on direct observation, made in the factory of the company, monitor the whole production process of its products, as well as conducting brainstorming. In then determined the need for deployment of PCP in the company under study. Therefore, it was possible to gather company management, some activities distributed in the five phases of PCP mentioned, so that it provides an improvement in the production process as a whole.

Resumen Este estudio tuvo como objetivo identificar y ejecutar las actividades de planificación y control de producción (PCP) en una empresa de fabricación de juegos de mesa con el objetivo de describir y analizar las fases de PCP. Para alcanzar el objetivo citado, se hizo una literatura sobre el tema elegido, y en paralelo a esto se hizo para recoger datos para la elaboración del estudio de caso. Esta colección se basó principalmente en la observación directa, realizada en fábrica de la compañía, el seguimiento de todo el proceso de producción de sus productos, así 1Jacinta

de Fátima Perreira Raposo ( e-mail: [email protected]) Universidade Federal de Pernambuco- CAA, Brasil

2Ana

Nery de Matos Costa ( e-mail: [email protected]) Universidade Federal de Campina Grande- Brasil 3André

Miranda Dourado Nunes ( e-mail: [email protected]) Universidade Federal de Campina Grande- Brasil

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como en la realización de lluvia de ideas. En continuación se determinó la necesidad de despliegue de PCP en la empresa objeto de estudio. Por lo tanto, fue posible reunir gestión de la empresa, algunas actividades distribuidas en las cinco fases del PCP mencionado, de modo que se proporciona una mejora en el proceso de producción en su conjunto.

Keywords: Production Planning and Control, Production Process, Process Improvement Palabras clave: Planificación y Control de Producción, Proceso de Producción, Mejora de Proceso

1 Introducción Actividades del PCP son desarrolladas por un departamento de apoyo a la producción dentro de la gestión de una empresa. El PCP es responsable de la coordinación y ejecución de los recursos productivos para satisfacer de la mejor manera posible a los planes establecidos en los niveles estratégico, táctico y operativo. En otras palabras, el PCP determina lo que se produce, cuánto se produce, cómo se produce, lo que se produce, quién va a producir y cuándo va a ser producido. Dentro de este contexto, el presente estudio tuvo como objetivo identificar y ejecutar las actividades de planificación y control de producción (PCP) en un pequeña empresa Paraibana, cuya jurisdicción la fabricación de juegos de mesa, con el objetivo de describir y analizar las fases PCP segundo Machline (1986): Programación; Hoja de Ruta; programación y puesta en libertad; control. Sin embargo, de acuerdo con los análisis, fue posible rastrear las actividades que se adapten a estas fases para mejorar el uso de PCP en la empresa. Para ello, se aplicó una metodología basada en una revisión de la literatura de carácter descriptivo, utilizando un marco teórico de autores clásicos que describen el PPC y Russomano Machline, y se clasifica como una investigación exploratoria porque da lugar a un estudio de caso. Los datos fueron obtenidos a través de observaciones directas sobre el piso de la fábrica, el seguimiento de todo el proceso productivo de la empresa y también la participación de una lluvia de ideas con la gestión de los mismos.

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2 Planificación y Control de Producción (PCP) Según Tubino (1997) actividades PCP se llevan a cabo en tres niveles jerárquicos de planificación y control de las actividades de producción de un sistema de producción, donde a) En el plano estratégico, donde se definen las políticas estratégicas a largo plazo del negocio, PCP participa en la formulación de la Producción Planificación Estratégica, la generación de un plan de producción b) En el plano táctico, donde se establecen planes de mediano plazo para la producción, el PCP desarrolla la planificación de la producción principal, obteniendo el Plan Maestro de Producción (PMP). c) A nivel operativo, donde los programas son preparados a corto plazo de la producción y llevó a cabo el seguimiento de los mismos, la elaboración de inventarios PCP el programa de producción, la gestión de secuenciado, emisión y liberación de órdenes de compra, fabricación y montaje, así como realiza vigilancia y control de la producción.

2.1 Programación Programación y planificación de la producción es el primer paso y que para determinar los tipos y cantidades de productos que se fabrican sobre la base de las órdenes recibidas de los clientes y / o previsiones de ventas. Es en esta etapa que el PCP realiza la gestión de inventario, emisión de órdenes de producción y programación de órdenes de producción, donde: a) En la gestión de inventario PCP administra materia prima, siempre se mantiene inventario surtido. Siempre debe estar en contacto con el área de emisión de órdenes, no para inmovilizar recursos financieros. b) La expedición de las órdenes de producción se utiliza generalmente para crear un programa de producción, gestión de tiempo, así que no se pierda la materia prima para el programa que se ha estipulado. c) En la programación de las órdenes de fabricación se realiza un análisis, es decir, en qué ocasión se realizará la operación de fabricación.

2.2 Plan de Trabajo En la segunda etapa del PCP segundo Machline (1986) es el tiempo para determinar quien hará operaciones, en las que se realizan y la unidad de tiempo de la fabricación de productos para cada operación

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2.3 Programación En esta etapa se determina que la producción comenzará y cuándo terminará, por diferencia, el tiempo que tomará. Con la finalización de esta fase, es posible determinar el patrón de tiempo de las operaciones y de este modo establecer un control de tiempo y aun así asegurar el servicio al cliente final en el período de preguntas de manera óptima.

2.4 Aplicación Según Russomano (1979), en sistemas de PPC más complejo, la liberación o el paso de las órdenes de fabricación se encarga de todos los trámites para hacer: la eliminación de almacén de materia prima, contando partes, traslado y entrega de las piezas producidas etc. Es por esta fase de la aplicación: a) Verifique la disponibilidad de materiales, herramientas e instrucciones técnicas para las órdenes de fabricación para ser iniciado, y ponerlos a disposición de los trabajadores; b) La decisión sobre la secuencia de procesamiento de órdenes de fabricación c) la distribución ordenada de los componentes de las vías de los pedidos y de fabricación; d) La recopilación de datos para el control.

2.5 Control La quinta fase se corresponde con el control de la producción, que en realidad se debe aplicar desde la primera fase. Es responsable de la supervisión de todos los aspectos de la producción, con vistas a garantizar que los planes sean implementados, pero que está debidamente modificada si es necesario Seguimiento y control de la producción se hace una recopilación y registro de datos sobre el empleo y el consumo de maquinaria, hombres y material, y los tiempos de operación. Esta información debe estar disponible tan pronto como el programa de producción se libera, lo que acelera la identificación de las desviaciones entre planeadas y ejecutadas.

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3 La Empresa El objeto social del estudio de caso es el de Fox Sports dedicada a la fabricación, venta y distribución de juegos de mesa, en la ciudad de Campina Grande, Paraíba. Fue creado en 1993 con un inicio de la producción de juegos de mesa destinados a arrendamiento.En el año 2012, la dirección de la empresa decidió trabajar sólo en el negocio de la venta y distribución de sus productos, dejando a la ubicación de las mesas en el exterior de sus objetivos. Desde entonces, Fox Sports está conquistando el mercado, la compañía ha tratado de mejorar su gestión y estrategia y la búsqueda de satisfacer mejor la demanda. De acuerdo con la caracterización adoptado en esta investigación, una microempresa se define como tener nueve empleados, cinco trabajadores en la línea de producción, más carga / supervisor, quien es responsable de la gestión de producción, un auxiliar administrativo, un vendedor de las ventas al por menor y también tenemos el propietario quien asume el papel de director general. Los productos fabricados por la empresa son: Billar, Mesa de ping pong (tenis de mesa); mesa de futbolín (Toto), Mesa y / o la bandeja botón de fútbol, mesa de dominó, mesa de ajedrez, dama escritorio, tabla tarjetas y accesorios para juegos como el cepillo de piscina, pelotas sínico, taqueiras, redinhas, etc.

3.1 Proceso de Producción El proceso de producción de la empresa es la de recibir la solicitud, recibirá patria prensa (MP) y almacenarlo, orden de producción cuestión y luego sigue las operaciones realizadas en el planta de producción: Cortar la materia prima, partes del arnés; Llevar a cabo una con salida y llegada en el monte paralelo / enmarcar algunas piezas del proceso de los productos; Pintar las piezas enmarcadas; Realizar un acabado final y ensamblar el producto final; Colocar el producto sobre la cicatrización, o esperar hasta que esté listo para empacar: empaquete y el producto, sino que enviemos. Los procesos de recepción de la solicitud, la recepción de materias primas (MP), tienda de MP y POS cuestión son funciones del sector administrativo de la empresa, de forma más directa y general director general a cargo de la producción, las operaciones ya cortadas, equipar y finales / home montaje son realiza en compañía de carpintería sector, la operación de pintura en una industria que lleva el mismo nombre, las operaciones terminar / ensamblar curado final, el embalaje y el envío se realizan en el sector de montaje y acabado.

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4 PCP en la empresa

4.1 Diagnóstico General Según el estudio identificaron que la compañía no utiliza la herramienta de planificación de la producción y de control - PCP en su proceso de producción, y no tiene conocimiento de tal herramienta. Aún así, fue posible verificar las fases del PCP que se celebra en su actividad, aun de manera informal. En la primera fase de la programación de PCP, se encontró que la producción de la carga constantemente global determinado que tipos de productos y cantidades de los mismos se han fabricado en un período determinado, basándose en las anteriores solicitudes de los clientes, sin embargo, no se ha utilizado para cualquier registro, o hecho previsión adecuada. Además, la acción fue suministrada de acuerdo con esta estimación informal de la demanda. Otro problema identificado que deben ser parte de esta primera fase de PCP, fue la falta de normalización de los productos, es decir, la empresa ofrece una variedad de productos sin clasificación, así, no tiene las mediciones de partes de productos a fabricar, haciendo de este trabajar bajo la responsabilidad y experiencia de sus trabajadores. La producción guion (segunda fase del PCP) se determinó diariamente. Con el pedido del cliente en la mano, se determinó que los trabajadores se encargarían de cada producto. El proceso de producción no funcionaría en una línea continua, cada trabajador es responsable de un producto. Para un guion de producción produce adecuadamente las necesidades de negocio de las máquinas y herramientas que se preparan y se realiza el mantenimiento necesario. Por lo tanto, se concluyó que la empresa no cuenta con un plan para el mantenimiento de las máquinas, sino una especie de mantenimiento correctivo, es decir, reparar rompió. Para la tercera fase de PCP, se observó que la administración de la compañía no tiene datos sobre los tiempos de producción de cada producto, de modo que no hay tiempo establecido programación estándar de producción, sólo para saber cómo muchos productos, por ejemplo, mesas de ping pong que la compañía podría producir en un día o una semana. En la cuarta etapa, la liberación, se observó que hay una persona responsable de llevar a cabo las actividades de esta fase como: liberación de materiales del almacén, recepción de materias primas y llevar a cabo el recuento de los productos fabricados en el final de cada día. Finalmente en la última fase, el control, se sabe que no hay forma en que la empresa lo hace porque su herramienta de administración hace uso de PCP, y ha establecido un responsable para el control del sistema de producción mismo. Sin embargo, la empresa puede cumplir con la demanda de forma proactiva. 1065


4.2 Programación y Planificación de la Producción Para la primera fase de PCP, se estableció primero para estandarizar los productos de la compañía. Los productos se clasifican en categorías y líneas. Después de eso, con la ayuda de dos carpinteros (trabajadores) empresa se estableció medidas para cada producto y está disponible en formato de tabla en la hoja de la planta. Por lo tanto, se determinó que el general a cargo de la producción será responsable junto con el director general para la aplicación de la PCP. Por lo tanto, estaba disponible en hoja de cálculo de Excel para el control de los pedidos del cliente y a través de él, será posible calcular una estimación de la demanda futura en meses. Con los datos de previsión de la demanda será posible mejor compañía de gestión de inventario. Sin embargo, también hizo un control de inventario de hoja de cálculo de materias primas y almacén de piezas, por lo que el administrador de la hoja de trabajo para alimentar la hoja que indica la cantidad de material que va a salir todos los días a producir a finales del mes sabrá cuánto material se deja en acciones y cuánto se gastó en la producción, mientras que también ayuda la gestión financiera de la empresa.

4.3 Plan de Trabajo En la fase 2, la producción de guion, negó que el sistema de producción de la empresa tiene características de un proceso de producción continua, es decir, ese tipo de producción con grandes volúmenes y variedad bajo de secuencia lineal, productos estandarizados y los pasos de producción en una secuencia programado un trabajo a otro. Sin embargo, la compañía trabajó aparato de unión por la colocación de cada uno responsable de un producto, es decir, cada uno realizado con un aparato de corte diferentes actividades y montaje inicial, por lo tanto, los productos de pintura y luego seguido para el montaje final y envasado más colaborador en cada sector. En esta lógica de producción hubo una secuencia de actividades en una línea continua, como también se dio cuenta de la pérdida de tiempo en las operaciones y retrasos en las actividades posteriores en la pintura y la industria assembly \ meta. En este contexto, se propuso que se divide y reubicación de las actividades entre todos los operadores, por lo que el proceso de producción más ágil y continuo. Las actividades se dividieron de la siguiente manera: Un carpintero realizar las actividades de corte y el aparejo, la otra partes de recepción equipado carpintero realiza el montaje inicial, un ayudante de los dos carpinteros realiza ajustes menores de las partes y ayuda en el manejo de máquinas de materias primas y los otros dos trabajadores de la empresa en la fábrica recibir las piezas montadas en la industria se divide entre la pintura y lijado actividades, pasar masiva y barniz y pintura, ya

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que las piezas se secan uno o dos empleados se desplazan Asamblea \ acabado y empaquetado. La compañía fabricó antes del cambio de dos mesas de ping pongo por día, con la nueva distribución de las actividades productivas que se duplicó así a obtener una mayor agilidad en la fabricación de otros productos principalmente en la piscina (producto que requiere más tiempo de producción).

4.4 Programación Para la fase de planificación se determinó los requisitos de tiempo de los tiempos de producción de cada producto en cada una de las líneas de producción (aparato de corte, mecanizado / montaje inicial de la pintura de acabado / montaje final y el paquete de curación). El momento fue hecho para algunos de los productos disponibles y de gestión de datos debido al cálculo del tiempo de producción. Debajo de los datos correspondientes al tiempo de producción de los productos que la empresa fabrica Con estos datos en la mano será más fácil para la producción de programas, así como controlar la misma.

4.5 Aplicación Para su publicación fase se incrementó sólo por el uso de hojas de cálculo para un mayor control, así como la participación de la general a cargo de las actividades productivas relevantes para esta fase.

4.6 Control de la Producción Para el control de fase se determinó que este cargo se llevará a cabo por el gerente general y general de la empresa, así como por los propios trabajadores, ya que están directamente vinculados a la producción. El control se realizará durante todas las fases del PCP discutidos previamente, es decir, el control de la previsión de la demanda, gestión de inventario, la calidad de los productos elaborados en la programación establecida y se reunió, entre otras observaciones que hacer constantemente. También puede incluir la necesidad de implementar un plan de mantenimiento de maquinaria y equipo. Para ello, la compañía ha lanzado un pequeño marco (que puede ser modificado según sea necesario), a las máquinas y equipos que requie-

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ren mantenimiento constante, las actividades que se deben hacer, plazo y responsables de cada

5 Consideraciones finales Al final del estudio se puede concluir que la empresa (Fox Sports) no haga uso de la herramienta PCP, se justifica por el desacuerdo o falta de interés por parte de su gobierno. A pesar de ello, la empresa puede cubrir su demanda, pero no obtuvo ninguna perspectiva de mejora de su proceso de producción. Así, a través del estudio de caso fue posible romper con la cultura de la gestión conservadora de esta empresa y mostrar la importancia de esta herramienta de gestión para su negocio como un todo. La empresa abrió sus puertas para la investigación a desarrollar, y por medio de bibliografías, y una colección de datos consistentes, fue posible no sólo para identificar las fases del PCP en el proceso de producción de la empresa, sino también distribuir estas actividades fases de contribuir a la mejora sistema de producción continua de la empresa. Sin embargo, es claro que dentro de una empresa / organización, un sistema de producción debe funcionar de forma continua y el PCP se preocupa por esto, desde la producción hasta el consumidor final. Se concluye entonces, que el uso adecuado de los PCP hace que la empresa funcione de manera más óptima, busca la mejora continua y proporciona mayores procesos de seguridad y por lo tanto para el consumidor final. Finalmente, se espera que la gestión de la empresa poner en práctica las actividades asignadas fases de PCP y se muestra en este estudio de caso .

6 Referencias Gil, Antônio Carlos, (1987), Métodos e Técnicas de Pesquisa Social, Atlas, São Paulo MACHLINE, Claude et al. Manual de administração da produção. V.1 7. Ed. Rio de Janeiro; Fundação Getúlio Vargas, 1984. Machline, Claude et al. Manual de Administração da Produção . Rio de Janeiro: Ed. da FGV, 1986, vol. 2. Cap. VI, pp. 247-269. Russomano, Vitor Henrique. Planejamento e Acompanhamento da Produção. São Paulo: Ed. Pioneira, 1979. Cap. 3, pp. 37-47. Tubino, Dalvio Ferrari. Manual de Planejamento e Controle da Produção. São Paulo: Atlas, 1987. Cap. 1, pp. 23-32. Tubino, D. F. Manual de planejamento e controle da produção. 2. Edição. São Paulo: Atlas, 2000. Zacarelli, Sérgio Baptista. Programação e Controle da Produção. São Paulo: Pioneira, 1987. Cap. 1 e 2, pp. 21-34.

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SP-04 Calidad y Gestión del Producto

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Las Empresas de Servicios Energéticos (ESE) en España y su contribución al desarrollo de las Ciudades Inteligentes (Smart Cities) Energy Service Companies (ESCO) in Spain and its contribution to Smart Cities development Morcillo Bellido J1, Prida Romero B2 Abstract This study analyze current trend towards more efficient and livable cities development which are being recognized as “Smart Cities” and new collaborative models start up and development - within those cities - between organizations involved on integral energy management projects, as key factor for higher efficiency

Resumen: El estudio analiza la tendencia actual hacía el desarrollo de ciudades más eficientes y habitables que están siendo reconocidas como “Ciudades Inteligentes (Smart Cities) así como la formación y desarrollo - dentro de ellas - de nuevos modelos de colaboración entre organizaciones involucradas en proyectos para la gestión integral de la energía, como factor clave para una mayor eficiencia.

Keywords: Smart Cities, Energy Efficiency Companies, ESCO, Collaborative Relationship, Services Management Palabras claves: Ciudades Inteligentes, Empresa Servicios Energéticos, ESE, Relaciones De Colaboración, Gestión De Servicios

1Jesús

Morcillo Bellido ( e-mail: [email protected]) Escuela Politécnica Superior. Área de Ingeniería de Organización. Universidad Carlos III de Madrid. Avenida de la Universidad nº 30, 28911 Leganés (Madrid) 2Bernardo

Prida Romero ( e-mail: [email protected]) Escuela Politécnica Superior. Área de Ingeniería de Organización. Universidad Carlos III de Madrid. Avenida de la Universidad nº 30, 28911 Leganés (Madrid)

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1 Introducción El siglo XXI ha supuesto la consolidación de la tendencia hacía la concentración de los habitantes del planeta en las ciudades. La mitad de la población mundial habita en las ciudades y a modo de ejemplo, se estima que sólo en China unos 350 millones de personas emigrarán de las áreas rurales a las mismas en los próximos 20 años, lo que supone una cifra superior a la población actual de los Estados Unidos. Concretamente en la Unión Europea (UE), durante las últimas décadas del siglo XX, se ha pasado de una situación en la que 50 por ciento de la población residía en ciudades en 1950, a que sea más del 77 por ciento en el año 2010, con una estimación del 85 por ciento en el año 2050 (Caragliu et al. 2011). Por otra parte, en las ciudades se consumen más de las tres cuartas partes de la energía mundial y en ellas se sitúan las principales áreas de desarrollo económico del planeta. A partir de esta situación, han surgido muchas iniciativas que, aunque un tanto dispersas, están todas ellas relacionadas con la calidad y la eficiencia en la gestión de los servicios que las personas y las empresas reciben en el entorno de las ciudades. En este estudio se desarrollará el concepto de “Smart Cities” y se analizará, a modo de ejemplo, una de las prácticas que está ganando importancia rápidamente: la aparición de nuevas formas de relaciones de colaboración entre organizaciones, con el fin de optimizar la gestión de la energía.

2 Metodología de la Investigación Para llevar a cabo esta investigación de prospectiva, en un área aún poco conocida y desarrollada, se han utilizado principalmente métodos de investigación cualitativa (entrevistas y estudio de buenas prácticas), que autores como Gummeson (1991) Eisenhardt (1989) y Rialp (1998) aconsejan como la adecuada para la prospección sobre aspectos innovadores en gestión empresarial. La información se ha obtenido principalmente a través de:  Información publicada en revistas especializadas en temas de sostenibilidad medio ambiental, eficiencia energética y desarrollo de estrategias de gestión pública-privada  Entrevistas en profundidad con altos responsables corporativos de organizaciones estratégicamente orientadas a la eficiencia energética de Endesa (España), Telvent (España) y Philips (Holanda y España)  Identificación y análisis de “buenas prácticas” consideradas como referencias, obtenidas con información facilitada por los responsables de organizaciones innovadoras en este ámbito, que son miembros de la Asociación Nacional de Empresas de Eficiencia Energética (ANESE) 1072


3 El concepto de Smart Cities El término de Smart City se ha utilizado con frecuencia en los últimos años para denominar proyectos relacionados con la mejora de las infraestructuras de comunicaciones y tecnologías de la información en las ciudades. La relación entre el desarrollo de las redes de comunicaciones y los indicadores de crecimiento económico ha sido estudiada, desde hace más de una década, por autores como Roller y Wavermann (2001). Otros autores enfatizan la importancia del papel del capital humano y la educación como palancas para el desarrollo de las ciudades (Glaeser y Berry, 2005/2006). A continuación se presentan diferentes estudios que caracterizan las Smart Cities Tabla1: Caracterización de las Smart Cities. 1. Utilización de infraestructuras de redes para mejorar los servicios, la economía y la gestión pública.

Hollands, 2008

2. Énfasis en el enfoque de desarrollo urbano de los negocios, con la creación de ciudades atractivas y agradables que sean capaces de atraer nuevos negocios

Holland, 2008

3. Enfoque al rol de la alta tecnología en la ciudad con la atracción de industrias de alto nivel tecnológico, creando entornos altamente sofisticados capaces de atraer a empresas y personas

Florida, 2002, Glaeser, 2005

4. Atención al desarrollo del capital relacional y social como base del desarrollo de la ciudad

Cohen y Levinthal,1990

5. Una Smart City será un lugar donde la comunidad aprende e innova

Abreu et al., 2008

6. Las personas usan la tecnología para mejorar su calidad de vida 7. La sostenibilidad social, medioambiental y económica son el mayor componente de la estrategia a largo plazo de la Smart City

Shapiro, 2006

Nijkamp, 2008, Hollands, 2008

Coe, et al., 2001 Caragliu y Nijkamp, 2011 Caragliu. et al, 2011

Fuente: elaboración propia

Entre todas las aportaciones, cabe destacar a Caragliu et al (2011), que define como “ciudad inteligente” a aquella que invierte en capital humano y social, administrando eficaz y eficientemente sus servicios públicos (como transporte, red de comunicaciones, etc) y soporta un crecimiento económico equilibrado a través del uso correcto y eficiente de los recursos, tanto en el ámbito de las administraciones públicas como de las entidades privadas. Cabe destacar que un número creciente de ciudades quieren ser reconocidas como Smart Cities, por lo que resulta preciso establecer criterios de valoración que permita reconocerlas como tales.

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Una de las clasificaciones más aceptada fue desarrollada por Giffinger y Gudrun (2010), que proponen los criterios indicados a continuación. Tabla 2: Criterios para la evaluación de las Smart Cities. Fuente: basado en Giffinger y Gudrun, 2010 COMPETITIVIDAD

PERSONAS ( capital humano)

Innovación, productividad y flexibilidad labor

Nivel de cualificación, participación en la vida pública y formación

PARTICIPACIÓN

TRANSP. Y COMUNICAC.

Participación política, servicios públicos y foros de participación

Accesibilidad, infraestructuras, transporte público, etc

MEDIO AMBIENTE

CALIDAD DE VIDA

Eficiencia energética, nivel de contaminación, tratamiento de residuos

Nivel de atención sanitaria, educación y calidad de vivienda

Desde principios del siglo XXI, los proyectos relacionados con el objetivo de las ciudades de conseguir ser clasificadas como “inteligentes” han surgido en diferentes partes del mundo y España no es una excepción. Entre los proyectos más representativos destacan los indicados en la Tabla 3. Tabla 3: Relación de proyectos relevantes de Smart Cities. Fuente: Elaboración propia, en base a información del Instituto para la Diversificación y Ahorro de la Energía (IDAE) País

Año

Objetivos

Japón

1997

Objetivos de reducción entre el 50-70% de la energía en 2050

Amsterdam (Holanda)

2002

40% de reducción de CO2 en 2025 vs 1990

Abu Dhabi (UAE)

2006

Ahorro de 30% electricidad en áreas universitarias

Ohio (USA)

2007

Proyecto ahorro 10% en electricidad

Málaga (España)

2009

20% de ahorro energético. Uso de fuentes renovables, modelos de micro gestión y vehículo eléctrico

Singapur

2009

Piloto de redes inteligentes (Smart grids)

Songdo (Corea del Sur)

2009

Nueva ciudad planificada para un uso eficiente de los recursos. Cogeneración central para la ciudad (100% electricidad). Reciclaje del 75% de los residuos de la construcción

Valladolid y Palencia (España)

2010

Incluye áreas de energía, gestión de residuos y transporte, entre otras

Paredes (Portugal)

2011

Nuevo proyecto para la construcción de una ciudad muy eficiente y alto nivel de reciclaje

Proyecto OutSmart

2011

Proyecto de la Unión Europea. Incluye: gestión de residuos, agua, transporte e iluminación

(Santander (España) y otras)

25% de reducción de energía en 2025 vs 1990

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Durante estos años el desarrollo de los proyectos era más consecuencia de las iniciativas locales que de una estrategia coordinada. Sin embargo, la Comisión Europea en su informe Smart Cities: European Innovation Partnership de julio de 2012, establece tres áreas claves (gestión eficiente de la energía, transporte y sistemas de información/comunicaciones) y pretende que estas prácticas sean no solo consecuencia de una serie de proyectos aislados, sino parte de una estrategia de gestión eficiente en las ciudades de la UE. Así, la forma en la que las ciudades manejan la energía es un pilar clave para que sean realmente “Smart” dentro del capítulo “medio ambiente”, según se indica la Tabla 2. Para la Comisión Europea, es parte de su estrategia de competitividad.

4 La Energía como Factor de Competitividad en las Ciudades y las Empresas de Servicios Energéticos Como se ha comentado, las personas que habitan y desarrollan sus actividades en las ciudades consumen el 75% de la energía mundial y dicho consumo no hace sino acelerarse. El rápido crecimiento del consumo de energía en los países emergentes es un problema particularmente grave para los países, cómo España, con una fuerte dependencia de fuentes exteriores de suministro A modo de ejemplo, según un informe publicado recientemente por McKinsey (Mohr, 2012), la energía representa un 45% del coste de producción para los fabricantes de televisiones LCD por lo que al aumentar su precio estos deben de volver a definir sus procesos operacionales, incluyendo el diseño del producto, de forma que el impacto en el coste del producto no deteriore gravemente su margen. Otro ejemplo, en este caso de una experiencia prometedora, es el relacionado con la industria de embalajes para artículos de consumo en Estados Unidos, que ha reducido a la mitad el consumo de energía en tres años (Dobbs, 2012) a través de la colaboración entre los diferentes miembros de la cadena de suministro en la búsqueda de materiales, tecnologías y formas de trabajar más eficientes. Es precisamente en este ámbito de colaboración en la Cadena de Suministro donde se enmarca la oportunidad para aquella compañía que sea capaz de gestionar eficientemente los procesos energéticos de sus clientes. Así en los últimos años han surgido empresas que aceptan acuerdos con otras organizaciones con el objetivo de optimizar la gestión total o parcial de su energía, garantizando el nivel de servicio acordado, con un ahorro de costes integral - respecto a la situación inicial- superior al que el cliente hubiera podido conseguir aisladamente. A estas compañías se las denomina “Empresa de Servicios Energéticos (ESE)” Para lograr los objetivos de eficiencia, la Empresa de Servicios Energéticos invierte en tecnologías más eficientes, las instala, las financia en algunos casos y las mantiene durante el número de años incluidos en el contrato, buscando la máxima 1075


eficiencia en los costes y garantizando un nivel de servicio acordado con el cliente en el proyecto concreto (Vine, 2005). No cabe duda que, como señala Hartley (2005), este tipo de prácticas constituyen un tipo de “innovación colaborativa horizontal”, ya que esta nueva forma de trabajar busca mejorar simultáneamente tanto el coste como el servicio a través de la integración en el manejo de la información, el uso de tecnologías y en el modelo de colaboración.

5 Servicios Ofrecidos por las Empresas de Servicios Energéticos en España En España, el Real Decreto Ley 67-2010 regula las empresas tipo ESE estableciendo las normas y las condiciones para su operación. Hasta esta fecha habían surgido algunos proyectos promovidos principalmente por las Agencias de la Energía de las Comunidades Autónomas en su afán de desarrollar proyectos piloto, que mostrasen que el concepto de Empresa de Servicios Energéticos (ESE) era factible como modelo de organización para llevar a cabo los proyectos de eficiencia energética. Sin embargo, cabe señalar que si bien este modelo empresarial basado en la colaboración entre organizaciones es algo relativamente nuevo, su origen en España podría remontarse a finales de la década de los 80 del pasado siglo, cuando aún sin reglamentación legal específica, comienzan los primeros proyectos en torno a la oportunidad de la cogeneración energética, según se muestra en la Fig 1.

2006 2014 • Proye ctos cogen eración

1985 - 2010

• Proye ctos climati zación • Proye ctos de ilumina ción

2015 en adelante (estimació n) • Genera lización de los modelo s ESE en España

Fig 1 Evolución de los modelos de gestión energética (ESE) en España. Elaboración propia a partir de expertos

En general, la Empresa de Servicios Energético factura sus servicios en función de los rendimientos, es decir, en función de la eficiencia energética conseguida. En este caso, hablar de “rendimiento” es una medida más adecuada para establecer el éxito de la gestión, puesto que el “ahorro” también depende de la propia activi1076


dad del cliente o incluso de factores exógenos como la climatología. De los casos estudiados en nuestra investigación, los servicios ofrecidos en España incluyen iluminación, climatización, operaciones de equipos (máquinas, ordenadores,…) y cogeneración. Estos proyectos se han extendido en todo tipo de ámbitos, según se muestra en la Fig.2. Oficinas

Hospitales

Hoteles

Universidades Alumbrado urbano Centros comerciales

• iluminación (20%), equipos (35%) y climatización (40%) • potencial de ahorro: 2540% • Iluminación (10%) y climatización (36%) • Potencial: 20-40% • ACS (30%), climatización (30%) e iluminación (12%) • Potencial de ahorro: 1540% • Áreas: iluminación (20%) climatización(65%) • potencial de ahorro: 2535% • Iluminación (100%) • Potencial: 40-60% • Iluminación (25%) y climatización (48%) • Potencial de ahorro: 2040%

Fig 2 Principales actuaciones de ESE en el sector privado. Fuente: Asociación Española de Agencias de Energía y Asociación Nacional de Empresas de Servicios Energéticos

En esta figura se indica los objetivos de ahorro potencial, estimados - mínimo y máximos previsibles - a partir de la comparación entre la situación actual de las instalaciones y los niveles conseguibles con la aplicación de i) integración de procesos integrados, como proponen las empresas de servicios energéticos, incluyendo cambios en la forma de gestionar la energía ii) utilización de nuevas tecnologías. Es de destacar que los potenciales ahorros van del 15% al 40%, dependiendo tanto de la situación de partida, como de las acciones de mejora aplicables. Estas últimas dependerán del periodo de recuperación de la inversión, lo que hace que a medida que crece el precio de la energía, los ahorros potenciales aumentan haciendo que los proyectos tengan menor periodo de recuperación y sean más atractivos. En la actualidad, los proyectos más frecuentes se realizan en alumbrado público, hospitales y centros comerciales. También existen varios proyectos en organismos de la Administración Central y de las Comunidades Autónomas, que en cierta medida buscan ser los pilotos para su extensión generalizada al sector público a partir del uso de contratos de colaboración público privada.

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6 Conclusiones Del análisis realizado, se puede inferir que los modelos de colaboración en la gestión de la energía son una buena herramienta en la consecución de los objetivos de eficiencia energética. El desarrollo en España de los proyectos de colaboración de gestión energética está siendo gradual. Sin embargo, las áreas de aplicación son amplias y existen importantes ahorros potenciales. En las instituciones públicas – como ayuntamientos - la necesidad de ser muy eficientes en la gestión de la energía se ha convertido en un tema prioritario y este tipo de acuerdos con empresas capaces de gestionarla y conseguir ahorrar entre un 20 y un 40 por ciento del consumo es crítico en un momento de reducción de ingresos. En el sector privado, aquellas empresas que se distinguen por sus buenas prácticas en la gestión de procesos, están comenzando a darse cuenta que las mejoras en sus procesos operacionales (diseño, fabricación, transporte, etc) pueden tener un límite, por lo que algunas de ellas comienzan a aplicar estas prácticas a otros recursos no tan relevantes hasta ahora - como la energía- a través proyectos de colaboración en la cadena de suministro. El interés que muestra la UE en el desarrollo de las Smart Cities, puede constituir una importante palanca para acelerar la velocidad de implantación de proyectos de Smart Cities y como consecuencia, de eficiencia energética. De hecho, sería muy difícil llegar a ser una Smart City sin conseguir ahorros significativos en esta área, los cuales son más alcanzables con la colaboración de Empresas de Servicios Energéticos. Todo ello puede significar, en breve, importantes mejoras en términos de eficiencia energética que podría ser observable y medible, tanto a través de un mayor nivel de competitividad (reducción de costes, mejora medio ambiental, etc), como por unos servicios a los ciudadanos más eficientes y baratos (caso de instituciones públicas).

7 Referencias Abreu, M. et al. (2008) Absorptive capacity and regional patters of innovation. Research Report 8/11 London: Department of Innovation, Universities and Skills Asociación Española de Agencias de la Energía (2011) Manual de Promoción de ESE. Madrid Asociación de Empresas de Servicios Energéticos (2012) Presentación Asociación. Madrid Bertoldi, P. et al. (2006) Energy service companies in European Countries: current status and strategy to foster their development. Energy Policy 34: 1818-1832 Caragliu, C. et al. (2011) Smart Cities in Europe. Journal of Urban Technology, vol. 18, nº 2, April 2011: 65-82 Coe, G. et al (2001) E-Governance and smart communities: a social learning challenge, Social Science Quarterly 35:1 Cohen, W. y Levinthal, D.(1990) Absorptive capacity: A new perspective on learning and innovation, Administrative Science Quarterly 35:1: 80-93

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Dobbs, R. et al. (2012) Mobilizing for a resource revolution. McKinsey Quarterly, Sustainability & Resource Productivity Practice, January 2012: 4-12 Eisenhardt, K.M. (1989) Building theories from case research. Academy of Management Review, vol. 14, nº 4: 532-550. European Commision (2012). Smart Cities and communities- European innovation partnership Florida, R. (2002) Bohemia and Economic Geography. Journal of Economic Geography, 2: 5571 Giffinder, R. y Gudrun, H. (2010) Smart Cities: an effective instrument for the positioning of cities. Architecture, City and Environment, 2010: 7-25 Glaeser, E.L. (2005) A review of Richards Florida´s: the rise of the creative class, Regional Science and Urban Economics 35:5: 593-596 Glaeser, E.L. y Berry, C. R. (2006) Why are smart places getting smarter, Taubman Center Policy Brief 2006-2. Cambridge, M.A.: John F. Kennedy School of Government Gummesson, E. (1991) Qualitative methods in management research. London: SAGE Publications Ltd. Hartley, J. (2005) Innovation in governance and public services: past and present. Public Money and Management, 25(19): 27-34 Hollands, J. R. (2008) Will the real smart city please stand up. Intelligent, Progressive, or Entrepreneurial?”, City 12:3: 303-320 IDAE (2012) Mapa tecnológico Ciudades Inteligentes. Observatorio Tecnológico de Energía. Madrid Mohr, S. et al. (2012) Manufacturing resource productivity. McKinsey Quarterly, June 2012: 2025 Nijkamp, P (2010) E Pluribus unum, Region Direct 2:3: 56-65 Roller, L-H. y Wavermann, L. (2001) Telecommunications Infrastructure and economic development: A Simultaneous Approach, American Economic Review: 91:4 Shapiro, J. M. (2008) Smart Cities: quality of life, productivity, and growth effects of human capital, The Review of Economics and Statistics: 304-335 Vine, E. (2005) An international survey of energy service company (ESCO) industry, Energy Policy 33: 691-704

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El Análisis del Ciclo de Vida en España. Temas de Investigación Principales y Agentes Clave LCA in Spain. Main research topics and key agents. Basañez Llantada A1, Martínez de Alegría Mancisidor I2, Insunza Aranzeta G3, González Laskibar X4 Abstract Since 2001, when the European Union published its Green Paper on Integrated Product Policy, LCA has received a further institutional boost, given that the European Commission itself has singled out LCA as one of the pillars for the development of this policy. Nevertheless, little is still known about this tool’s effective deployment in Spanish businesses or about the level of knowledge they have of it. This paper seeks to provide a starting point for subsequently addressing these unresolved issues. Through an analysis of the scientific papers published by Spanish authors in the main international journals on the matter, the aim is to provide a snapshot of the Spanish scenario in research into LCA.

Resumen Desde la publicación en 2001 por parte de la Unión Europea del Libro Verde sobre la Política de Productos Integrada (PPI), el ACV ha recibido además un impulso extra institucional, debido a que la propia Comisión Europea identifica el ACV como uno de los pilares de cara a desarrollar dicha política. Sin embargo, poco se sabe aun de la implantación real que esta herramienta tiene en las empre-

1

Aitor Basañez Llantada (e-mail: [email protected]) Dpto. de Organización de Empresas. Escuela Técnica Superior de Ingenieria de Bilbao (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao.

2 Itziar Martínez de Alegría Mancisidor Dpto. de Organización de Empresas. Escuela Técnica Superior de Ingenieria de Bilbao (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao. 3

Gaizka Insunza Aranzeta Dpto. de Organización de Empresas. Escuela Técnica Superior de Ingenieria de Bilbao (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao. 4

Xabier González Laskibar Dpto. de Organización de Empresas. Escuela Técnica Superior de Ingenieria de Bilbao (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao.

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sas españolas o sobre el nivel de conocimiento que de ella se tiene en las mismas. Este trabajo quiere aportar un punto de partida que permita abordar posteriormente estas incógnitas. A través del análisis de los artículos científicos publicados por autores españoles en las principales revistas internacionales, se pretende realizar una radiografía del panorama investigador español sobre el ACV.

Keywords: Life Cycle Assessment (LCA), Life Cycle Management (LCM) Sustainability, Integrated Product Policy (IPP) Palabras clave: Análisis del Ciclo de Vida (ACV); Gestión del Ciclo de Vida (LCM); Sostenibilidad, Política de Productos Integrada (PPI)

1 Introducción En un contexto como el actual, de gran preocupación por el binomio ahorro energético-cambio climático, es innegable el interés que todo lo relacionado con el medioambiente suscita entre consumidores, fabricantes y legisladores. Por una parte las empresas necesitan herramientas que les ayuden a mejorar el desempeño medioambiental de sus procesos y productos y por su parte los organismos públicos necesitan criterios fiables y objetivos de cara a establecer políticas públicas que impulsen la sostenibilidad. En este sentido, son diversos los autores que han identificado el ACV como una herramienta de apoyo al proceso de toma de decisiones para gobiernos, empresas, organizaciones de consumidores y grupos ambientales (Wenzel et al., 1997; Krozer et al., 1998; Field et al., 1999). Los ámbitos de decisión en los que el ACV puede servir de ayuda incluyen desde la gestión general de empresas e instituciones y el análisis de alternativas para políticas públicas, hasta la elección en fase de diseño de características específicas de productos y procesos (Tan et al., 2008). Ahora bien, ¿en qué medida aplican las empresas españolas esta metodología? Antes de contestar a esta pregunta cabría preguntarse ¿es el ACV suficientemente conocido por las empresas españolas? Este trabajo pretende arrojar algo de luz sobre estos interrogantes.

2 Objetivos El objetivo principal de este trabajo es conocer la situación en España de la investigación sobre el ACV a través del estudio de las aportaciones que los autores españoles han realizado al desarrollo de esta metodología. Mediante el análisis de los artículos científicos publicados en las revistas internacionales claves sobre el tema, se pretende descubrir cuál ha sido la evolución en 1081


el tiempo del número de artículos publicados por investigadores españoles y conocer las áreas de investigación más desarrolladas en dichos artículos. Por último, se pretende conocer también algunas de las características de los autores españoles, como las empresas o instituciones a las que pertenecen.

3 Metodología de la Investigación Para lograr los objetivos definidos se ha realizado la búsqueda, para su posterior análisis, de aquellos artículos que incluyen las frases "evaluación del ciclo de vida" o "análisis del ciclo de vida”, en su título, abstract o palabras clave, y hayan sido publicados en alguna de las publicaciones referidas en la tabla 1 durante el periodo comprendido entre los años 1995 y 2010.

4 El Análisis del Ciclo de Vida. Definición y Objeto El ACV es una metodología que intenta identificar y cuantificar los diferentes impactos ambientales potenciales, asociados a cada una de las etapas del ciclo de vida de un producto o proceso. Por ello, el ACV recibe también la denominación de Análisis de la Cuna a la Tumba. De acuerdo a la definición de la Society for Environmental Toxicology and Chemistry (SETAC), el ACV es una técnica que permite evaluar las cargas ambientales asociadas a un producto o proceso productivo (Krozer et al. 1998). Por su parte la norma ISO 14040, Gestión Ambiental. Análisis del Ciclo de Vida Principios y Estructura, lo define como “una técnica para evaluar los aspectos medioambientales y potenciales impactos asociados con un producto o proceso” (Tan et al., 2008). Un estudio de ACV implica tomar en consideración el ciclo de vida completo del producto o actividad en estudio, es decir, se deben analizar las etapas de adquisición de materias primas, procesado y manufacturado, distribución y transporte, uso, reutilización y mantenimiento, reciclado y la gestión de residuos. El ACV proporciona información útil de cara tomar decisiones dirigidas a mejorar el desempeño ambiental de sus productos y/o servicios. Así mismo, resulta de utilidad a la hora de decidir entre varias alternativas, al proporcionar información sobre los impactos ambientales de cada opción.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 1 Publicaciones seleccionadas para la realización del estudio Título de las Revistas

Factor de Impacto 2010

Primera edición

International Journal of Life cycle Assessment, IJLCA

3.148

1996

Journal of Cleaner Production, JCP

2.425

1993

Journal of industrial ecology, JIE

2.446

1997

Environmental Science and Technology, ES&T

4.827

1967

5 El ACV Elemento Clave de la Política de Productos Integrada Hoy en día, las industrias utilizan el ACV para comparar alternativas en el desarrollo de productos, en el ámbito comercial para informar sobre su desempeño ambiental, y como herramienta en el proceso de toma de decisiones sobre la gestión ambiental. Los gobiernos por su parte, lo utilizan para analizar alternativas sobre diversos sistemas sociales, como los sistemas de gestión de residuos, y como pilar de la Política de Productos Integrada en los sistemas de eco etiquetado y de compra pública verde (Hauschild et al., 2005). De hecho en Europa el ACV recibió un impulso por parte de las instituciones en febrero de 2001, cuando la Comisión Europea publicó el Libro Verde sobre la Política de Productos Integrada (PPI) (European Commission, 2003). El ACV es reconocido en el contexto de la PPI como “el mejor marco disponible en la actualidad' para evaluar los posibles impactos ambientales de los productos” (Nissinen et al., 2007). El término PPI surgió durante la década de 1990, la primera investigación sobre el tema en la UE fue un proyecto financiado por la DG XII, dentro del programa 'Medio Ambiente y Clima" (Oosterhuis et al., 1996; Rubik et al., 2002). Posteriormente otro estudio proporcionaría la siguiente definición: "La política pública que explícitamente aspira a modificar y mejorar el desempeño ambiental de los sistemas producto" (Ernst & Young/SPRU, 1998). Un estudio publicado en 2002 (Rubik et al., 2002), comparaba el desarrollo de la PPI en varios países de la UE. Dicho estudio situaba a España en el vagón de cola junto a países como Irlanda, Luxemburgo o Portugal, mientras que países como, Holanda, Dinamarca, Suecia o el Reino Unido aparecían en cabeza. Aunque no es la única herramienta para implementar la PPI, parece evidente la necesidad de que el ACV se desarrolle y sea abrazado por las empresas e instituciones españolas de cara a lograrlo.

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6 Antecedentes del ACV en España En España los primeros pasos serios en la investigación del ACV se dieron en Cataluña a principios de los años 90, de hecho, se puede afirmar que el primer evento celebrado en España en este ámbito fue el “Seminario Internacional Producte i embalatge” que tuvo lugar en Sitges en junio de 1993 (Fullana et al., 1997). En marzo de 1995 se creó la Asociación Española para la Promoción del Desarrollo del Análisis de Ciclo de Vida (APRODACV), primera asociación española dedicada en exclusiva al ACV (Doménech et al., 1996). Un hito importante para APRODACV en particular, y para el desarrollo del ACV en España en general, lo constituyó sin duda el primer taller de trabajo sobre ACV que se celebró en Barcelona bajo el nombre “LCA 2000” en noviembre de 1997, organizado por APRODACV (Ayuso et al. 1997). Durante los años siguientes, el desarrollo de actividades en el campo del ACV aumentó significativamente como lo demuestran los siguientes hechos: La publicación en 1997 del libro “Análisis de Ciclo de Vida”, primera guía práctica de aplicación del ACV en español (Fullana et al., 1997), la celebración en Madrid en mayo de 2001 del “SETAC Europe 11th Annual Meeting” y en diciembre de 2002 en Barcelona, el “X SETAC Europe LCA Case Studies Symposium”. Pero fueron sin duda las dos iniciativas que se citan a continuación, las que ayudaron a consolidar en España esta metodología: En el año 2000 se creó la Red Catalana del Ciclo de Vida que en cierta medida tomó el relevo a APRODACV. En ella, participan junto a otras instituciones públicas y privadas, la práctica totalidad de las universidades catalanas, si bien, su coordinación corre a cargo de la Universidad Autónoma de Barcelona. Poco después, en 2002, se creó la Red Temática de Análisis de Ciclo de Vida, coordinada desde la Universidad de Santiago de Compostela, con los mismos objetivos que su antecesora catalana pero de ámbito nacional. Merece la pena resaltar que sobre estas dos asociaciones recayó la responsabilidad de organizar el segundo congreso internacional sobre gestión del ciclo de vida en Barcelona en el año 2005 bajo el título “LCM 2005 Innovation by Life Cycle Mangement”.

7 Resultados Dado su carácter monográfico, no es extraño que la revista International Journal of Life Cycle Assessment haya publicado prácticamente el 70% de los artículos considerados para el estudio tal y como se muestra en la tabla 2.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 2 Distribución de artículos en el periodo 1993-2010 Revistas consideradas para el estudio

Nº de artículos

International Journal of Life cycle Assessment, IJLCA

47

Journal of Cleaner Production, JCP

10

Journal of industrial ecology, JIE

5

Environmental Science and Technology, ES&T

6

Total

68

En la figura 1 se detalla la evolución en la publicación de dichos artículos. 21

nº de Artículos 14 8 2

4 1

2

4

3

4

5

Fig. 1 Evolución en el número de artículos

La producción de los investigadores españoles en el siglo pasado se limitó a unos pocos artículos publicados en 1997 y 1998, a partir del año 2002 su número creció lentamente hasta despegar definitivamente en el año 2007. Es de suponer que los investigadores españoles se vieron animados a publicar por la celebración de los congresos ya mencionados, en Madrid en 2001 y Barcelona en 2002 y 2005. Dado que el problema del cambio climático sigue más vigente que nunca, se puede afirmar que el ACV mantendrá su interés a corto y medio plazo cuando menos. A la hora de clasificar los artículos según su temática, surgieron múltiples opciones dado que no existe ninguna normativa específica al respecto. A ello se le une el hecho de que algunos artículos abordan más de un tema, y que otros, están en la frontera entre los denominados desarrollos metodológicos y las aplicaciones industriales. Finalmente se optó por considerar las categorías de la tabla 3. Los temas más trabajados por los investigadores españoles además de los aspectos metodológicos, han sido la agricultura la pesca y la alimentación y los relacionados con el agua. Las tres categorías representan en conjunto la mitad del total de los artículos. Tras ellos, la gestión de residuos, la industria maderera y papelera, la construcción y el sector químico son los más tratados. Aunque como veremos más adelante las empresas no aparecen entre las principales agentes investigadores, la realidad del tejido empresarial español sí parece tener relación con los temas escogidos por los investigadores. No parece casualidad que sectores económicos de especial relevancia en España sean motivo de es1085


tudio por los investigadores españoles: El peso de los artículos que tratan temas relacionados con la agricultura, la pesca o la alimentación refleja la importancia que el sector primario mantiene aun hoy día en la economía española, lo mismo se puede decir de la industria forestal y papelera y en menor medida del sector textil y calzado, el sector químico, la construcción o los temas energéticos. Tabla 3 Áreas de actividad estudiadas Categorías: Áreas de Actividad

Nº de Artículos

Metodologías y otros Desarrollos

14

20,59%

Gestión Tratamiento y Uso del Agua

11

16,18%

Agricultura, Pesca, Alimentación Bebidas y Tabaco

9

13,24%

Gestión y tratamiento de Residuos (Excepto agua)

6

8,82%

Industria Forestal y Papelera

6

8,82%

Sector Químico y Plásticos

4

5,88%

Edificación y Construcción y Hormigón

4

5,88%

Transporte y Automoción

3

4,41%

Sector Textil y calzado

3

4,41%

Electricidad Generación, Transporte, Distribución y Uso

2

2,94%

Otros

6

8,82%

TOTALES

68

100%

Tal y como muestra la tabla 4 casi el 60% de los artículos son obra de autores españoles exclusivamente mientras que el resto cuenta entre sus autores al menos con algún autor de otra nacionalidad diferente. El número total de investigadores que han participado en la elaboración de los 68 artículos analizados, asciende a 166, de los cuales 101 son españoles y los 65 restantes, extranjeros. Se ha constatado que en general, los diferentes autores de un mismo artículo pertenecen también a organizaciones distintas, lo que refleja una inclinación hacia el trabajo cooperativo y en red, característica muy positiva en trabajos de investigación. En este mismo sentido, resulta también positivo que el 41% de los artículos analizados haya sido realizado por autores de diferentes nacionalidades. En cuanto a los organismos a los que pertenecen los autores, los resultados de la tabla 5 son elocuentes: Casi el 80% de los autores pertenece al mundo de la universidad, 14 trabajan en diversos organismos públicos, asociaciones sectoriales, y centros de investigación privados y públicos y sólo 7 desempeñan su actividad en el ámbito de la empresa. Aun siendo un número pequeño y por tanto poco significativo para sacar conclusiones definitivas, merece la pena analizar la tipología de dichas empresas. Las empresas que ofrecen servicios de consultoría e ingeniería medioambiental o servicios relacionados con la gestión del agua y los residuos urbanos son las más abundantes, mientras que las pocas empresas de 1086


sectores productivos o con carácter más industrial pertenecen a los sectores de automoción, energías renovables y la minería y materiales de construcción. Tabla 4 Nacionalidad de los autores Nº de artículos con autores españoles exclusivamente

40

58,82%

Nº de artículos con autores españoles e internacionales

28

41,18%

Número total de artículos

68

100%

Autores Españoles

101

61%

Autores del resto de nacionalidades

65

39%

Número total de autores

166

100%

¿Quiere esto decir que las empresas no utilizan la metodología del ACV? No necesariamente, algunos autores coinciden al señalar que los trabajos de investigación realizados en las empresas rara vez acaban siendo publicados ya que a la hora de utilizar los resultados en foros públicos se mostraban muy cautelosas (Curran MA, 1999). Por su parte, la norma ISO 14044 impone requisitos rigurosos sobre el uso publicitario de los resultados para comparación de alternativas (ISO, 2006). Tabla 5. Organismos a los que pertenecen los autores españoles Universidades

80

79,2%

Organismos y asociaciones públicas y privadas

14

13,9%

Empresas

7

6,9%

Total

101

100%

7 Conclusiones El estudio revela que la investigación en España sobre ACV discurre en paralelo a la investigación realizada a escala mundial pero con un desfase de casi diez años, mientras que el despegue mundial del ACV se produjo hacia el año 1995 (Peters GM, 2009), en España, esto no ocurre hasta el año 2002. En cuanto a los temas escogidos por los investigadores, además de los aspectos meramente metodológicos, se aprecia cierta conexión entre estos y la realidad industrial española. Sin embargo la conclusión más relevante, y preocupante, es el aparente escaso interés que el mundo empresarial demuestra de momento por el ACV. Los resultados muestran que únicamente algunas pocas empresas del ámbito de la asesoría y consultoría medioambiental están publicando sus experiencias. Aun considerando que algunas empresas que realizan estudios de ACV deciden no hacerlos públicos y que evidentemente existen muchas revistas no consideradas en este trabajo, lo cierto es que cabe suponer que el ACV no es aún muy conocido entre las em1087


presas. Algunos de los motivos podrían encontrarse en los programas académicos ya que en España el ACV no se encuentra plenamente extendida y únicamente se imparte en algunos casos especializados. Es de esperar que el interés por el ACV aumente a medida que la legislación a fin de impulsar el desarrollo sostenible, vaya incorporando la exigencia de realizar estudios de este tipo a productos y procesos. De hecho, estos estudios son ya requisito para la obtención de certificados de ecodiseño, declaraciones medioambientales y etiquetas ecológicas. Dado la positiva aceptación que algunos esquemas certificables, (calidad y medioambiente principalmente) han tenido en España (Marimón et al., 2006), cabe esperar que en este ámbito también ocurra lo mismo.

8 Referencias Ayuso S, Fullana P, Milá Ll, Rieradevall J (1997) First LCA Workshop in Spain “LCA 2000”: Preliminary Results. Int J Life Cycle Assess 2(4):250 Curran MA (1999) The status of LCA in USA. Int J Life Cycle Assess 4(3):123–124 Doménech X, Fullana P (1996) LCA association in Spain. Int J Life Cycle Assess 1(4):207 Ernst & Young/SPRU 1998. Integrated product policy. London: Study on behalf of DG Environment. European Commission, (2003) Integrated Product Policy - Building on Environmental Life Cycle Thinking. Commission of the European Communities. IPP COM(2003) 302 final. Field FR and Ehrenfeld JR (1999) Life-Cycle Analysis: The Role of Evaluation and Strategy. In: Schulze, P.C., ed. Measures of Environmental Performance and Ecosystem Condition. National Academy Press, Washington, D.C. Fullana, P., Puig, R., 1997. Análisis de Ciclo de Vida. Cuadernos de Medio Ambiente, pub. Rubes Editorial,S.L., Barcelona. Hauschild M, Jeswiet J, Alting L, (2005) From Life Cycle Assessment to Sustainable Production: Status and Perspectives. CIRP Annals - Manuf Technol 54(2):1-21 ISO 14044, 2006. International Standard. Environmental management- Life-cycle assessment Requirements and guidelines; ISO: Geneva, Switzerland. Krozer J and Vis JC (1998) How to get LCA in the right direction? J Clean Prod 6(1):53-62 Marimon F, Casadesús M, Heras I (2006) ISO 9000 and ISO 14000 standards: an international diffusion model. Int J Oper Prod Manag 26(2):141-165 Nissinen A et al. (2007) Developing benchmarks for consumer-oriented life cycle assessmentbased environmental information on products, services and consumption patterns. J Clean Prod 15(6):538-549 Oosterhuis F, Rubik F, Scholl G., 1996. Product Policy in Europe: New environmental perspectives. Kluwer Academic Publishers. AH Dordrecht, The Netherlands Peters GM (2009) Popularize or publish? Growth in Australia, Int J Life Cycle Assess 14(6):503507 Rubik F and Scholl G (2002) Integrated Product Policy (IPP) in Europe - a development model and some impressions. J Clean Prod 10(5):507-516 Tan R and Culaba A (2008) Environmental Life-Cycle Assessment: A Tool for Public and Corporate Policy Development. De la Salle University Manila (Philippines). http://www.dlsu.edu.ph/library/webliography/fpub/alvin_culaba.asp. Cited March 2012 Wenzel, H., Hauschild, M. and Alting, L. (1997). Environmental Assessment of Products. Vol. 1: Methodology, Tools and Case Studies in Product Development. Chapman & Hall.

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Un Sistema Integrado de Gestión como Elemento de Mejora Competitiva An Integrated Management System as a Competitive Improvement Fortea E1, Mikeo I2 Abstract The article then develops, recounts how a company Elevators Goian SL, identifies the need for the design, development and implementation of an integrated management system for quality, environment and risk prevention. And how identical this methodology to improve business excellence following the EFQM excellence model.

Resumen El artículo que a continuación se desarrolla, relata el modo en que una empresa Elevadores Goian S.L, identifica la necesidad de realizar el diseño, desarrollo e implantación de un sistema integrado de gestión de calidad, medio ambiente y prevención de riesgos laborales. Y cómo idéntica esta metodología para mejorar en excelencia empresarial siguiendo el modelo de excelencia EFQM.

Keywords: Systems Management, Systems Integration, Process Management. Palabras clave: Sistemas de Gestión, Integración de Sistemas, Gestión por Procesos.

1Eider

Fortea Méndez ( e-mail: [email protected]) Departamento de Mecánica y Producción Industrial. Escuela de Ingeniería. Universidad Mondragón. C/Loramendi, 4, 20500 Mondragón. 2Imanol

Mikeo Aizkorbe ( e-mail: [email protected]) Alumno en proyecto final de Grado en Ingeniería en Organización Industrial. Escuela de Ingeniería. Universidad Mondragón. C/Loramendi, 4, 20500 Mondragón.

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1 Introducción Llevamos ya años implantando en las empresas sistemas de gestión con objeto de conseguir una gestión más eficiente en el ámbito en el que se implantan. Y los resultados de tales implantaciones confirman efectivamente, la bondad de dichas actuaciones. Entrando concretamente en el ámbito de la seguridad y salud laboral, el medio ambiente y la calidad, tenemos la posibilidad de utilizar especificaciones técnicas internacionalmente reconocidas: ISO 9001:2008 de sistema de gestión de calidad (ISO 2008) e ISO 14001:2004 de sistema de gestión ambiental (ISO, 2004), y una especificación técnica reconocida y adaptada por la mayoría de las empresas para ayudarles al diseño y desarrollo de un sistema de gestión de la seguridad y salud laboral (OHSAS 18001:2007) (BSI, 2007). Como en el caso que nos ocupa, la gran mayoría de empresas (hablamos del País Vasco) tienen ya y desde hace tiempo implantado y certificado un sistema de gestión de calidad según la ISO 9001; menos son las certificadas en medio ambiente, y aún menos las certificadas en seguridad y salud laboral, aunque mantenemos unos índices altos en lo referente al resto de España en cuanto al número de certificaciones. Tal y como Aenor expresó en una nota de prensa en el año 2007, el País Vasco ocupaba el tercer lugar en el conjunto del Estado español por número de certificaciones, tanto según la norma ISO 9001 de calidad, como ISO 14001 de medio ambiente (AENOR, 2007). Una de las circunstancias de las que más se han quejado las empresas a la hora de implantar la norma de gestión de la calidad (normalmente la primera en implantarse) es la cantidad de “papeleo” que se tenía que hacer; primero para implantarla y luego para mantenerla. La exigencia de firmas requeridas, registros y documentos para todo hacía que los trabajadores fueran poco a poco “saboteando” su mantenimiento y finalmente dejara de poder gestionarse de esa manera. Se suele culpar a esta normativa de ser una moda, un factor de rigidez, una fuente de descalificación para el trabajador, un retorno al taylorismo, de no garantizar la calidad del producto, de tener un costo elevado, y de ser un factor que aumenta el papeleo y la burocracia (Casadesús y Heras, 1999). Por otra parte, si además la empresa decidía implantar también un sistema de gestión ambiental según la ISO 14001:2004, las exigencias de registros y el “papeleo” se multiplicaban y la situación se complicaba aún más si la empresa decidía certificarse también contra la OHSAS 18001:2007 de seguridad y salud laboral. Vista esta situación se comenzó a diseñar sistemas de gestión integrados que cumplieran con los requisitos de las tres normas máxime cuando las tres están predispuestas a ser integradas ya que todas están diseñadas siguiendo un ciclo de mejora continua o rueda de Deming (Deming,1989 ). Asimismo, para llevar a cabo fácilmente esta integración las propias normas comenzaron a incorporar en su parte final una tabla en la que se relacionaban los capítulos de una y otra norma (ISO 9001:2008 e ISO 14001:2004).

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Cierto es que ya existe una norma UNE 66177:2005 (AENOR, 2005) de sistemas de gestión: guía para la integración de los sistemas de gestión, sin embargo, la integración que propone de los tres sistemas de referencia se contradice con las sugerencias lógicas de integración que las normas ISO 9001:2008 e ISO 14001:2004 hacen en sus últimas ediciones. Por otra parte tenemos la NTP 576 (Norma Técnica de Prevención) (INHST, 2001) que propone las posibilidades de integración en función a la similitud de los diferentes capítulos o artículos de las normas de calidad ISO 9001:2000, ISO 14001:2004, OSHAS 18001:2007 y UNE EN 81900 EX. Esta NTP quedó obsoleta en el momento en que desapareció la UNE 81900 de sistema de gestión de prevención de riesgos laborales y la ISO 9001:2000 que se actualizó en la edición de 2008. Pero vayamos al concepto, ¿qué significa integración?. Existen numerosas definiciones en la literatura, pero por considerarla la más completa nos haremos eco de la establecida por el Grupo Mondragón cuando aún era MCC: Integración es el proceso a través del cual la organización aprende a introducir criterios y especificaciones en sus procesos de modo que satisfagan a todos sus clientes (internos, externos, institucionales, partes interesadas, etc.) de forma simultánea, ahorrando costes y esfuerzos, con un espíritu innovador, autocrítico y comprometido con la mejora continua (MCC, 2000). Por tanto, cubrir las necesidades de la empresa en su gestión, significa tener en cuenta su gestión particular, los elementos a los que les da más o menos importancia, identificar y evaluar los indicadores que necesita esa empresa y no otra, establecer la frecuencia y el tipo de auditorías que esa empresa necesita y valora y no otra. Un proceso de integración de sistemas de gestión no es sencillo, y en muchas ocasiones nos podemos encontrar con una no implicación del personal en el desarrollo y documentación de los procesos y procedimientos; podemos caer en la tentación de redactar instrucciones muy largas y áridas que realmente nunca se lean y mucho menos se apliquen; podemos caer en la no implicación de toda la plantilla, incluyendo a los directivos, en el cumplimiento de procedimientos y normas (Phillips, A.W, 2004).

2 Motivos para la Certificación. Motivos para la Integración Los motivos que pueden llevarle a una empresa a la certificación de una norma de gestión pueden ser muy variados: “lo pide el cliente” “mejoramos la imagen” “demostramos que creemos en la gestión”, etc. Sin embargo, cuando hablamos de que existen estudios que demuestran que las empresas certificadas en un sistema de gestión son más competitivas que las que no lo están, la cosa cambia. El estudio realizado por Mann y Kehoe (1994) (Mann y Kehoe, 1994) señalaba que la implantación de ISO 9000 estaba asociada con la mejora de los resultados de la empresa a nivel operativo. 1091


Igualmente, el estudio realizado por Casadesús, Heras y Ochoa (Casadesús, Heras y Ochoa, 2000) en 500 empresas certificadas en esta norma, llegaba a la misma conclusión. También es cierto que existen estudios muy rigurosos que no llegan a constatar una relación positiva entre la certificación y la mejora del rendimiento empresarial, como es el caso de Terziovski, Samson yDow, 1997, en empresas de Australia y Nueva Zelanda (Heras, I, Arana, G, Casadesús M; Marimon, F, 2002). Sin embargo, en lo que sí parecen estar de acuerdo gran parte de todos los estudios realizados en relación a la mejora de la competitividad y la certificación es que se puede predecir el grado de mejora obtenido en función de los motivos que les llevaron a la búsqueda de la certificación. Y si uno de los motivos que les llevaron a ello es la mejora del modelo EFQM, podemos afirmar que la integración de los sistemas de gestión es una herramienta que ayuda a la consecución de dicho modelo de excelencia empresarial (hipótesis que se lanza en el estudio de caso). Pero, ¿son los mismos los motivos para la certificación que para la integración?. Obviamente, no. La integración de los sistemas de gestión de la calidad, el medio ambiente y la seguridad y salud laboral permite a la empresa evaluar completamente la viabilidad y la salud de la organización, revisando todos los datos que puedan afectar a su éxito continuado. Los objetivos de negocio se revisan y evalúan y se ponen en marcha las acciones necesarias para asegurarse de que se cumplan. Por otra parte, permite reducir la repetición y redundancia de las auditorías y ahorra tiempo y recursos. Además genera una mentalidad de “proceso” en toda la organización que facilita la mejora continua y permite identificar los éxitos a través del sistema de gestión (Phillips, A.W, 2004).

3 La Gestión por Procesos Partiendo de un modelo de excelencia empresarial, EFQM, por ejemplo, una organización que quiere iniciar o mantener su carrera particular hacia la excelencia, necesita orientar y dirigir sus esfuerzos a aplicar las practicas que le permitirán desarrollar y consolidar una cultura de gestión por procesos dentro de la organización (Orero G, A, González D, F, 2007). En la literatura pueden encontrarse diferentes definiciones de proceso: Proceso: “conjunto de actividades mutuamente relacionadas o que interactúan, las cuales transforman elementos de entrada en resultados” ISO 9001:2000; El modelo EFQM lo define como “secuencia de actividades que van añadiendo valor mientras se produce un determinado producto o servicio a partir de determinadas aportaciones”; y Hammer y Champy (Hammer y Champy, 1993) como “conjunto de actividades que, coordinadas, crean un valor para el cliente”. Los procesos son posiblemente el elemento más importante y más extendido en la gestión de las empresas innovadoras, especialmente de las que basan su sistema de gestión en la 1092


Calidad Total (Zaratiegui, 1999). El gestionar por procesos prepara a la empresa para el entorno actual, incierto y cambiante, es decir, la preocupación creciente de la empresa por la adecuación de los procesos a las exigencias del mercado ha ido poniendo de manifiesto que una adecuada gestión, que tome los procesos como base organizativa y operativa es imprescindible para diseñar políticas y estrategias que luego se puedan desplegar con éxito (Zaratiegui, 1999). La gestión por procesos permite asegurar una excelente calidad del producto o servicio, tiempos de respuesta más cortos y la minimización de costos como aspectos clave para un buen posicionamiento en el mercado que cada vez exige mayor flexibilidad y variedad. Los modelos de excelencia, para los que la gestión por procesos es un paso previo, permiten evaluar, a través de la consideración de múltiples criterios, si una determinada empresa alcanza ese ideal o perfección empresarial (Núnez, L.I; Vélez, M; Berdugo, C, 2004). Teniendo en cuenta, por tanto, la importancia de la gestión por procesos, la empresa ha de comenzar por identificar cuáles son sus procesos, tipificándolos en función de su relevancia para la estrategia empresarial (misión y visión), su relación con la función principal de la empresa (cadena de valor) y su relación con las actividades de apoyo. A continuación se muestra el nuevo mapa de procesos de la empresa GOIAN S.L

Fig. 1 Nuevo Mapa de procesos Elevadores Goian S.L.

4 Estudio de Caso: Diseño, Elaboración e Implantación de un Sistema Integrado de Gestión en Elevadores Goian S.L. Elevadores GOIAN S.L tiene más de 40 años de experiencia en el diseño, fabricación y comercialización de maquinaria de elevación. El objetivo de su constitución fue ampliar la gama de equipos de elevación para el sector de la construcción con máquinas tales como montacargas, elevadores y plataforma elevadoras piñón cremallera, así como para otros sectores industriales, centrándose inicialmente en el sector eólico.

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En la actualidad, Goian está encaminando su gestión hacia la gestión de la Calidad Total y, para conseguirlo ve la necesidad de dar una serie de pasos. Primeramente, han comenzado a basar su gestión en una gestión por procesos, lo que permite a todo el personal el conocimiento y la información global de la empresa necesaria para poder satisfacer las necesidades del cliente en toda su amplitud. Asimismo, lleva a cabo una forma de gestión de la calidad basada en la norma ISO 9001:2008, por lo que efectúa periódicamente la revisión del Sistema de Gestión que garantiza la conformidad de los productos y servicios. Cuenta hasta el momento con un sistema de gestión de calidad, basado en la norma internacional ISO 9001:2008, certificada por la entidad TÜV Rheinland el 19/12/2008. Sin embargo, Goian empezó a darse cuenta de que por circunstancias derivadas principalmente de requisitos legales y exigencias de clientes, tenía la necesidad de comenzar a gestionar a modo de sistema de gestión, su seguridad y salud laboral y todos los aspectos relacionados con el medio ambiente (identificación y gestión de residuos, emisiones, vertidos, consumos energéticos, etc). Por una parte, es la propia ley de prevención de riesgos laborales 31/95 la que obliga a la empresa a disponer de un sistema de gestión de prevención del riesgo laboral y por otra, los nuevos requisitos legales en torno a la gestión de residuos, vertidos, emisiones, etc obligaban a Goian comenzar con una gestión más férrea de dichas situaciones. Asimismo, debido también al incremento de la concienciación social dentro y fuera de la empresa, en cuanto a la seguridad y salud laboral y al medio ambiente nace la motivación de la empresa a embarcarse en la aventura de diseñar e implantar un sistema de gestión de seguridad y salud laboral y uno medio ambiental. Finalmente también se buscaba una gestión basada en el modelo de excelencia empresarial EFQM y se entendió que un modelo integrado de gestión ayudaría a la implantación más fácil del mismo.

4.1 Objetivos y Desarrollo del Proyecto Teniendo en cuenta la problemática de Goian, se definieron dos ámbitos de actuación: por una parte el diseño, desarrollo e implantación de un sistema integrado de gestión que permita su certificación; y por otra la medición del impacto de dicho sistema en el modelo de excelencia empresarial EFQM. La consecución de dichos objetivos se fue desarrollando partiendo de la revisión inicial y diagnóstico de la situación de la empresa, estudiando las normas de referencia y viendo su posible adaptación a Goian en un modelo integrado, estudiando la legislación relacionada, tanto la relativa a seguridad como a medio ambiente, rehaciendo el mapa de procesos existente así como los procedimientos de actuación, por una parte, y realizando una autoevaluación de la empresa basándose en el cuestionario de autoevaluación elaborado por EUSKALIT (Fundación Vasca para la Calidad) con objeto de medir el impacto de la integración del sistema de gestión. 1094


4.2 Resultados y Conclusiones Como conclusión principal podemos decir que la empresa entiende que la integración de las tres normas es una buena herramienta para la mejora de productos y servicios y la satisfacción del cliente; para reducir la repetición y redundancia de las auditorías y ahorrar tiempo y recursos; para generar una mentalidad de proceso en toda la organización que facilite la mejora continua y permita identificar los éxitos a través del sistema de gestión; y para la integración de elementos clave como la seguridad laboral y la gestión ambiental en el sistema general de gestión. Y por otra parte, que el hecho de haber realizado una autoevaluación EFQM les ha permitido identificar aquéllos ámbitos de gestión donde están más débiles, identificándolos como puntos débiles e introduciéndolos como posibilidades de mejora desde dirección. Se espera repetirlo el próximo año y estudiar su resultado. En lo referente a resultados, se ha diseñado un sistema integrado de gestión y se ha elaborado un manual integrado. El 80% ha sido revisado y aprobado por la dirección y se está comenzando su implantación, que está alrededor del 30%. Se prevé la realización de una auditoría interna para el mes de junio en la que ya esté todo el sistema revisado. A continuación se muestra uno de los resultados más evidentes de este proyecto que es la modificación de uno de sus procesos estratégicos: Gestión integrada. En color amarillo se pueden ver las modificaciones realizadas. Responsable Objeto

Responsable de Calidad Implantar, mantener y mejorar todos los aspectos relacionados con el Sistema Integrado de la empresa.  Gestión documental del sistema

Descripción

 Medición del sistema: no conformidades, auditorias, indicadores …  Gestión de la mejora continua

Departamentos Implicados Puntos de las ISO/OHSAS referente

Procedimientos

Normas

Documentos

Registros/Impresos

Gerencia; Calidad; I+D+i; Producción; Comercial; Posventa; Finanzas, Administración y RRHH; - 4.1 Requisitos Generales / 4.1 Requisitos Generales / 4.1 Requisitos generales - 8. Medición, Análisis y Mejora / 4.5.1 Seguimiento y medición del desempeño / 4.5.1 Seguimiento y medición -

PR-03-4.2-01 Control de los Documentos y Registros PR-03-7.6-01 Calibración de Equipos de Control PR-03-8.2-01 Auditorías Internas PR-03-8.3-01 No Conformidad / Incidencia de Producto PR-03-8.5-01 Acciones Correctivas y Preventivas PR-03-X Gestión del Servicio de Prevención ajeno PR-03-X Coordinación de Actividades Empresariales

-

Las referencias de las Normas se incluyen en la Matriz Control de la Documentación

-

D-30-4.1-01 Mapa de Procesos D-30-4.2-01 Manual Integrado

-

D-30-4.2-02 Matriz Control de la Documentación D-30-7.6-01 Inventario de Equipos de Medición D-30-8.2-01 Programa de Auditoría Interna D-30-8.2-02 Tabla de Indicadores

-

Las referencias de los Registros/Impresos se incluyen en la Matriz Control de la Documentación

-

€ pagados en las No Conformidades Emisiones CO2/Ahorro energía en % o € /nº de clientes ganados por esta ventaja competitiva / € ganados por esos clientes  Con intención de motivar al personal Nº de accidentes/incidentes / € que provocan los accidentes/incidentes

Indicador -

Desarrollo Indicador

La suma de los € pagados en las No Conformidades La suma del ahorro de energía / La suma del nº/€ de clientes La suma de nº de accidentes/incidentes / La suma de € que provocan los accidente/incidentes

Control

3 meses

Fig.2 Nuevo proceso de gestión integrada

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Finalmente podemos mostrar la matriz Reder utilizada para autoevaluarse en excelencia empresarial en su apartado “relevancia y utilidad” y ver el impacto de la implantación de un sistema de gestión integrado. La conclusión a la que se llega es que Goian está en el camino hacia la excelencia, pero aún le falta mucho por recorrer (25% realizado). Relevancia y Utilidad Ámbito y Relevancia:  El ámbito de aplicación de los resultados:  Aborda las necesidades y expectativas de los grupos de interés relevantes.  Es coherente con la estrategia y sus políticas de apoyo.  Los Resultados Clave están identificados y priorizados.  Las relaciones entre los resultados relevantes se entienden. Integridad:  Los resultados son oportunos, fiables y precisos Segmentación:  Los resultados se han segmentado de forma adecuada.

0%

25%

50%

75%

100%

Relevancia no establecida o información anecdótica.

¼ de las áreas implicadas (aprox.) tienen resultados y son relevantes.

½ de las áreas implicadas (aprox.) tienen resultados y son relevantes.

¾ de las áreas implicadas (aprox.) tienen resultados y son relevantes.

Todas las áreas implicadas tienen resultados y son relevantes.

Ninguna evidencia o información anecdótica.

¼ de los resultados (aprox.) son oportunos, fiables y precisos.

½ de los resultados (aprox.) son oportunos, fiables y precisos.

¾ de los resultados (aprox.) son oportunos, fiables y precisos.

Todos los resultados son oportunos, fiables y precisos.

Sin segmentación.

Segmentación útil en aproximadamente ¼ de los resultados.

Segmentación útil en aproximadamente ½.

Segmentación útil en aproximadamente ¾.

Segmentación útil en todos los resultados.

Total para Relevancia y Utilidad*

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

*Nota: El total no debe exceder la puntuación de ámbito y relevancia. Rendimiento Tendencias:  Las tendencias son positivas y/o el rendimiento es bueno y sostenido.

0%

25%

50%

75%

100%

¼ de los resultados (aprox.) con tendencias positivas y/o buen rendimiento sostenido al menos 3 años.

½ de los resultados (aprox.) con tendencias positivas y/o buen rendimiento sostenido al menos 3 años.

¾ de los resultados (aprox.) con tendencias positivas y/o buen rendimiento sostenido al menos 3 años.

Todos los resultados con tendencias positivas y/o buen rendimiento sostenido al menos 3 años.

Sin objetivos o información anecdótica.

Establecidos, adecuados y alcanzados en ¼ (aprox.) de los Resultados Clave.

Establecidos, adecuados y alcanzados en ½ (aprox.) de los Resultados Clave.

Establecidos, adecuados y alcanzados en ¾ (aprox.) de los Resultados Clave.

Establecidos, adecuados y alcanzados en todos los Resultados Clave.

Sin comparaciones o información anecdótica.

¼ de los Resultados Clave (aprox.) con comparaciones favorables y adecuadas.

½ de los Resultados Clave (aprox.) con comparaciones favorables y adecuadas.

¾ de los Resultados Clave (aprox.) con comparaciones favorables y adecuadas.

Todos los Resultados Clave con comparaciones favorables y adecuadas.

Fig. 3 Matriz REDER de resultados Sin resultados o Objetivos:  Se han establecido para los Resultados Clave.  Son adecuados.  Se alcanzan.

5 Referencias

Comparaciones:  Se comparan los Resultados Clave.  Son adecuadas.  Son favorables. Causas:  Se comprende la relación entre los Resultados alcanzados y sus Agentes Facilitadores.  Según las evidencias presentadas hay confianza en que el rendimiento siga siendo positivo en el futuro.

información anecdótica

La relación con los Agentes La relación con los Agentes AENOR (2005), UNE 66177:2005 Guía para la integración de los sistemas de gestión. La relación con los Agentes es La relación con los Agentes es es visible en ¼ de los es visible en ½ de los Las causas no generan visible en ¾ de los resultados visible en todos los resultados y resultados (aprox.) y hay resultados (aprox.) y hay AENOR (2007) Nota de prensa confianza o información (aprox.) y hay alguna evidencia hay alguna evidencia de que el alguna evidencia de que el alguna evidencia de que el anecdótica de que el rendimiento seguirá rendimiento seguirá siendo rendimiento seguirá siendo rendimiento seguiráForum siendo Casadesús M, Heras I (1999) ISO 9000 obstáculos y beneficios. Calidad. siendo positivo. Madrid positivo. positivo. positivo. Total para Rendimiento: Casadesús M, Heras I, Ochoa C (2000) benefits the45 implementation the85ISO 0 5 10 The 15 20 25 30 35of 40 50 55 60 65 70 75of 80 90 9000 95 100 norValoración Total 10 15 20 companies. 25 30 35 40 45 50 55 60 65Conference 70 75 80 85 on 90 Production 95 100 mative. Empirical research in 0the5 Spanish First Work and Opetations Management. POM. Sevilla Deming W (1989) Calidad, productividad y competitividad: la salida de la crisis. Ediciones Díaz de Santos. Madrid. Heras I, Arana G, Casadesús M, Marimon F (2002) Incidencia de la gestión de la calidad en el rendimiento económico empresaial: un estudio empírico en las empresas vascas. XII Congreso Nacional de ACEDE. Palma de Mallorca INSHT (2001) NTP 576 Integración de sistemas de gestión: prevención de riesgos laborales, calidad y medio ambiente. Mann R, Kehoe D (1994) An evaluation of the effects of quality improvement in manufacturing. International Journal of quality and reliabililty management 11, nº 7 Nuñez L, Vélez M, Berdugo C (2004) Aplicación de una metodología de mejora de procesos basada en el enfoque de gestión por procesos en los modelos de excelencia y el QFD en una empresa del sector de confecciones de Barranquilla. Ingeniería & Desarrollo. Universidad del Norte. Colombia Orero G, Conzález D (2007) Las claves de una organización orientada a procesos. Forum calidad nº 179. Phillips A W (2004) Beneficios de la gestión integrada: calidad, seguridad y medio ambiente Zaratiegui J R (1999) La gestión por procesos: su papel e importancia en la empresa. Economía Industrial, nº 130

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Modelo para la Implementación de Sistemas de Gestión Preventivos en Sectores Singulares Modelling for Implantation of the Systems Preventive Management in the Singular Sectors Solano Martos J1, Maeso González E2 Abstract The fundamental aim of this study has been the development of a System of Management of the Safety Risks of general application to business sectors of singular activity. The study proposes, the necessary tools for the modelling of the tending systems to the implantation of the tools of applicable preventive management in the singular sectors. Conscious of the existence of specific models centred in the strict fulfillment of the valid legislation, these can suffer from of the sufficient level that provide the suitable results of in accordance with the problematic that really pose in preventive matter in the singular sectors. At the same time, it pretends develop a scientific methodology that allow the identification and correct business classification of the singular sectors with the end to give an effective preventive treatment of the intrinsic risks to the activities that in them develop, taking into account the specific legislation that affects them in preventive matter and of industrial safety, and in base to a correct identification of the dangers and evaluation of the risks that allow subsequently exert the pertinent preventive actions tending to the effective management of said risks, with the end to delete them and/or reduce them to acceptable levels.

Resumen El objetivo fundamental de este estudio ha sido el desarrollo de un sistema distribuido de Gestión de la Prevención de Riesgos Laborales de aplicación 1 José Solano Martos ( e-mail: [email protected]). Dpto. de Ingeniería Civil, Materiales y Fabricación. Escuela Técnica Superior de Ingenieros Industriales. Universidad de Málaga. C/Doctor Ortiz Ramos s/n, Campus Teatinos, 29071 Málaga 2 Elvira Maeso González ( e-mail: [email protected]) Dpto. de Organización de Empresas. Escuela Técnica Superior de Ingenieros Industriales. Universidad de Málaga. C/Doctor Ortiz Ramos s/n, Campus Teatinos, 29071 Málaga

* Destacar nuestro agradecimiento a la “Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech” por su apoyo en todo momento.

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general a sectores empresariales de actividad singular. El estudio propone, las herramientas necesarias para la modelización de los sistemas tendentes a la implantación específica de las herramientas de gestión preventiva aplicables en los sectores singulares. Conscientes de la existencia de modelos específicos centrados en el estricto cumplimiento de la legislación vigente, éstos pueden adolecer de la suficiente eficacia que proporcionen los resultados adecuados de acorde con la problemática que realmente se plantean en materia preventiva en los sectores singulares. Al mismo tiempo, se pretende desarrollar una metodología científica que permita la identificación y correcta clasificación empresarial de los sectores singulares con el fin de dar un tratamiento preventivo eficaz de los riesgos intrínsecos a las actividades que en ellos se desarrollan, teniendo en cuenta la legislación específica que les afecta en materia preventiva y de seguridad industrial, y en base a una correcta identificación de los peligros y evaluación de los riesgos que permita con posterioridad ejercer las acciones preventivas pertinentes tendentes a la gestión eficaz de dichos riesgos, con el fin de eliminarlos y/o reducirlos a niveles aceptables.

Keywords: Singular Sectors, Minoritary Sectors, Group of Risk, Model of Preventive Management, Elements of the System of Management. Palabras clave: Sectores Singulares, Sectores Minoritarios, Grupo de Riesgo, Modelo de Gestión Preventivo, Elementos del Sistema de Gestión.

1 Introducción Es indudable el avance experimentado en los últimos años en materia preventiva; disponemos de una completa normativa y legislación laboral adaptada al entorno europeo, utilizamos novedosos programas informáticos de prevención de riesgos, realizamos un completo seguimiento estadístico de la siniestralidad laboral de nuestras empresas, ya sea a nivel local, autonómico ó estatal. El avance en materia de formación preventiva en consonancia con la aplicación de las nuevas tecnologías de la comunicación nos ha permitido llegar a sectores ó empresas antes inalcanzables. Las empresas han implantado sistemas de gestión preventiva basados en una mejora continua e integrable con otros sistemas existentes ó en pro de una mayor competitividad, convirtiéndose la prevención de los riesgos laborales en un factor estratégico empresarial. Sin embargo, a la hora de abordar la existencia de modelos de gestión preventivos en sectores singulares refiriéndonos a “sectores minoritarios” ó aquéllos a los que por sus características especiales se denominan “sectores singulares”. Resulta curioso saber, que a pesar de los avances tecnológicos y del conocimiento experimentado en los últimos años, coexistan todavía empresas pertenecientes a sectores de especial peligrosidad de los que apenas se tiene 1098


conocimiento alguno y que carecen en gran medida de los medios y de los recursos necesarios para poder desarrollar su actividad laboral con la suficiente garantía de protección y de seguridad para sus trabajadores. El símil más comprensible al hablar de estos “sectores singulares”, es sin lugar a dudas, el que podemos establecer comparativamente con el término de “enfermedades raras” ó “enfermedades poco comunes, minoritarias ó enfermedades poco frecuentes”. Con dificultades similares a las indicadas con anterioridad en el símil propuesto, nos encontramos cuando tratamos con empresas pertenecientes a sectores singulares. Se trata de sectores que tienen muy poco impacto en el conjunto de la sociedad; todos somos conocedores de su existencia y de la peligrosidad que entraña la actividad que en ellos se desarrollan, pero no disponemos de herramientas eficaces para una correcta aplicación de la metodología de control y gestión de sus riesgos, limitándose, en ocasiones, si procede, al estricto cumplimiento legislativo. La carencia de información y de recursos presente en la mayoría de los sectores singulares junto con la necesidad de prestar toda nuestra experiencia para la mejora de las condiciones de seguridad y de salud laboral de los profesionales que trabajan en sus empresas, han sido los principales factores que han motivado el acometer un estudio de estas características. Es de señalar que el modelo propuesto en este estudio se ha refrendado en el sector de las actividades subacuáticas, ya que por las características singulares de dicho sector, la influencia del medio en el que se trabaja y la falta de información estadística de incidentes con daño que afectan a la seguridad y la salud de sus profesionales, su regulación preventiva, la reciente publicación de su convenio colectivo, supone un importante reto hacia la mejora de las condiciones de trabajo de los profesionales del sector.

2 Factores de Clasificación de un Sector Singular A la hora de determinar la pertenencia de la empresa a un determinado sector singular, el modelo define cuatro factores considerados fundamentales:  El tamaño de la organización  El riesgo potencial  La normativa y la legislación preventiva que le aplica  La siniestralidad laboral Los diversos factores que intervienen en una clasificación empresarial no son excluyentes, lo que significa que el modelo se basa en una interacción ó combinación de factores que confieren a la empresa un determinado carácter singular.

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MODELO DE CLASIFICACIÓN SECTOR SINGULAR • Actividad • Evaluación de riesgos • Peligrosidad sustancias • Productos químicos • Maquinaria/Equipos • Procesos

• Prevención • Seguridad Industrial • Medio Ambiente • Otras disposiciones

RIESGO

NORMATIVA

POTENCIAL

LEGISLACIÓN

TAMAÑO

SINIESTRALIDAD

ORGANIZACIÓN

LABORAL

• Organización • Nº de empleados

• Histórico de Accidentes e Incidentes • Índices estadísticos

Fig. 1 Clasificación de un sector singular según factores que afectan (Fuente: Autores)

El modelo de clasificación sectorial atendiendo al código de actividad empresarial define sin lugar a dudas de forma directa la pertenencia de ciertas empresas a un determinado grupo de riesgo. Según define el propio INE. MODELO DE CLASIFICACIÓN SECTORIAL POR CÓDIGO DE ACTIVIDAD EMPRESARIAL

CNAE

CNO

NACE

¿EMPRESA CLASIFICADA?

RIESGO BAJO

NO

SECTOR DE RIESGO

SI

RIESGO MEDIO

RIESGO ESPECIAL

CUESTIONARIO DE CLASIFICACIÓN

Fig. 2 Clasificación sectorial por código de actividad empresarial (Fuente: Autores)

1100


Si la empresa o profesional ha procedido a la realización de la evaluación de sus riesgos laborales, pero no se dispone de CNAE ó CNO, ó éste no aportara infomación alguna acerca de su pertenencia a un determinado grupo de riesgo, el modelo propone la realización de un cuestionario con la siguiente información: Datos básicos de la empresa  Nº de trabajadores en plantilla  Actividad económica principal de la empresa  Nº de centros de trabajo con los que cuenta la empresa  Sector de actividad al que pertenece: – – – –

Agrario Industrial Servicios Construcción

Actividades que desarrolla Con el fin de verificar de forma directa su pertenencia a un determinado grupo de riesgo, el cuestionario relaciona aquéllas actividades consideradas de riesgo especial en función de la normativa y legislación aplicable. Evaluación de riesgos laborales El cuestionario establece una metodología específica para la clasificación del riesgo empresarial en función de los resultados ponderados de las evaluaciones de riesgos realizadas. Para la clasificación sectorial del riesgo empresarial el modelo toma como referencia la metodología de evaluación de riesgos laborales desarrollada por el INSHT en su “Guía de Evaluación de Riesgos Laborales” adaptando dicha metodología de forma que agrupa y pondera los resultados de las evaluaciones realizadas. De esta manera el modelo presenta tres categorías del riesgo empresarial: BAJO, MEDIO y ESPECIAL. Table 1 Clasificación de riesgos (Fuente: adaptada INSHT. Método simplificado de Evaluación) NIVEL DE RIESGO

% RIESGO BAJO % RIESGO MEDIO % RIESGO ESPECIAL

= = =

TRIVIAL

TOLERABLE

MEDIO

TOLERABLE

MEDIO

IMPORTANTE

MEDIO

IMPORTANTE

INTOLERABLE

% RIESGO TRIVIAL + %RIESGO TOLERABLE % RIESGO MEDIO % RIESGO IMP. + % RIESGO INTOLERABLE

1101

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 2 Agrupación de riesgos (Fuente: Autores) RIESGO BAJO

RIESGO MEDIO

% TRIVIAL

% MEDIO

% TOLERABLE

RIESGO ESPECIAL % IMPORTANTE

% INTOLERABLE

Para determinar con posterioridad a la evaluación de riesgos laborales el nivel de intervención mediante la aplicación de elementos de gestión preventiva basados en OHSAS 1800:2007, se ha tomado como referencia la NTP–330/1993 del INSHT que agrupa los diferentes niveles de riesgo y de intervención en categorías. Nivel de Riesgo = Nivel de Probabilidad x Nivel de Consecuencias Nivel I: Situación Crítica. Corrección urgente Nivel II: Corregir y adoptar medidas de control Nivel III: Mejorar si es posible. Sería conveniente justificar la intervención Nivel IV: No intervenir salvo que un análisis más preciso lo justifique Table 3 Determinación del nivel de riesgo y de intervención (Fuente: Adaptada de NTP 330/1993, INSHT)

10 25 60 100

2-4 IV III

6-8 III II I

II

10-20 III II I I

24-40 II I

Clasificación del riesgo ponderado: Riesgo BAJO: Si al menos el 75% de los puestos de trabajo evaluados han sido clasificados como riesgos TRIVIALES ó TOLERABLES. Riesgo MEDIO: Si al menos el 50% de los puestos evaluados han sido clasificados de RIESGO MEDIO. Riesgo ESPECIAL: Si al menos el 25% de los puestos evaluados han obtenido una calificación de IMPORTANTE ó INTOLERABLE Resultado ponderado de la Evaluación de Riesgos Laborales

RIESGO BAJO

RIESGO MEDIO

RIESGO ESPECIAL

75%

50%

25%

1102

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. CLASIFICACIÓN SECTORIAL POR NORMATIVA Y LEGISLACIÓN AFECTADA NORMATIVA Y LEGISLACIÓN PREVENTIVA QUE LE AFECTA

1

• INTERNACIONAL

0TRAS DISPOSICIONES

2

3 4

• EUROPEA

PREVENCIÓN DE RIESGOS LABORALES

SEGURIDAD INDUSTRIAL

MEDIO AMBIENTE

Convenios colectivos

Agentes de riesgo

• ESTATAL

Específica de equipos

• SECTORIAL

Ley Real Decreto Orden Ministerial

Fig. 3 Clasificación sectorial según normativa y legislación preventiva (Fuente: Autores) CLASIFICACIÓN ESTADÍSTICA SECTORIAL

Mº de Trabajo

Clasificación Estadística Asociaciones Sectoriales

IF II IG

CC.AA. Provincia

Fig. 4 Clasificación estadística sectorial (Fuente: Autores)

1103

INSHT


AFECTADA POR NORMATIVA DE CARÁCTER

ACTIVIDAD EMPRESARIAL DE DIFÍCIL CLASIFICACIÓN

INDUSTRIAL Y MEDIO AMBIENTAL POTENCIAL DE RIESGO ALTO CLASIFICACIÓN COMO ACTIVIDADES PELIGROSAS

POCO ESTUDIADAS TAMAÑO < 250 EMPLEADOS - Autónomos

INDICADORES DE FRECUENCIA Y DE GRAVEDAD DESCONOCIDOS

- Microempresas - Empresa pequeña - Empresa mediana

ALTA SINIESTRALIDAD LABORAL

Fig. 5 Características de una empresa singular (Fuentes: Autores)

3 Modelo Sectorial Sistema de Gestión Preventivo: Elementos Dado el objetivo de simplicidad que perseguimos no emplearemos valores absolutos del riesgo en función de su probabilidad y consecuencia, sino sus “niveles” de riesgo ponderados en una escala de tres posibilidades. A MAYOR Nivel de Deficiencia

MAYOR Nivel de Intervención

MATRIZ MODELO DE GESTIÓN EN FUNCIÓN DEL RIESGO EMPRESA SINGULAR

Modelo de Gestión

Modelo de Gestión

Modelo de Gestión

BÁSICO

MEDIO

AVANZADO

Nivel de Riesgo

Nivel de Riesgo

Nivel de Riesgo

Bajo

Medio

Especial

Fig. 6 Matriz asociada de modelo de gestión (Fuente: Autores)

El modelo propone cumplir con una serie de elementos que conforman el Sistema de Gestión Preventivo de SST. Estos elementos preventivos se han desarrollado tomando como referencia el estándar OHSAS 18001 adaptado y ampliado a las peculiaridades de las empresas del sector singular. 1104


A medida que vamos subiendo en la clasificación de la empresa en función de su riesgo se adoptan más requisitos del estándar de referencia. El modelo ha sido validado en el sector del buceo profesional.

MODELO SECTORIAL SISTEMA DE GESTIÓN PREVENTIVO ELEMENTOS DEL SISTEMA DE GESTIÓN PREVENTIVO POLÍTICA

• Política de Seguridad y Salud Laboral

BÁSICO

MEDIO

AVANZADO

MEDIO

AVANZADO

• Identificación de Peligros y Evaluación de riesgos • Identificación de requisitos legales y otros requisitos PLANIFICACIÓN

• Objetivos de Seguridad y Salud Laboral • Planificación de la acción preventiva • Formación, entrenamiento y capacitación en materia preventiva • Comunicación, participación y consulta

• Control de la documentación y registros • Control Operacional IMPLEMENTACIÓN

• Seguridad para contratistas/subcontratistas • Seguridad en compras y adquisición de bienes y equipos • Vigilancia periódica de la salud de los trabajadores • Control periódico de las condiciones higiénicas de trabajo • Preparación y respuesta ante emergencias • Inspecciones de seguridad y observaciones preventivas • Notificación, investigación y análisis de accidentes e incidentes

VERIFICACIÓN

• No conformidad, acción correctora y preventiva

• Auditorías REVISIÓN

• Revisión del Sistema

Fig. 7 Modelo sectorial sistema de gestión preventivo empresas singulares (Fuente: Autores)

4 Referencias AENOR (2007): Sistemas de gestión de la seguridad y salud en el trabajo. OHSAS 18001:2007. Asociación Española de Normalización y Certificación. Madrid. BRITISH STANDARS INSTITUTION (2008): OHSAS 18002:2008. Occupational health and safety management systems – Guidelines for the implementation of OHSAS 18001:2007. British Standars Institution. Londres. INSHT (1975): Nota Técnica de Prevención NTP 330. Sistema simplificado de evaluación de riesgos de accidente. Instituto Nacional de Seguridad e Higiene en el Trabajo (INSHT). Solano Martos, J. (2011): Tesis doctoral Modelización para el estudio, análisis y prevención de riesgos intrínsecos en sectores singulares. Universidad de Málaga.

1105


SP-05 Gestión del Conocimiento y de Proyectos

1107


Estimación de la Evolución de Proyectos en el Ámbito de la Producción Industrial mediante la Parametrización de la Curva S del Coste Acumulado Estimation of the Projects Evolution in the Field of Industrial Production by Parameterization the Cumulative Cost S Curve García Escribano E1 Abstract We aim to design a project control mechanism based in the parameterization of the cumulative cost S curve to applied it to projects in the field of industrial production. In this way, we will complement the earned value technique by helping in the estimation of the different stages evolution of these projects, so that we will increase control and cost estimation efficiency.

Resumen Se pretende diseñar un mecanismo de control de proyectos basado en la parametrización de la curva S del coste acumulado para aplicarlo a proyectos en el ámbito de la producción industrial. Así, se complementará la técnica del valor ganado ayudando en la estimación de la evolución de las diferentes etapas de dichos proyectos, de forma que se aumentará la eficiencia en el control y en la estimación de costes.

Keywords: Control, Earned Value, Industrial Production, S Curve Palabras clave: Control, Valor Ganado, Producción Industrial, Curva S

1Eduardo García Escribano ( e-mail: [email protected] / [email protected]) Grupo INSISOC. Dpto. de Organización de Empresas y CIM. Escuela de Ingenierías Industriales. Universidad de Valladolid. Pso del Cauce S/N, 47011 Valladolid. Connectia Solutions Factory. Avd Colada de Pozuelo, 20, 28925 Alcorcón (Madrid)

1109


1 Introducción Controlar un proyecto significa seguir su evolución estudiando las posibles desviaciones entre los costes y plazos reales, los costes presupuestados y los plazos planificados (PMI, 2008). La multiplicidad de tipos de empresas, tipos de proyectos y tipos de tareas que pueden existir dificultan la obtención de un patrón de control de proyectos global. Se va a particularizar el estudio para proyectos desarrollados en el ámbito de la producción industrial con una secuencia de actividades que se extiende sobre un largo período de tiempo, y que representan una importante dedicación de capitales, recursos materiales y personal. Este enfoque permitirá validar la base teórica y la metodología que se describirá a continuación. El artículo se estructura comenzando por enumerar los objetivos que se quieren alcanzar. Después, se particularizará el modelo continuo de la función logística definiendo las etapas que forman los proyectos de ámbito industrial. A continuación, se validarán los resultados obtenidos simulando para ello un número suficientemente alto de proyectos, y se terminará con las conclusiones extraídas de este trabajo de investigación.

2

Objetivos

La metodología del valor ganado (Anbari, 2003) aporta desviaciones temporales, índices de rendimiento, porcentajes de avance y estimaciones del coste final de un proyecto (Christensen, 1999 y Henderson, 2003), pero no puede indicar cómo será la evolución de dicho proyecto desde el estado actual de ejecución del mismo hasta su cierre (Lipke, 2005 y Taylor, 2009), es decir, utiliza estimadores para realizar predicciones aproximadas, utilizando las variaciones que está sufriendo un proyecto y anticipar las variaciones en la finalización del mismo. En este trabajo se pretende mejorar la capacidad predictiva en los proyectos de ámbito industrial, complementando este tipo de técnicas usadas habitualmente (García, 2010 y Vanhoucke, 2009), y utilizando para ello la parametrización como una función continua de la curva que representa el coste planificado acumulado del proyecto, conocida como curva S, resultando así una aproximación más real que simula el comportamiento del proyecto hasta su cierre. La función continua parametrizada será una estimación de la evolución del proyecto hasta su finalización, la cual podrá ser usada como mecanismo de control de proyectos comparando el progreso del proyecto con las previsiones dadas por la curva, que será la referencia que el director del proyecto utilizará durante la ejecución del mismo para corregir las desviaciones. Así, se mejora el seguimiento, anticipando los ajustes necesarios para llegar al cierre del proyecto con éxito y aumentando la eficiencia en el control y en la estimación de costes. 1110


3

Etapas de un Proyecto de Producción Industrial

Los proyectos de producción desarrollados en el ámbito industrial se caracterizan principalmente por una larga duración y una gran cantidad de recursos utilizados. Para el desarrollo de la investigación propuesta se va a suponer que sus etapas se presentan secuencialmente en cinco grandes grupos con el fin de dividir el dominio del tiempo en cinco segmentos, lo cual es suficiente para representar la aproximación de la curva S del coste acumulado (Noori, 2008). 1. Etapa de Definición Es aquélla en la que la idea se concreta y se realizan los estudios preliminares. Por lo general, los proyectos comienzan con una pequeña cantidad de tareas iniciales, por lo que el coste acumulado será prácticamente constante en esta etapa.

E1 (t )  cte  [- < x  t1 ]

(3.1)

2. Etapa de Concepción Su propósito es determinar las especificaciones técnicas, el coste, el alcance, el programa y las necesidades de recursos. Se comienza a hacer frente a un gran número de actividades al mismo tiempo, lo que aumenta considerablemente el gasto en comparación con el trabajo inicial (Cioffi, 2005 y Weisstein, 2004). Así, el coste acumulado se puede simular mediante una ecuación de segundo grado. E2 (t )  ax 2  bx  c  [t1 < x  t 2 ]

(3.2)

3. Etapa de Construcción Es la más larga y costosa en la mayoría de los casos, donde se hace real lo que se ha definido anteriormente, ejecutando y controlando los elementos del producto o sistema según las especificaciones desarrolladas en las etapas precedentes. El coste acumulado aumenta rápidamente y se puede simular con una función lineal. E3 (t )  ax  b  [t 2  x  t 3 ]

(3.3)

4. Etapa de Puesta en Marcha El presupuesto suele ser limitado y el gasto tiende a disminuir en las etapas finales. Además, muchas de las tareas dependen unas de otras y no pueden terminar todas simultáneamente, sino que van terminando poco a poco (Vitner, 2006), lo que se puede simular con una ecuación de segundo grado de signo negativo.

E4 (t )  ax 2  bx  c  [t 3 < x  t 4 ] 1111

(3.4)


5. Etapa de Cesión La organización del proyecto va finalizando sus funciones, bien porque el producto o sistema se ha integrado en la estructura organizativa regular, bien porque el producto se ha entregado al cliente que lo solicitó, o bien porque el proyecto ha terminado en un fracaso y debe cancelarse. En esta etapa, al igual que en la primera, el coste acumulado será prácticamente constante en el periodo. (3.5)

E5 (t )  cte  [t 4  x  ]

De esta forma, se puede representar cada segmento por una función simple, obteniéndose la figura del coste acumulado de un proyecto en función del tiempo mediante una curva tipo S (Cioffi, 2006). Su adaptación permitirá simular diferentes escenarios para ver diferentes alternativas sobre los costes reales, el gasto previsto y el coste presupuestado. Segmentos de la funcion logistica 1 E5(t)

0.9 E4(t) 0.8 0.7

E(t)

0.6

E3(t)

0.5 0.4 0.3 0.2 0.1 0 -5

E2(t) E1(t)

-4

-3

-2

-1

0 tiempo

1

2

3

4

5

Fig. 1 Segmentos de la función logística

4 Parametrización de la Curva S mediante la Función Logística Cuando se muestra el valor ganado como una función del tiempo, los costes de un proyecto suelen tener una forma determinada, descrita como curva de S. Podremos simular la planificación de los costes dentro de un sector específico comparando la línea base obtenida mediante la técnica del valor ganado y las aproximaciones obtenidas mediante parametrización de la función logística. A continuación se expone la solución a la ecuación diferencial logística (Cioffi, 2005 y Meyer, 1999). Lo que se pretende es aprovechar las propiedades de una función continua como es la función logística, en vez de usar valores discretos (García, 2012). La solución a la 1112


función logística se puede expresar en función de los parámetros α, β y κ (García, 2012 y Meyer, 1999).

E (t )  E0 



(4.1)

1  e  t  

El parámetro α representa la pendiente de la curva y se suele representar como una variable ∆t que es el tiempo necesario para llegar del 10% al 90% de κ, siendo ∆t=ln(81)/ α (Cioffi, 2005). El parámetro β es el instante en que se alcance 1/2 κ. Así, se puede representar la curva S en función los siguientes parámetros: el límite máximo de crecimiento de la curva (Ef), el tiempo de crecimiento (∆t) y el punto medio (tm) en el que la curva alcanza ½ de Ef.

Ef

E (t )  1 e



ln(81) ( t t m ) t

(4.2)

Es posible estimar numéricamente estos tres parámetros para calcular la función de la curva S (García, 2012) y así estimar la evolución del coste acumulado mediante el perfil de curva deseado que más se adapta a este tipo de proyectos.

5

Simulación y Validación de los Resultados

Para la validación experimental de la función propuesta se ha dispuesto de una cantidad de datos suficientemente amplia (20 proyectos). Los proyectos analizados son reales, y todos desarrollados en el ámbito objetivo de este trabajo. Se ha realizado la media de los costes acumulados de todos los proyectos, en términos de porcentaje, en tres puntos equidistantes temporalmente en cada una de las etapas, con el fin de poder trazar la curva en S a lo largo de las mismas. Las características de los proyectos reales analizados se muestran en la siguiente tabla. Tabla 1 Características de los proyectos reales analizados para la validación de los resultados Entorno

Industrial

Tipo de proyectos

Producción

Número de proyectos analizados

20

Duración media de los proyectos

52,5 semanas

Suma de la duración de los proyectos

1.050 semanas

Proyecto de mayor duración

61 semanas

Proyecto de menor duración

45 semanas

Desviación estándar de la duración de los proyectos

5,43

1113


Representando la media de los costes acumulados de los proyectos analizados, y realizando una aproximación mediante una regresión logística, se obtienen las curvas en S de la Fig. 2. Coste acumulado(%). Media de los proyectos en cada etapa analizada 1 WD5-C

0.9

WD5-A

WD5-B

WD4-C

0.8

WD4-B

WD4-A

Coste Acumulado (%)

0.7 0.6

WD3-C

0.5 0.4 WD3-B

0.3 WD3-A

0.2 WD2-B

0.1

WD2-C

WD1-C WD1-A

WD1-B WD2-A

0

0

10

20

30 Tiempo (semanas)

40

50

60

Coste acumulado(%). Aproximación a la función logística 1 0.9

Coste Acumulado (%)

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

0

10

20

30 Tiempo (semanas)

40

50

60

Fig. 2 Media de los proyectos en cada etapa analizada. Aproximación a la función logística

Mediante simulaciones (Miranda, 2002) en función del tiempo con los diferentes valores de Ef, tm y ∆t de la ecuación 4.2, se obtienen diferentes gamas de curvas. Ajustando dichos parámetros en Ef = 1, tm = 30 y ∆t = 25, se obtiene una curva superpuesta a la obtenida realmente con los datos del coste acumulado. Se puede ver la superposición de dichas curvas en la Fig. 3., donde se muestra a su vez una predicción real de la curva S.

1114

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Coste acumulado(%) de los proyectos analizados

E(t)

1

0.5

0

0

10

20

30 40 50 tiempo (semanas) Parametrización de la función logística. Ajuste de parámetros

10

20

60

E(t)

1

0.5

0

0

30 tiempo (semanas)

40

50

60

Fig. 3 Parametrización de la función logística. Ajuste de parámetros

En la Fig. 4 se puede observar que ajustando los parámetros de la ecuación 4.2 se puede obtener una buena aproximación de la curva logística que se adapta a los parámetros de la curva real. Así, tras una muestra de 20 proyectos, todos ellos del mismo entorno, queda demostrado que se pueden utilizar dichos parámetros para obtener una estimación del coste planificado acumulado del proyecto. Comparación entre la curva real y la curva parametrizada ajustada 1 Curva parametrizada ajustada Curva del coste acumulado real

0.9 0.8 0.7

E(t)

0.6 0.5 0.4 0.3 0.2 0.1 0

0

10

20

30 tiempo (semanas)

40

50

Fig. 4 Comparación entre la curva real y la curva parametrizada ajustada

1115

60


6

Conclusiones

Se ha construido un modelo matemático aplicando las propiedades continuas de la función que representa el coste planificado acumulado del proyecto, obteniéndose así una estimación de la evolución del proyecto hasta su finalización. Mediante el análisis de los proyectos llevados a cabo en la investigación se ha demostrado como se puede complementar la técnica del valor ganado mejorando la capacidad predictiva y de seguimiento de los proyectos de ámbito industrial, ajustando los parámetros que definen la función logística para representar la curva del coste acumulado del proyecto, reduciendo así la incertidumbre desde la etapa actual del proyecto hasta su finalización. Con este enfoque, la modelización de la curva de S pasa de ser una mera descripción a una definición matemática completa, pasando de los valores discretos utilizados en la técnica del valor ganado, a una función continua con características propias, lo que permite aumentar la eficiencia en el seguimiento de cada proyecto, facilitando así al director de proyectos que pueda representar y particularizar cualquier escenario de predicción mediante la selección de los parámetros Ef, ∆t y tm, adecuados.

7 Referencias Anbari FT (2003) Earned value project management method and extensions. Project Management Journal, 34 (4):12-23. Christensen D (1999) Using the Earned Value Cost Management Report To Evaluate the Contractor’s Estimate At Completion. Acquisition Review Quarterly. Cioffi D (2006) Designing project management: A scientific notation and an improved formalism for earned value calculations. International Journal of Project Management, 24: 136-144. Cioffi, D.: A tool for managing projects: an analytic parameterization of the s-curve. International Journal of Project Management. Vol. 23, No. 3, pp. 215–222 (2005). García EE (2010) Specific Project Portfolio Management Techniques for monitoring and controlling Enterprise Project Portfolios. Best Practices in Project Management. CEPMaW 2010. Insisoc Ed. García EE (2012) Control y monitorización de un proyecto mediante el cálculo de estimaciones obtenidas a través de la parametrización de la curva S del coste acumulado. Best Practices in Project Management. CEPMaW 2012. Insisoc Ed. Henderson K (2003) Earned Schedule: A Breakthrought Extension to Earned Value Theory? A Retrospective Analisys of Real Project Data. The Measurable News. Kim EH, Wells WG, Duffey MR (2003) A model for effective implementation of Earned Value Management methodology. International Journal of Project Management, 21: 375-382. Lipke W (2005) A Re-examination of Project Outcome Prediction using Earned Value Management Methods. Meas News. pp. 14–26. Meyer PS (1999) A Primer on Logistic Growth and Substitution: The Mathematics of the Loglet Lab Software. Technological Forecasting and Social Change, Vol. 61, No. 3, pp. 247–271. Miranda MJ, Fackler PL (2002) Applied Computational Economics and Finance. The Ohio State University & North Carolina State University. Massachusetts Institute of Technology.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Noori S, Bagherpour M, Zareei A (2008) Applying Fuzzy Control Chart in Earned Value Analysis: A New Application. World Applied Sciences Journal 3 (4): 684-690. ISSN 18184952. PMI (2008) A Guide to the Project Management Body of Knowledge. PMBOK Guide, Fourth Edition, PMI Publications, p.16. Tylor, J (2009) Project Scheduling and Cost Control (Planning, Monitoring and Cost Control). E.U.A.: J. Ross Publishing, Inc. Vitner G, Rozenes SH (2006) Using data envelope analysis to compare project efficiency in a multi-project environment. International Journal of Project Management, 24: 323-329. Weisstein E (2004) Gompertz curve. MathWorld. A Wolfram Web Resource, accessed 3.

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Aprendizaje Organizacional: Estudio de Caso Sector Turismo de Ciudad Guayana, Venezuela Organizational Learning: A Case Study of Tourism Sector of Guayana City, Venezuela. D’Armas M1, Arzola M2 Abstract In the present study, the dimensions that determine the organizational learning of the Tourism Sector in Guayana City, Venezuela, were identified by statistical methods multivariants. An instrument consisting of 33 items, was designed from the conceptual literature review. The items were associated with three levels of learning and five conditions for learning to take place. The instrument was applied to 125 workers of the Tourism Sector. The dimensions of Tourism Sector of Guayana City were identified, after demonstrating the adequacy of the data, index KMO = 0.873: learning orientation, retention and application of knowledge, mutual collaboration; learning group, shared vision, and individual learning. These six dimensions explained 75% of the total variance.

Resumen En el presente estudio se identificaron mediante métodos estadísticos multivariantes las dimensiones que determinan el aprendizaje organizacional del Sector Turismo de Ciudad Guayana, Venezuela. A partir de la revisión de la literatura conceptual se diseñó un instrumento conformado de 33 ítems. Los ítems se asociaron a tres niveles de aprendizaje y a cinco condiciones para que el aprendizaje se lleve a cabo. El instrumento se aplicó a 125 trabajadores del Sector Turismo. Previa demostración de la adecuación de los datos, índice KMO= 0.873, se identificaron las dimensiones del Sector Turismo de Ciudad Guayana: orientación al aprendizaje; retención y aplicación del conocimiento; colaboración mutua;

1Mayra

D’Armas Regnault ( e-mail: [email protected]) Centro de Desarrollo Gerencial. Dpto. de Ingeniería Industrial. UNEXPO. Edif. de Mecánica. Urb. Villa Asia. Final Calle China. Puerto Ordaz. Estado Bolívar. Venezuela. 2Minerva

Arzola Hamilton ( e-mail: [email protected]) Centro de Desarrollo Gerencial. Dpto. de Ingeniería Industrial. UNEXPO. Edif. de Mecánica Urb. Villa Asia. Final Calle China. Puerto Ordaz. Estado Bolívar. Venezuela.

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aprendizaje grupal; visión compartida; y aprendizaje individual. Estas dimensiones explican el 75% de la varianza total.

Keywords: Organizational Learning, Tourism Sector, Factor Analysis, Case Study Palabras clave: Aprendizaje Organizacional, Sector Turismo, Análisis de Factores, Estudio de Caso

1 Introducción El principal soporte de la economía venezolana es la industria petrolera seguida por las industrias básicas y minera. En Venezuela la actividad turística como fuente de ingreso siempre ha quedado relegada a un segundo plano, a pesar de poseer un gran potencial para desarrollar el Sector Turismo, debido a su favorable posición geográfica, la variedad de paisajes, la riqueza de la flora y fauna, y su clima, los cuales son recursos fácilmente aprovechables para el desarrollo de este sector. Las condiciones turísticas de Ciudad Guayana no escapan a las realidades del país, de hecho a pesar de ser una región donde convergen atractivos naturales importantes de interés mundial, el turismo no ha sido bien gestionado para sacarle el mayor provecho. En los últimos años en la región se ha venido impulsando el desarrollo del sector turismo trabajando conjuntamente gobierno y empresas privadas, sin embargo, los esfuerzos realizados no han sido suficientes por lo que es importante promover y apoyar todas las iniciativas que ayuden a mejorar el turismo local aprovechando su potencial y contribuyendo en el crecimiento regional. La actual sociedad del conocimiento plantea un reto para las organizaciones, desde la perspectiva de la asimilación de toda la información disponible, selección de aquella útil para cumplir con los objetivos y que realmente contribuya con la ventaja competitiva (Arzola, 2011). En una época de cambios y de información como la actual, el único factor permanente de ventaja competitiva de una empresa es el aprendizaje organizacional, pues éste es la base del mejoramiento y la innovación, los dos pilares de la competitividad contemporánea. Considerando la importancia del Sector Turismo para la economía venezolana, el objetivo de este trabajo fue identificar las dimensiones del aprendizaje organizacional en dicho sector. El aprendizaje organizacional es un campo de investigación académica y de práctica profesional con un desarrollo relativamente reciente. Desde 1997 se han realizado publicaciones con cuatro características: (1) asociadas al desempeño competitivo de las organizaciones; (2) la relación aprendizaje en las organizaciones y cultura organizacional; (3) temas de menor frecuencia de asociación como 1119


liderazgo, procesos interpersonales y conflictos; y (4) el uso de los términos más usados por los investigadores de aprendizaje organizacional, aprendizaje individual, organizaciones de aprendizaje, memoria organizacional y aprendizaje de equipo que buscan avalar el estado del arte en términos teóricos o empíricos. (Garzón y Fisher, 2008) Son muchas las definiciones de aprendizaje organizacional, las cuales ofrecen una aproximación distinta. De acuerdo con Castañeda y Fernández (2007), dentro de la perspectiva de cambio existen dos corrientes. La primera entiende el aprendizaje organizacional como los cambios que la entidad hace con el propósito adaptarse a su entorno. La segunda, como las acciones que las entidades hacen para transformarse y cambiar su entorno. Las organizaciones del primer tipo están preocupadas por sobrevivir y sus mayores esfuerzos se dirigen a resolver los problemas del día a día, de tal forma que se garantice su permanencia en el mercado. Las del segundo, están interesadas en intervenir su entorno de manera innovadora, para posicionar nuevos productos o nuevos servicios, primero que la competencia. Para efecto de la presente investigación se entiende por Aprendizaje Organizacional como un proceso de adquisición de nuevos conocimientos con la finalidad de alcanzar mayores niveles de competitividad a través de agregar valor a las personas y a los grupos que conforman la organización.

2 Metodología El estudio se desarrolló con el objetivo de identificar mediante métodos estadísticos multivariantes las dimensiones del aprendizaje organizacional en el Sector Turismo de Ciudad Guayana, Venezuela. El presente proyecto se realizó mediante de una investigación no experimental del tipo exploratoria y evaluativa, e incluyó técnicas de índole cualitativa, ya que se utilizó el estado del arte para la comprensión, revisión teórica e interpretación del aprendizaje organizacional en el Sector Turismo. A partir de la revisión de la literatura conceptual en cuanto a la medición del aprendizaje organizacional se diseñó un instrumento conformado de 33 ítems. Los ítems se asociaron a tres niveles de aprendizaje: individual, grupal y organizacional; y a cinco condiciones para que el aprendizaje se lleve a cabo: cultura organizacional, distribución de la información, adiestramiento, fuentes del aprendizaje y dirección estratégica. Los ítems se presentan en la escala graduada de Likert, permitiendo al encuestado posicionarse en opciones que van desde el 1 al 5, donde 1 representa total desacuerdo y 5 total acuerdo. El instrumento se aplicó en los hoteles y posadas de Ciudad Guayana, mediante un Muestreo Casual donde únicamente se determina el tamaño de la muestra, pero los integrantes se seleccionan sin ningún criterio establecido. Se tomó como muestra el 30% de las empresas del sector y se aplicó el instrumento a 125 trabajadores. 1120


El análisis de los datos se realizó con ayuda de los paquetes EXCEL® y SPSS®. Además, se realizaron las respectivas pruebas de adecuación muestral de los datos disponibles y las pruebas para determinar la fiabilidad y validez de la encuesta para el caso en estudio.

3 Instrumento de Medición del Aprendizaje Organizacional El aprendizaje organizacional ha sido estudiado desde diferentes perspectivas, niveles y condiciones. El Modelo de Crossan, Lane y White (1999) plantea que el aprendizaje organizacional consta de tres niveles: individual, grupal y organizacional; y en dos vías: del individuo a la organización y de la organización al individuo. Senge (1992) plantea que el aprendizaje organizacional es un proceso colectivo que requiere de condiciones para que ocurra; y que para que tal aprendizaje se produzca es necesario contar con: dominio personal, modelos mentales, visión compartida, trabajo en equipo y pensamiento sistémico. De acuerdo con la revisión de la literatura conceptual en la medición del aprendizaje organizacional Garzón y Fisher (2010), Castañeda y Fernández (2007), Mayorca y Viloria (2007), Pérez et al (2005), Lloria et al (2004), Ordoñez (2002), Goh (2001), Martínez et al (2001), se puede concluir que a pesar de la diversidad de enfoques existe un relativo acuerdo en que éste se da en tres niveles: individual, grupal y organizacional. Sin embargo, sobre las condiciones para que el aprendizaje ocurra se encontró que los planteamientos son distintos y que no existe consenso. De esta manera, mediante la pertinente adaptación de algunos ítems de las escalas estudiadas y de la generación de unos nuevos, y después de varias revisiones el instrumento quedó conformado de 33 ítems. Los ítems están asociados a tres niveles de aprendizaje: individual, grupal y organizacional; y a las condiciones para que el aprendizaje se lleve a cabo. Para efectos de esta investigación, las condiciones que deben ser consideradas y utilizadas en el Sector Turismo para impulsar el aprendizaje organizacional se clasificaron en

cultura organizacional, distribución de la información, adiestramiento, fuentes del aprendizaje y dirección estratégica. La dimensión Cultura Organizacional expresa el esfuerzo de la organización para incentivar el aprendizaje y el propósito que las personas tienen sobre el logro del aprendizaje organizacional. La dimensión Distribución de la Información manifiesta los medios que utiliza la empresa para gestionar el conocimiento, así como la difusión del conocimiento a todos los empleados de la organización. La dimensión Adiestramiento muestra el interés de la empresa en crear oportunidades para el aprendizaje continuo para todos sus empleados. La dimensión Fuentes del Aprendizaje refleja el esfuerzo de la empresa para establecer y mantener sistemas de tecnología para obtener conocimiento de manera eficiente y compartir el conocimiento y el aprendizaje. La dimensión Dirección Estratégica indica el grado en 1121


el cual los dirigentes de la empresa utilizan de manera estratégica el aprendizaje para el logro de los objetivos propuestos y se constituyen en modelos a seguir.

4 Resultados

4.1 Análisis de Fiabilidad La fiabilidad se refiere a la estabilidad de las mediciones cuando no existen razones teóricas ni empíricas para suponer que la variable a medir haya sido modificada diferencialmente por los sujetos, por lo que se asume su estabilidad mientras no se demuestre lo contrario. Para realizar el análisis de fiabilidad del instrumento usado, se utilizó el modelo de consistencia interna de Cronbach, el cual asume que la escala está compuesta por variables homogéneas que miden la misma característica y que la consistencia interna de la escala puede evaluarse mediante la correlación existente entre todas sus variables. El Alfa de Cronbach obtenido fue de 0,961 lo cual indica una alta homogeneidad y equivalencia de respuesta entre todos los ítems a la vez y para todos los encuestados.

4.2 Análisis Factorial Como primer paso del Análisis Factorial se obtuvo la matriz de correlaciones mediante el SPSS. Uno de los requisitos que deben cumplirse para que el análisis factorial tenga sentido es que las variables estén altamente correlacionadas. Los determinantes próximos a cero indican que las variables utilizadas están linealmente relacionadas, lo que significa que el análisis factorial es una técnica pertinente para analizar esas variables. Para el caso en estudio, el valor del determinante es 1,32.10-6 este valor es pequeño, lo cual es un buen dato desde el punto de vista de la idoneidad del análisis. Del test de esfericidad de Bartlett, con un valor de 3625,99 con un nivel de significancia α=0,05, se rechaza la hipótesis nula de ausencia de correlación significativa entre las variables; lo que permite la aplicación del análisis factorial. El Índice KMO Kaiser-Meyer-Olkin es muy útil cuando el tamaño muestral es pequeño, según las salidas del SPSS se obtuvo un KMO= 0,873 por lo que existe un nivel meritorio de calidad para el índice, lo que es suficiente para continuar con la aplicación del análisis factorial a los datos en estudio.

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4.2.1 Análisis de los Componentes Principales Una vez demostrada la adecuación de los datos para la aplicación de dicho análisis, se procedió a buscar los factores mediante el método de extracción de componentes principales para representar los datos originales. Se utilizó el criterio de Kaiser el cual indica conservar solamente aquellos factores cuyos valores propios son mayores a la unidad. El SPSS versión18, utiliza este criterio por defecto. En la Tabla 1, se muestra que existen seis (6) componentes con valores propios mayores a uno, entre los cuales se acumula un 75,08% de la varianza total explicada. Tabla 1 Varianza total explicada, seis (6) factores Componente

Autovalores iniciales Valor Propio Total

% Varianza Total

% Acumulado

1

15,276

46,291

46,291

2

3,989

12,088

58,379

3

1,860

5,636

64,015

4

1,414

4,284

68,300

5

1,193

3,615

71,915

6

1,045

3,166

75,080

4.2.2 Matriz de Componentes Extraídos Como resultado inicial del análisis factorial, se obtuvo la matriz de correlaciones entre variables y componentes. Los resultados del modelo experimental obtenido por el SPSS, arrojaron una distribución de variables que no obedecía a lo mostrado por el modelo propuesto de Ocho (08) dimensiones. Además, se encontró una saturación de todas las variables en el primer factor, y que el tercer y el cuarto factor no agrupaban ninguna variable. Debido a esto se aplicó una rotación Varimax, que es un método de rotación ortogonal que minimiza el número de variables que tienen saturaciones altas en cada factor y simplifica la interpretación de los mismos optimizando la solución por columna. Se puede observar en la Tabla 2, que la Matriz de componentes rotados Varimax posee una agrupación particular de Seis (06) factores, con variables que saturan significativa en diferentes factores. El primer factor agrupa las variables: V13, V16, V20, V22, V25, V26, V27, V28, V30, V32, V33 (conocimiento de los trabajadores, colaboración mutua, los medios de información son eficientes, existencia de prácticas operativas, informes, manuales, normas y otros, cursos de inducción al ingresar a la empresa, se utiliza soporte tecnológico, acceso a la tecnología computarizada, acceso a fuentes externas de información, buenas oportunidades de aprendizaje) y es identificado como: Orientación al aprendizaje. El segundo factor agrupa las variables: V10, V11, V19, V24, V29, V31 (se 1123


aplica el conocimiento con que cuenta la empresa, la empresa aprende en el tiempo requerido adaptándose a los cambios del entorno, los jefes informan sobre las reuniones y eventos, los jefes brindan el apoyo para las oportunidades de aprendizaje y entrenamiento, la capacitación recibida se aplica al trabajo, existen prácticas operativas, manuales, normas y procedimientos) y es identificado como: Retención y aplicación del conocimiento. Tabla 2 Resultados de la Matriz de Componentes rotados VARIMAX

V01 Se aprende de las experiencias.

01 0,043

02 0,511

Componente 03 04 0,563 -0,182

05 06 0,031 0,243

V02 Se aprende observando a los compañeros de trabajo.

0,287

0,297

0,438

0,597

0,201 0,044

V03 Se produce conocimiento ensayando y probando.

0,067

0,576

0,075

0,504

0,025 0,516

V04 Se aprende de la documentación disponible en la empresa.

0,055

0,428

0,195

0,004

0,085 0,817

V05 Se recibe ayuda de las personas en la empresa.

0,359

0,096

0,722

0,249

0,016 -0,157

V06 Se aprende mediante el diálogo con otros trabajadores.

0,417

0,216

0,245

0,602 0,131 0,023

V07 Se intercambia conocimiento libremente en grupo.

0,530

0,301

0,059

0,553 -0,029 -0,042

V08 Todos se ayudan en el proceso de aprendizaje. Las ideas se generan como resultado de las discusiones en V09 grupo y por la información recogida por el grupo. V10 Se aplica el conocimiento con que cuenta la empresa. La empresa responde a los cambios del entorno aprendienV11 do en el tiempo requerido. Se mejoran los procesos con base en el conocimiento de V12 los trabajadores. Se generan nuevos productos o servicios en base al conoV13 cimiento de los trabajadores. La empresa promueve situaciones para que los trabajadores V14 intercambien conocimiento. V15 La empresa reconoce a los trabajadores que son proactivos. Colaboración mutua de forma voluntaria aunque no forme V16 parte de las funciones. La empresa actúa según las recomendaciones de los trabaV17 jadores Acceso a la información en cualquier momento rápida y V18 fácilmente. V19 Los jefes informan de las reuniones y los eventos

0,209

0,328

0,740

0,189 0,166 0,114

V20 Los medios para compartir la información son eficientes. Cuando se solicita información laboral a otro compañero V21 de trabajo ésta se obtiene en el tiempo requerido. Disponibilidad de prácticas operativas, informes, manuaV22 les, normas y procedimientos. V23 Todos los trabajadores reciben cursos de adiestramiento.

Variable

0,171

0,178

0,655

0,318

0,330 0,167

0,134

0,809

0,117

0,144

-0,025 0,287

0,129

0,653

0,432

0,291

0,138 0,116

0,186

0,426

0,588

0,219

0,037 0,157

0,605

0,180

0,464

0,303

-0,079 0,022

0,468

0,047

0,471

0,386

0,388 0,225

0,358 -0,042

0,395

0,469

0,461 0,221

0,736

0,031

0,320

0,295

0,253 0,042

0,191

0,571

0,014

-0,011

0,652 0,062

0,272

0,207

0,222

0,137

0,742 0,011

0,135

0,838

0,113

-0,115

0,157 0,109

0,756

0,089

0,267

0,081

0,158 0,164

0,468

0,056

0,621

0,046

0,076 0,267

0,511

0,204

0,486

0,453

0,098 -0,034

0,345

0,306

0,729

-0,054

0,143 -0,045

V24 La capacitación recibida en la empresa se aplica al trabajo. -0,024

0,739

0,416

0,244

-0,010 0,027

0,741 -0,066

0,360

-0,061

0,036 0,079

0,675

0,143

0,462

0,295

0,222 -0,016

0,741

0,226

0,206

-0,130

0,272 0,120

0,664

0,095

0,283

0,225

0,365 -0,172

V25 Siempre se recibe inducción de la empresa al ingresar. Se utiliza soporte tecnológico para procesar y consultar la V26 información de los clientes y de la competencia. Existe acceso a tecnología computarizada para enviar y reV27 cibir información. Las fuentes externas (informes, consultores, periódicos, V28 etc.) son muy importantes para las operaciones.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 2 (continued) Resultados de la Matriz de Componentes rotados VARIMAX Variable V29 V30 V31 V32 V33

Existen prácticas operativas, informes, manuales, normas y procedimientos, etc. Los dirigentes comparten información sobre la competencia, tendencias y líneas directrices de la empresa. Los dirigentes brindan el apoyo necesario para las oportunidades de aprendizaje y entrenamiento. Los dirigentes buscan oportunidades de aprendizaje tanto para ellos como para los trabajadores. Los dirigentes de esta organización consideran el impacto de las decisiones en la moral de los trabajadores.

Componente 03 04

01

02

0,234

0,683

0,286

0,075

0,171 -0,056

05

06

0,738

0,196

0,099

0,407

0,133 -0,149

0,115

0,729

0,031

0,291

0,155 0,006

0,852

0,247

0,007

0,153

-0,025 0,073

0,871

0,069

0,076

0,186

0,099 -0,004

El tercer factor agrupa las variables: V01, V05, V08, V09, V12, V21, V23 (se aprende de las experiencias, se recibe ayuda de las personas en la empresa, todos se ayudan en el proceso de aprendizaje, las ideas se generan como resultado de las discusiones en grupo, e mejoran los procesos con base en el conocimiento de los trabajadores, cuando se solicita información laboral a otro compañero de trabajo ésta se obtiene en el tiempo requerido) y es identificado como: Colaboración mutua. El cuarto factor, agrupa las variables: V02, V06, V07 (se aprende observando a los compañeros, se aprende mediante el diálogo con otros trabajadores, se intercambia conocimiento libremente en grupo) y es identificado como: Aprendizaje grupal. El quinto factor agrupa las variables: V17 y V18 (confianza en que la empresa actúa según las recomendaciones de los trabajadores, la información que se necesita se consigue en cualquier momento rápida y fácilmente) y es identificado como: Visión compartida. Finalmente, el sexto factor agrupa las variables: V03 y V04 (en la empresa se produce conocimiento ensayando y probando, se aprende de la documentación disponible en la empresa) y es identificado como: Aprendizaje individual.

4.3 Nivel de la Aprendizaje Organizacional Para conocer en qué nivel se encuentra el Aprendizaje Organizacional del Sector Turismo de Ciudad Guayana, el resultado que se debe extraer de los datos, es el promedio total de las treinta y tres (33) variables que miden el Aprendizaje tal y como se muestra en la siguiente expresión, donde n  33 y Vi es el promedio de la variable i: N

Nivel 

Vi i 1

N

1125


Este promedio arrojó un valor de 3,39 aproximadamente; en una escala que va del uno (1) al cinco (5). Este valor se encuentra por encima de la mediana de la escala que es igual a tres (3), valor que señala un nivel aceptable de aprendizaje.

5 Conclusiones En este trabajo se identificaron mediante métodos estadísticos multivariantes las dimensiones que determinan el aprendizaje organizacional en el Sector Turismo de Ciudad Guayana, Venezuela. Se diseñó un instrumento, el cual se aplicó a una muestra constituida por 12e trabajadores del Sector Turismo de Ciudad Guayana, determinado para una población infinita, desviación estándar desconocida, nivel de confianza de 95 % y una precisión de un 8%. Técnicamente el procedimiento de selección de la muestra se realizó de manera no aleatoria e intencional, determinándose que es adecuada, lo que queda demostrado en los resultados de las Pruebas de Validez y Fiabilidad realizadas al mismo (alfa de Cronbach= 0,961). El análisis de factores permitió identificar seis (6) dimensiones de interés en el aprendizaje organizacional: (1) Orientación al aprendizaje; (2) Retención y aplicación del conocimiento; (3) Colaboración mutua; (4) Aprendizaje grupal; (5) Visión compartida; y (6) Aprendizaje individual. Finalmente, los resultados indican que el nivel de aprendizaje organizacional del Sector Turismo de Ciudad Guayana es de 3.39, en una escala del 1 al 5, lo cual demuestra un nivel aceptable de aprendizaje.

6 Referencias Arzola M. (2011) Evaluación del Aprendizaje en el Sector de Consultoría de Ciudad Guayana, Venezuela. Revista Ingeniería Industrial. Actualidad y Nuevas Tendencias. Vol. II, N° 5, p. 23-36. Castañeda D. y Fernández M. (2007) Validación de una escala de niveles y condiciones de aprendizaje organizacional. Universitas Psicológicas, Vol. 6, N° 2, p.245-254 Crossan, M., Lane, H. y White, R. (1999). An organizational learning framework: From intuition to institution. Academy of Management Review, Vol. 24, N°3, p. 522-537. Garzón M. y Fisher A. (2010) El aprendizaje organizacional, prueba piloto de instrumentos tipo Likert. Forum Empresarial. Vol. 15, N° 1, pp. 65-101 Garzón M. y Fisher A. (2008). Modelo Teórico de Aprendizaje Organizacional. Revista Pensamiento y Gestión. N° 24, p. 195-224 Goh S. (2001). The learning organization: an empirical test of a normative perspective. International Journal of Organization Theory an Behavior. Vol. 4, N° 4, p. 329-356 Lloria M., Moreno M. y Persis F. (2004). Diseño y validación de una escala para medir el aprendizaje en las organizaciones. Universidad de Valencia. 23p Martínez I., Ruiz J. Ruiz C. (2001) Aprendizaje organizacional en PYMEs. XI Congreso Nacional de la Asociación Científica de Economía y Dirección de la Empresa (ACEDE). Zaragoza.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. España. p. 1-22. Mayorca R., Ramírez J., Viloria O. y Campos J. (2007) Evaluación de un cuestionario sobre organizaciones que aprenden: adaptación, validez y confiabilidad. Revista Venezolana de Análisis de Coyuntura. Vol. 13, N° 2, p. 149-164 Ordoñez P. (2002). Knowledge Management and Organizational Learning: Typologies of Knowledge Strategies in the Spanish Manufacturing Industry from 1995 to 1999. Journal of Knowledge Management, Vol. 6, p. 52-62. Pérez S., Montes J. y Vásquez C. (2005). Human Resources Practices, Organizational Learning and Business Perfomance. Human Resource Development International, Vol. 8, p. 147-164. Senge, Peter M. (1992): La quinta disciplina. El arte y la práctica de la organización abierta al aprendizaje; Trad. Carlos Gardini; Buenos Aires, Arg.; Coed. Juan Granica y Javier Vergara.

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Gestión de la Innovación y el Papel de las TIC: El caso de SILK Crowdsourcing Influence in the Processes of Organizations Planuch Prats C1, Salvador Vallès R Abstract This paper analyzes the impact of information and communication technologies (ICTs), and particularly the Web 2.0 tools, on innovation and processes in the company SILK (CaixaBank Information Systems).

Resumen Este artículo analiza la incidencia que, sobre la innovación y los procesos en la empresa SILK (Sistemas Informáticos de CaixaBank), tienen factores como las tecnologías de la información y comunicación (TIC) y las herramientas Web 2.0.

Palabras clave: Web 2.0, Innovación Abierta (IA), Procesos, Tecnologías de la Información y Comunicación (TIC). Keywords: Web 2.0, Open Innovation, Business Processes, Information and Communication Technology (ICT).

1 Introducción En un entorno económico complejo, en 2011 se completó el proceso de reorganización de “La Caixa”, por el cual CaixaBank ha pasado a ejercer la actividad financiera del grupo. SILK, la empresa tecnológica del grupo, juega un papel determinante para los objetivos de la entidad. El propósito del trabajo es analizar la influencia de las herramientas Web 2.0, y el rol de las TIC en SILK, durante el período 2007-2012.

1Carles Planuch Prats ( e-mail: [email protected]) Dpto. de Lenguajes y Sistemas Informàticos. Universitat Politècnica de Catalunya, Barcelona.

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El presente trabajo se estructura de la forma siguiente: en primer lugar, se describe la metodología aplicada en el punto 1. Posteriormente, se presentan las principales características de la organización a analizar en el punto 2. En el punto 3 se plantean las hipótesis sobre la influencia de las herramientas Web 2.0 en la innovación y en los procesos de SILK (una empresa del sector de servicios TIC), y por último, se propone un breve comentario de los resultados obtenidos en el punto 4. Finalmente se presentan las conclusiones más importantes obtenidas a partir del análisis de la información.

2 Metodología La metodología aplicada en la investigación relacionada con el presente trabajo es de tipo cualitativo. Más concretamente, se utiliza la estrategia del estudio de caso, debido a las grandes posibilidades que presenta en la investigación y explicación de fenómenos contemporáneos ubicados en su entorno real (Yin, 1989; Eisenhardt, 1989).

2.1 Ventajas e inconvenientes del estudio del caso Kingsley y Bozeman (1997) resumen las principales ventajas del estudio de casos como técnica de investigación:  Los estudios de casos proporcionan al investigador una gran cantidad de información sobre el fenómeno analizado, característica que ha sido destacada también por Platt (1992), entre otros.  Aunque los estudios de casos pueden ser utilizados en cualquier fase de conocimiento del fenómeno a analizar, no es menos cierto que son especialmente adecuados cuando nuestro conocimiento es escaso, o cuando se desea llegar a una teoría explicativa del fenómeno.  El estudio de caso se considera una herramienta muy útil para el aprendizaje de un determinado fenómeno.  Es una técnica enormemente flexible, al permitir que el investigador modifique sus procedimientos de investigación a lo largo del estudio, como consecuencia de la interacción con quien está siendo investigado. Frente a este amplio abanico de ventajas, sus detractores han concentrado sus críticas en los problemas de objetividad y generalización. Con independencia de la aplicación de técnicas específicas de análisis, la mayoría de los autores han explicado de modo convincente temas como: la investigación cualitativa (Gephart, 2004), la construcción de la teoría fundamentada (Suddaby, 2006), el valor de la 1129


riqueza (Weick, 2007), y el poder persuasivo del único caso (Siggelkow, 2007) mediante dicha metodología.

2.2 Justificación de la Metodología El estudio del caso se ha utilizado para desarrollar investigación en aspectos tan diversos como el proceso en grupo (Edmondson, Bohmer, y Pisano, 2001), la organización interna (Galunic y Eisenhardt, 2001; Gilbert, 2005) y la estrategia (Mintzberg y Waters, 1982). Estudiosos clásicos como Chandler (Chandler, 1962; Whyte, 1941), así como los autores de gran prestigio que han publicado artículos en la AMJ (Academy of Management Journal), y Dutton (Dutton y Dukerich, 1991; Sutton y Rafaeli, 1988) han utilizado dicho método. En efecto, los documentos que construyen la teoría de los casos se consideran a menudo como los más interesantes de la investigación (Bartunek, Rynes, e Ireland, 2006). Además, se encuentran entre los artículos más citados en AMJ (por ejemplo, Eisenhardt, 1989; Gersick, 1988), con un enorme factor de impacto. No es de extrañar entonces, que los autores ganadores del premio al mejor artículo en la AMJ (Ferlie, Fitzgerald, Wood, y Hawkins, 2005; Gilbert, 2005) se basaran en este método. En definitiva, el estudio de caso es la técnica de investigación más adecuada cuando intentamos responder a las preguntas cómo y por qué ocurre un determinado fenómeno, cuando el investigador no tiene control sobre el fenómeno a estudiar y cuando éste es actual. En el presente trabajo, nos centramos en la estrategia de investigación relacionada con la construcción de la teoría de los casos, concretamente en el caso de SILK.

3 SILK e Hipótesis de Investigación Serveis Informàtics La Caixa S.A. (SILK) es una empresa del grupo CaixaBank, S.A., creada para convertirse en la empresa de tecnología del grupo, y para posicionarlo a la vanguardia de ésta, contribuyendo a la excelencia de los servicios ofrecidos a sus clientes. La empresa ha sido constituida aprovechando años de experiencia de profesionales del área técnica de canales electrónicos de CaixaBank. Esta experiencia, unida a la innovación que caracteriza a la entidad y a la incorporación de nuevos profesionales del sector, ha dado como resultado a SILK, una empresa puntera dentro del sector de la tecnología. Con unos 50 colaboradores, la misión principal de SILK consiste en dar soporte a la consecución de los objetivos estratégicos de CaixaBank, mantener los mayores niveles de calidad y servicio al negocio. Asimismo, pretende mejorar la efi1130


ciencia y la productividad en el uso de la tecnología, especialmente las TIC, mediante una gestión eficaz de los recursos. Los objetivos de SILK se basan en resolver las necesidades de CaixaBank mediante TIC e innovación. El único cliente de SILK es CaixaBank, quien tras la integración de Banca Cívica (con fecha 3/8/2012, y constituida por Caja Navarra, Caja Canarias, Caja Burgos y Cajasol), se ha consolidado como la entidad líder del mercado español con unos activos de 348.294 millones de euros. Además, posee una cuota de penetración de clientes del 26,1% en banca de particulares (22,2% de penetración como primera entidad), unos 13 millones de clientes, y muestra una marcada vocación por la innovación, para ofrecer los servicios más punteros a los clientes de CaixaBank.

3.1 Características e hipótesis del estudio. Uno de los retos de la empresa 2.0 es la gestión de la información que todos sus colaboradores pueden volcar, desde intranets sociales hasta la creación de wikis y blogs. Esto es posible, ya que tienen a su alcance una gran diversidad de aplicaciones y herramientas Web 2.0 con las que pueden generar conocimiento para la empresa, así como mejorar en aspectos como:  Gestión de la innovación  Desarrollo de productos  Mejora de procesos Nuestras hipótesis se basan en que las aplicaciones Web 2.0 permiten la creación de comunidades virtuales donde se acumula conocimiento. Por tanto: H1a: El aumento del grado de utilización de herramientas Web 2.0 mejora la gestión de la innovación de la empresa. H1b: El aumento del grado de utilización de herramientas Web 2.0 incrementa el desarrollo de productos de la empresa. H1c: El aumento del grado de utilización de herramientas Web 2.0 optimiza los procesos de la empresa. Las ventajas de la cooperación van en aumento en la era de la innovación abierta. La comunidad académica comenzó haciendo hincapié en que las empresas deben estar abiertas a la innovación desde fuera de la empresa (por ejemplo, Rigby y Zook, 2002; Christensen et al, 2005). Por otro lado, “No todas las personas inteligentes trabajan para nosotros. Nosotros necesitamos trabajar con gente inteligente dentro y fuera de nuestra empresa” (Chesbrough, 2003). Por todo ello podemos afirmar que: H2: El aumento del grado de utilización de nuevas tecnologías propicia un incremento de la innovación técnica.

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Desde la perspectiva del efecto sobre los procesos (Chesbrough et al, 2007.) podemos pensar en que: H3: El grado de utilización de las nuevas tecnologías propicia un incremento de la innovación en los procesos internos y/o externos. El presente trabajo pretende validar las hipótesis citadas anteriormente mediante un estudio cualitativo, en el período 2007-2012, obteniendo la información necesaria tras diversas entrevistas a los responsables de los departamentos de innovación y de gestión multicanal de SILK, S.A.

4 Estudio del Caso SILK Tratando de validar las hipótesis planteadas en el apartado anterior, referentes al efecto que sobre la innovación en SILK tienen factores como las herramientas Web 2.0, la influencia sobre la innovación en sus procesos y las propias mejoras en los procesos, se han organizado las entrevistas orientadas a los tres ámbitos siguientes, mencionados en 2.1: 1. Herramientas y aplicaciones TIC (Web 2.0) 2. Influencia sobre la innovación 3. Mejoras en los procesos El grado de utilización de herramientas y aplicaciones TIC (Web 2.0) en SILK es actualmente elevado, y si consideramos a CaixaBank, la empresa cliente, el grado de utilización es aún mayor, con un incremento muy significativo de uso de herramientas, como blogs corporativos y comunidades de clientes. Es el caso de Club ARA, que consiste en una red social de clientes mayores de 65 años para relacionarse entre sí y compartir contenidos con otros miembros de la comunidad. El principal objetivo del Club ARA es elevar la atención sobre dicho colectivo, muy importante para la entidad, ya que actualmente CaixaBank cuenta con 1,8 millones de clientes mayores de 65 años. Según un estudio de mercado del comportamiento financiero de los particulares 2011, realizado por la consultora especializada FRS Inmark, CaixaBank tiene una cuota de mercado del 13,7% de clientes mayores de 65 años. El objetivo de la entidad es alcanzar una cuota de mercado del 20% en 2014. La utilización de la tecnología implementada en SILK va dirigida a la gestión multicanal dentro de CaixaBank, de modo que el cliente puede realizar todas las operaciones en cualquier momento (ya sea a través de la red de cajeros, presencialmente en las oficinas, por videoconferencia vía RDSI, teléfono móvil, tablet o smart tv o mediante la web “Línia Oberta”). De modo que se ha conseguido que el cliente sea autosuficiente, y por tanto se minimizan costes para la compañía. Aunque también cuenta con la implantación pionera a nivel mundial de la tecnología

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“Contactless” para cajeros, situando Barcelona como la primera ciudad europea donde se pueden operar pagos contactless. La influencia sobre la innovación en SILK es realmente significativa. Prueba de ello es el volumen de inversión en I+D en SILK, que es de unos 300.000 euros anuales. De nuevo, si observáramos el volumen para CaixaBank, estaríamos por encima de los 600.000 euros anuales, de modo que se trata de un grupo donde la inversión en I+D es un factor clave para su modelo de negocio. El modelo de gestión de la innovación de SILK consiste, básicamente, en un modelo de innovación abierta (Chesbrough, 2003) con HP e IBM, sus proveedores tecnológicos. Se basa en la creación de un fondo económico de I+D, alimentado por el 2% de la facturación de todos los proyectos tecnológicos colaborativos. Además, este modelo le ha permitido desplegar más de 100 nuevos productos a CaixaBank, y desarrollar numerosas patentes en el diseño de cajeros automáticos vía Fujitsu, la empresa proveedora a tal efecto. De todo lo citado, se deduce que las TIC juegan un papel realmente relevante en la innovación de la compañía. Un papel únicamente limitado a nivel económico por los recientes movimientos estratégicos de CaixaBank, citados anteriormente en referencia a Banca Cívica. En el ámbito concreto de la innovación en los procesos, el efecto de la utilización de herramientas Web 2.0 en los procesos internos de la empresa ha sido muy importante. Por ejemplo, antes de la llegada de la Web 2.0 a SILK era el departamento de calidad, dentro de organización y métodos el responsable de gestionar las incidencias de CaixaBank. Actualmente, se ha desarrollado e implementado la aplicación GIC (Gestión de Incidencias y Consultas) con HP como proveedor tecnológico que, basado en la metodología ITIL (Information Technology Infrastructure Library). Se trata de un conjunto de conceptos y prácticas para la gestión de servicios de TIC, el desarrollo de tecnologías de la información y las operaciones relacionadas con la misma en general. ITIL proporciona descripciones detalladas de un extenso conjunto de procedimientos de gestión, ideados para ayudar a las organizaciones a lograr calidad y eficiencia en las operaciones TIC. Estos procedimientos son independientes del proveedor y han sido desarrollados para servir como una guía que abarque toda infraestructura, desarrollo y operaciones de TIC. Además, permite un control exhaustivo de la gestión incidental, controlando y monitorizando la duración de la resolución de una incidencia desde el programa, servidor, aplicación y/o proveedor afectado en la resolución de la misma. Permite incluso establecer un horario de actuación para no influir en los procesos batch (procesos diferidos) de CaixaBank o con la actividad diaria de la entidad. Otro proyecto de I+D, con un importante contenido Web 2.0, desarrollado en colaboración con IBM ha sido el “Fes-te client” (“Hazte cliente”). Es un proyecto para la captación de nuevos clientes vía Internet, basado en la metodología BPM (Business Process Management – Gestión de Procesos de Negocio: se trata de un conjunto de disciplinas empresariales, basadas en enfoques metodológicos, aplicadas con el fin de mejorar la eficiencia a través de la gestión de los procesos, reglas 1133


y servicios del negocio, que se deben modelizar, automatizar, integrar, monitorizar y mejorar de forma continua). En este caso, la mecanización del proceso ha consistido en controlar miles de millones de transacciones anualmente. No se ha dejado ninguna posibilidad o alternativa del cliente potencial al azar, y permite certificar el éxito del proceso al dar de alta a un nuevo cliente a través de la web de CaixaBank. Se trata además, de una aplicación auditable por el Banco de España (quien evalúa a las entidades financieras por el número de incidencias), y consultable por el cuerpo de Policía Nacional para controlar los ataques por parte de los hackers a que se ve sometida la web corporativa. Por todo esto, ha llegado convertirse en un brillante exponente del efecto de las tecnologías web 2.0 en CaixaBank.

5 Discusión Una vez realizadas las entrevistas, resulta evidente pensar que tanto en SILK, y por extensión en CaixaBank, la innovación es un punto fuerte. Son empresas donde la I+D con el soporte de las TIC, constituye una de las core competences del grupo. Se ha observado que el aumento del grado de utilización de las TIC, durante el periodo 2007-2011 ha propiciado el desarrollo y la implantación de la tecnología contactless para cajeros, donde se pueden operar pagos contactless validando H1a. La creación de más de 100 nuevos productos financieros, confirma la validez de H1b. Además, se ha producido un incremento de la innovación técnica. Por un lado, por la implementación de proyectos creativos llevados a cabo dentro de SILK para aumentar el volumen de conocimientos y su posterior utilización para idear productos nuevos o mejorados, incluyendo el desarrollo de software. Por otro, por las mejoras continuas en el servicio web de “Línia Oberta” por ejemplo, confirmando así la hipótesis H2. Además, el incremento de las inversiones en tecnología en SILK que se han realizado durante el último quinquenio, se han correspondido con mejoras en los procesos citados (BPM, Fest-te Client, GIC), confirmando las hipótesis H1c y H3.

6 Conclusiones Las herramientas Web 2.0 contribuyen de manera significativa en el modelo de negocio de SILK, mejorando la gestión multicanal con el cliente, favoreciendo la creación de comunidades de clientes, el Club ARA, e implementado la tecnología contactless para los cobros en cajeros y comercios. La I+D constituye un factor clave para el grupo CaixaBank y, asimismo, ha permitido desarrollar más de 100 nuevos productos financieros, numerosas patentes en cajeros automáticos (Fujitsu) 1134


y proyectos de innovación abierta con HP. Desde el punto de vista de los proyectos, la implantación de la aplicación GIC para la gestión de incidencias y la mecanización del proceso de captación de clientes, “Fes-te client”, basado en la metodología BPM, completan las aportaciones tanto de la herramientas Web 2.0 como de la innovación y los procesos para SILK. La única limitación para SILK no procede de aspectos organizativos ni tecnológicos, sino que resulta de aspectos económicos derivados del proceso de restructuración del sistema financiero español. En concreto, del llevado a cabo por CaixaBank, con la reciente integración de Banca Cívica que, unida a las previas de Caixa Girona y Bankpime, limitan el presupuesto de SILK en relación a la inversión en TIC y su influencia en la innovación.

7 Referencias Bartunek JM., Rynes, SL., Ireland, RD. (2006) What makes management research interesting and why does it matter? Academy of Management Journal, 49: 9–15. Chandler AD. (1962) Strategy and structure. Cambridge, MA: MIT Press. Chesbrough, HW. (2003) Open Innovation: The New Imperative for Creating and Profiting from Technology. Cambridge, MA: Harvard Business School Publishing. Chesbrough, HW. Vanhaverbeke W West J (2007) Open Innovation. Researching a New Paradigm. Oxford: University Press. Dutton, JE., Dukerich, JM. (1991) Keeping an eye on the mirror: The role of image and identity in organizational adaptation. Academy of Management Journal, 34: 517–554. Dittrich K. Duysters G. (2007) Networking as a means to strategy change: the case of open innovation in mobile telephony. Journal of Product Innovation Management, 24, 6, 510–521. Edmondson AC., Bohmer, RM., Pisano, GP. (2001) Disrupted routines: Team learning and new technology implementation in hospitals. Administrative Science Quarterly, 46: 685–716. Eisenhardt KM. (1989), Building theories from case study research, Academy of Management Review, Vol.14, No, 4, 532-550. Ferlie E., Fitzgerald, L., Wood, M., Hawkins C. (2005) The nonspread of innovations: The mediating role of professionals. Academy of Management Journal, 48: 117–134. Galunic DC., Eisenhardt, KM. (2001) Architectural innovation and modular corporate forms. Academy of Management Journal, 6: 1229–1249. Gephart RP. (2004) Qualitative research and the Academy of Management Journal. Academy of Management Journal, 47: 454–462. Gersick CJG. (1988) Time and transition in work teams. Toward a new model of group development. Academy of Management Journal, 31: 9–41. Kingsley G; Bozeman B. (1997) R&D value-mapping: a new approach to case study based evaluation. Journal of Technology Transfer, Vol. 22, No. 2, pp. 33-42. Mintzberg H., Waters, JA. (1982) Tracking strategy in an entrepreneurial firm. Academy of Management Journal, 25: 465–499. Platt, J. (1992) Case study in American methodological thought. Current Sociology, Vol 40, No.1, spring, pp. 17-48. Siggelkow, N. (2007) Persuasion with case studies. Academy of Management Journal, 50: 20– 24. Suddaby, R. (2006) What grounded theory is not. Academy of Management Journal, 49: 633– 642.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Sutton, RI., Raphaeli, A. (1988) Untangling the relationship between displayed emotions and organizational sales: The case of convenience stores. Academy of Management Journal, 31: 461–487. Weick, KE. (2007) The generative properties of richness. Academy of Management Journal, 50: 14–19. Whyte, WF. (1941) Corner boys: A study in clique behavior.American Journal of Sociology, 46: 647– 664. Yin, R. (1994), Case study research. Design and methods (second edition). Sage Publications. Newbury Park, CA.

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La Intragestion Financiera a través de las TIC Basada en la Auditoria de Orden del Sector Universitario Venezolano The Financial Intragestion through ICT Audit Based on Order of a Venezuelan University Sector Guaido Suarez D1 Abstract University institutions forming and organizing the knowledge required to be pioneers in the application of innovative ideas, the use of ICT is required to simplify and control and optimize resources. The order provides audit assessment and improvements to optimization. Com-parative diagnosis national and international university processes in human Intragestion comprehensive knowledge with ICT systems. Field research and project, interview technique, qualitative nondirective until data saturation. Training consists of three levels, implementation and optimization. Your application has been effective organizations and universities co first level has begun to bear fruit.

Resumen Las instituciones universitarias formadoras y organizadoras del conocimiento requieren ser pioneras en la aplicación de ideas innovadoras, el uso de las TIC se requiere para simplificar y controlar los recursos y optimizarlos. La auditoria de orden provee evaluación y mejoras hasta la optimización. Diagnostico comparativo nacional e internacional de procesos universitarios en Intragestion del conocimiento integral humano con sistemas TIC. Investigación de campo y proyecto, técnica de la entrevista, cualitativa no directiva, hasta la saturación de datos. Consta de tres niveles formación, aplicación y optimización. Su aplicación en organizaciones ha sido efectiva y en las universidades su primer nivel ha comenzado a dar frutos.

1Dacmile Guaido Suarez ( e-mail: [email protected]) Universidad Politécnica de Madrid, España. Universidad Nacional Experimental Politécnica “Antonio José de Sucre” Av. Corpahuaico con Av. Rotaria y Av. La Salle Barquisimeto, Venezuela

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Keywords: Intragestion, Finance, Audit, ICT Palabras clave: Intragestion, Finanzas, Auditoria, TIC

1 Introducción La crisis financiera que invade a un gran número de organizaciones y personas a nivel mundial, ha tocado igualmente el sector universitario, la lucha por obtener una óptima base financiera preocupa a la humanidad. Sin embargo el fraude y/o los errores voluntarios o involuntarios del ser humano han traído como consecuencia la pérdida de recursos en las empresas, Arancibia (2004). La respuesta a la mejora del ambiente financiero se encuentra en el mismo ser humano como parte de esos recursos que posee la organización y por ser el recurso más importante. Gestionar es administrar y parte de la administración es la organización, como uno de los pilares de la buena gerencia y, cuando una institución ha fallado en la organización, ha de buscar mecanismos para salir del desorden o reorganizar. En base a ello nace la intragestion o gestión interna, para llevar nuevamente a la organización a un nivel estable y optimo, Arzola (2004). La intragestion requiere de herramientas para ordenar lo desordenado y es la auditoria de orden, propuesta en la presente investigación. Las instituciones universitarias formadoras y organizadoras del conocimiento requieren ser pioneras en la aplicación de ideas innovadoras, es por ello que el uso de las TIC en todas las áreas de las instituciones es requerida para simplificar y controlar cada uno de los recursos y optimizarlos, Rodriguez (2004). El área financiera por su importancia "informativa necesita de mecanismos que agilicen y comprueben la veracidad de los recursos que maneja la institución y también requieren de agilidad del recurso humano que los manipula, Chiavenato (2002). Los resultados de la auditoría de orden aplicada como parte del sistema de procedimientos de control provee no solamente una evaluación de la adecuación del programa que sobre protección de los recursos institucionales existan, sino que de igual manera compara los resultados contra las mejoras que puedan ser desarrolladas, implantadas o evaluadas para el mejor aprovechamiento de dichos recursos. Los objetivos se logran a través de la elaboración de diagnostico de la situación actual en el sector universitario comparando ámbito nacional e internacional, determinación de la situación financiera aplicando auditoria de orden e implantando la intragestion financiera a través de las TIC.

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2 Metodología Se realiza un diagnóstico comparativo a nivel internacional de los procesos universitarios en intragestión del conocimiento del área financiera y sus sistemas TIC, utilizando Auditoría de Orden Aplicada. Se identifica y analizan las actividades y normativa nacional que rigen sus sistemas financieros y tecnológicos (TIC), al igual que fortalezas, oportunidades, debilidades y amenazas en la intragestión del conocimiento financiero en las universidades. Se determina la situación actual en la interacción y funcionamiento sistemático, aplicando auditoría de Orden. Es una investigación de campo y también es un proyecto, aplica la técnica de la entrevista, cualitativa no directiva, se efectúan en la comunidad universitaria hasta llegar a la saturación de los datos. Se considera la población como la totalidad del recurso humano en cada una de las áreas y según entrevistas que se realizan en los diferentes niveles de la organización; se implementa el proceso estadístico SPSS para determinar el tamaño de la muestra de procesos que serán postulados para proceder a su jerarquización y se constituye así el orden en que se implementa la gestión sistemática unificada del conocimiento financiero en la organización universitaria, Navarro (2004). Definida y estratificada la población, se determina la muestra de los procesos que cumplen un subgrupo de la población que incide directa o indirectamente en los procesos potentes de la organización, prioritariamente financiero, en primer lugar y tomando en consideración que los expertos a los que se le envía el cuestionario de auto-evaluación de procesos es muy numerosa, se infiere que el muestreo adecuado a aplicar es el Muestreo Aleatorio Simple, el cual plantea que al seleccionar una muestra de tamaño (n) de una población de N unidades, cada elemento tiene una probabilidad de inclusión igual y conocida de n/N. El Estudio implica tomar herramientas cualitativas y cuantitativas que permiten la generación de ideas, se inicia con una revisión bibliográfica, informes y trabajos realizados en el área en estudio, así como de sites de Internet relacionados con la temática planteada, fundamentando de una manera diáfana y objetiva los diversos aspectos que inciden directa e indirectamente en la investigación, la recolección de datos implica:

2.1 Recolección de Datos  Selección de instrumentos de medida.  Aplicar esos instrumentos de medición.  Preparar las mediciones obtenidas.

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2.1.1 Instrumentos de Recolección Por lo tanto, cada instrumento aplicado describe los tres pasos anteriores: 1. Observación directa 2. Entrevistas a) Entrevistas de todas las áreas. b) Entrevistas en las divisiones. – Matriz de área versus equipos – Matriz de ponderación de criticidad de áreas c) Entrevistas Generales.

2.1.2 Informantes La selección de los informantes son las unidades de observación, se efectúan de acuerdo a su relación y su desarrollo en el campo de control del recurso humano y financiero, seleccionados al azar, con el propósito de conocer la concepción de ellos referente a su desarrollo en el área de gestión integral e intragestión, entre los que serán seleccionados: a) Comunidad Universitaria. b) Organismos públicos competentes a los asuntos universitarios. c) Comunidad general universitarios adscritos. El proceso de análisis se efectúa de forma sistemática y ordenada, usando la auditoria de orden con un programa de auditoría elaborado con cada uno de los pasos o procedimientos a seguir. Para reducir los datos cualitativos generados por las entrevistas aplicadas, se necesitan elaborar códigos que faciliten el proceso; considerando que Códigos: es una abreviación o símbolo que aplicamos a unas frases o párrafos de las respuestas de las entrevistas. Con tales códigos o categorías se clasifican o codifican los datos. La elaboración de códigos está orientada a los objetivos de la investigación.

2.1.3 Resultados Alcanzados La investigación consta de tres niveles, un ABC, el primer nivel de formación, un segundo nivel de aplicación e auditoria junto a las TIC, tercer nivel de implantación y optimización financiera. En el primer nivel se constituye la unidad para fomentar la calidad del ambiente interno e implantar la intragestion en la organización, la cual ha de realizarse en todas las unidades, involucrando al personal con programas y tareas. Elaboración y aplicación de auditoría de orden interna utilizando la red de programas a través de las TIC para asegurar su objetividad, se realiza sobre bases periódicas, según la importancia del ambiente en las actividades y 1140


los resultados de auditorías previas. Reuniones con la gerencia, estableciendo políticas de conducir sus actividades hacia el resto de las unidades, conservación del ambiente o cultura organizacional en el cumplimiento de los principios desarrollados. Hallazgos, metas logradas y fallas encontradas en las diferentes unidades orgánicas que integran la institución. Estudio y evaluación de los diferentes procesos y actividades que generan algún impacto negativo en la organización y los efectos nocivos que afectan el ambiente en las unidades existentes. Estudio y revisión constante en la adquisición de la materia prima utilizada para elaborar el producto final y determinar el tipo de componentes que contiene. Comportamiento ambiental y prácticas de los contratantes, sub-contratantes y proveedores junto con la prevención y limitación de accidentes que desestimulan o desmotivan el recurso humano en las diferentes áreas. Selección del equipo líder, en cada unidad, de coordinar la educación de intragestion financiera al resto del personal, elaborar presupuestos a corto y a largo plazo para la consecución de objetivos planteados por la unidad creada. Repartir los costos obligatorios que puedan ocasionarse, según las peticiones que realicen la unidad creada, en varios períodos. Informa externamente a consumidores, clientes, amigos, sobre actividades de intragestion financiera realizadas utilizando las TIC. El segundo y el tercer nivel o B y C se encuentra en el proceso de implantación, el primer nivel o A ha Sido aplicado en organizaciones distintas a las universidades donde se ha observado efectivos resultados a quien ha realizado paso por paso la Gestión sistemática unificado financiero.

3 Referencias Arancibia, Sergio (2004). Innovación y Desarrollo en una Economía Formal. Barquisimeto, Venezuela. UNExPo “Antonio José de Sucre”. Arzola Hamilton, Minerva. (2004). Economía, Organización y Dirección de la Innovación Tecnológica: Gestión del Conocimiento. Barquisimeto, Venezuela. UNExPo “Antonio José de Sucre”. Azkoul Nasser. (2004). Estrategias Comerciales de la Empresa. Barquisimeto, Venezuela. UNExPo “Antonio José de Sucre”. Balestrini, M. (2001). Como se Elabora el Proyecto de investigación. Venezuela, BL Consultores Asociados. Byme, Jhon. (2000). “Gerencia por el WEB- Revista Business Week”, en: Revista Gerente Venezuela. Nº 166. Chiavenato, Idalberto (2002). Gestión del Talento Humano. Colombia, Mc Graw Hill. Díaz Barrigas. (2000). Teoría Constructivista. Caracas. Venezuela. Dubric R., H. (2003). Nacimiento de un Nuevo Ejecutivo. Venezuela. Textografía Jamer, C.A. Escalona A., Lenny. (2005). Análisis de la eficiencia técnica y económica de las empresas hidrológicas venezolanas. Universidad de Zaragoza. España Gates, William. (2000). Los Negocios en la Era Digital. Cómo Adaptar la Tecnología Informática para Obtener el Mayor Beneficio. Barcelona, España. Traducción de J.A. Bravo. Editorial Plaza & Janés Editores, S.A.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. González H., Jorge. (2004) Neurobiología de la Inteligencia Emocional. http:// escuela.med.puc.cl/paginas/publicaciones/neruología/cuadernos/1999/pu_10_99.html. Granderson, G and Linvill, c. (2002). Regulations, efficiency and granger causallitys. International Journal of Industrial Organization. Volume 20. Nº 9. November. Págs. 1225-1245. Guaidó S. Dacmile. (2008) Auditoria de Orden en la Gestión de las instituciones de educación superior en Venezuela. Puerto Ordaz. D.E.A. Universidad Politécnica de Madrid Hernández, R.; Fernández, C. y Baptista, P. (1997). Metodología de la Investigación. Segunda Edición. Editorial Mc Graw- Hill. México. Martínez, M. (2003). La medición de la eficiencia en las instituciones de educación superior. Bilbao. Fundación BBVA. Maxwell, John C. (2006). Developing the Leader Within you. Nashville, EE.UU. Thomas Nelson Publishers. Mercado, S. (2003). ¿Cómo hacer una tesis? México. Tercera edición. Editorial Limusa, S.A. de C.V. Noriega Editores. Masifern, Esteban. (2001). Empresas del Siglo XXI. Disponible: http://www.uah.cl/diplomados/2001/dge/docs/cursos/gestion21/ii/02doc. Mochón, F. (2000). Economía. Teoría y Política. Madrid. Editorial Mc Graw Hill Interamericana de España. Navarro V., Arturo. (2004). Metodología y Documentación Científica. Madrid. Universidad Politécnica de Madrid – Material de Apoyo. Nieto, J. (2001). Decisiones y Mercados. Una introducción a la Economía. Madrid. Ediciones Pirámide. Nuñez Bottini. (2004). Ingeniería de la Productividad. Venezuela UNExPo “Antonio José de Sucre” Periodismo.com. En estos días de Crisis Mundial. 09 de octubre 2008 República Bolivariana de Venezuela. (2000). Constitución. Gaceta Oficial Nº 5.453 Extraordinaria. Editores- Distribuidores DISCOLAR, S.A. Caracas. República de Venezuela. (1999). Ley Orgánica de Administración Central. Gaceta Oficial Nº 36.775. 30 de agosto de 1.999. Caracas. República Bolivariana de Venezuela. (2004). Ley Orgánica de la Administración Pública. Gacetas Oficiales Nº 37.305 del 17 de octubre del 2.001 y Nº 37.963 del 18 de junio del 2.004. Caracas. Rincón, D. y M. Romero. (2002) Tendencias Organizacionales de las Empresas. Revista Venezolana de Gerencia. Volumen 7. Maracaibo. Venezuela Rodríguez Monroy, Carlos. (2004) El Impacto de las TIC en la Externalización. Barquisimeto. UNExPO “Antonio José de Sucre”. Sabino, C. (2000). El Proceso de la Investigación. Caracas. Editorial Panapo. Salazar, Renzo. (2010) Gerencia para la Vida. Barquisimeto. Conceptos Financieros Crown. Schmidt, Eduardo. (2001) Ética y negocios. Perú. Universidad del Pacífico. Suárez, A. (2001). Nueva Economía y Nueva Sociedad. Madrid. Prentice Hall. Szlaifsztein, Gabriel. (2000). Hipótesis y Teorías de la Organización. Disponible: http://www.lafacu.com/apuntes/empresas/teo-organic/default.htm. Tamayo, M. (2000). El Proceso de Investigación Científica. México. Editores Noriega. Thierauf. (2000) Auditoria Administrativa. México. Limusa Noriega Editores. Valera Ibarra, Rafael. (2005) Manual de Estadística Básica. Venezuela. IMPREUPEL. Vence, X. y González, M. (2002). “Los servicios y la innovación”. La nueva frontera regional en Europa. Economía Industrial. Nº 347. V. p. 41. Zrimsek, Brian, et al. “Estimating the Time and Cost of ERP and ERP II Projects: A 10-Step Process.” Gartner Research, 26 Sept. 2001.

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SP-06 Sistemas de Servicios

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La Calidad de E-Servicio en Portales Web B2C: Evaluación Mediante Sistemas de Inferencia Borrosos The E-Service Quality in B2C Websites: Evaluation by means of Fuzzy Inference Systems. Castro A1, Puente J2, de la Fuente D3, Parreño J4, Lozano J5 Abstract The present paper proposes a model to evaluate B2C websites. It has been considered a set of dimensions that have influence in the evaluation according to the literature review and a study of reliability. Once validated the model, it makes use of fuzzy inference systems in order to reduce the uncertainty associated with the decision-making process. As a result of this research, a model capable of designing a simple and intuitive knowledge base is obtained (experts I users) in the evaluation of B2C websites, thus allowing a further optimization of the results obtained.

Resumen El presente artículo propone un modelo para evaluar la calidad de eservicio en portales web B2C. Para ello, se ha considerado un conjunto de dimen1

Adrián Castro López ( e-mail: [email protected]) Grupo de Ingeniería de Organización de Gijón. Dpto. Administración de Empresas. EPI Gijón. Universidad de Oviedo. Campus Viesques s/n, 33204 Gijón. 2 Javier Puente García ( e-mail: [email protected]) Grupo de Ingeniería de Organización de Gijón. Dpto. Administración de Empresas. EPI Gijón. Universidad de Oviedo. Campus Viesques s/n, 33204 Gijón. 3

David de la Fuente ( e-mail: [email protected]) Grupo de Ingeniería de Organización de Gijón. Dpto. Administración de Empresas. EPI Gijón. Universidad de Oviedo. Campus Viesques s/n, 33204 Gijón. 4

José Parreño Fernández ( e-mail: [email protected] ) Grupo de Ingeniería de Organización de Gijón. Dpto. Administración de Empresas. EPI Gijón. Universidad de Oviedo. Campus Viesques s/n, 33204 Gijón. 5

Jesús Lozano Mosterín ( e-mail: [email protected]) Grupo de Ingeniería de Organización de Gijón. Dpto. Administración de Empresas. EPI Gijón. Universidad de Oviedo. Campus Viesques s/n, 33204 Gijón.

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siones relevantes en la evaluación de acuerdo con la revisión de la literatura y un estudio de fiabilidad. Una vez validado el modelo, se hace uso de sistemas de inferencia borrosos con el fin de reducir la incertidumbre asociada a los procesos de decisión. Como resultado de este estudio, se obtiene un modelo capaz de diseñar de forma sencilla e intuitiva la base de conocimiento (expertos y/o usuarios) en la evaluación de portales B2C, permitiendo así una mayor optimización de los resultados obtenidos.

Keywords: Fuzzy Inference Systems, E-service, Quality Service, B2C Websites Evaluation Palabras clave: Sistemas de Inferencia Borrosos, E-servicio, Calidad de Eservicio, Evaluación de Portales B2C.

1 Introducción El crecimiento de las actividades comerciales online está siendo particularmente rápido debido a las nuevas oportunidades de negocio entre empresas y consumidores que este tipo de negocio supone. Este canal permite llegar a colectivos y áreas geográficas impensables hace unos años para algunas empresas (Pires and Aisbett, 2003). Entre los diferentes tipos de E-commerce, el comercio B2C (Business to Consumer) cubre aquellos portales web y transacciones a través de los cuales las empresas venden bienes y servicios a clientes directamente por Internet. La eficiencia y la rentabilidad de este tipo de comercio electrónico ha transformado la web en un entorno global para las empresas. Sin embargo, los consumidores encuentran muchas dificultades en los procesos de compra online relacionadas con la búsqueda y navegación en el portal web, con la evaluación y comparación de productos o con el proceso de pago, entre otros. Todos estos inconvenientes afectan determinantemente a la satisfacción de los clientes con los sitios web B2C (Kuo et al., 2011). El presente trabajo propone inicialmente un análisis exhaustivo de las variables influyentes en el diseño y evaluación de sitios web B2C. Una vez validado el modelo propuesto se realiza una propuesta metodológica basada en la teoría de conjuntos borrosos. Ésta metodología, permite mejorar la interpretación de la base de conocimiento inducido en el sistema de decisión, mejorando así el comportamiento del modelo frente a otros sistemas más simples.

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2 Estado del Arte En el presente apartado se detallan aquellas variables más utilizadas para evaluar la calidad del e-servicio en portales web B2C, según la bibliografía consultada (ver Tabla 1). Tabla 1 Variables relevantes en la evaluación de la calidad de e-servicio DISEÑO. El diseño web es una actividad que consiste en la planificación, modelado e implementación de portales web. Autores: Rangathan y Ganapathy (2001), Alpar (2001), Melián y Padrón (2005), Brown y Jayakody (2008), Lin (2009), Oppenheim y Ward (2010), Stefani y Xenos (2011). INFORMACIÓN. La información, en su sentido más general, se define como un conjunto organizado de datos procesados, que constituyen un mensaje que permite mejorar el estado de conocimiento del sujeto o sistema que recibe dicho mensaje. Autores: Chang y Sangjae (2002), DeLone y McLean (2003), Evanshitzki et al. (2004), Melián y Padrón (2005), Cao et al. (2006), Meziane y Nefti (2006), Nielsen (2006), Joia y Barbosa (2008), Bauernfeind et al. (2009), Lin (2009), Sun y Lin (2009), Oppenheim y Ward (2010). GARANTÍA. La garantía suele referirse a la acción que una persona o empresa despliegan con el objeto de afianzar aquello que se haya estipulado. A través de la concreción o presentación de una garantía, se pretende dotar de una mayor seguridad al cumplimiento de una obligación o al pago de una deuda, según corresponda. Autores: Santos (2003), Melián y Padrón (2005). OFERTA. En términos generales una oferta es aquella propuesta realizada para ejecutar o cumplir algo. Autores: Yang et al. (2000), Melián y Padrón (2005), Cao et al. (2006). PERSONALIZACIÓN. La personalización consiste en la adaptación de los productos o servicios a las necesidades del cliente, de tal forma, que éste se sienta exclusivo, especial, único y diferente.Autores: Melián y Padrón (2005), Koutsabasis et al (2008) Adjei y Clark (2009), Bauernfeind et al (2009), Oppenheim y Ward (2010). SEGURIDAD PAGOS. La seguridad en los pagos se define como la garantía de protección con respecto a las transacciones realizadas y los medios de pago utilizados durante el proceso de compra. Autores: Madu y Madu (2002), Francis y White (2002), Venkataiahgari et al. (2006), Oppenheim y Ward (2010). PRIVACIDAD. La privacidad del servicio se define como la garantía de protección de los datos de interés suministrados por el cliente en relación con su archivo, tratamiento y conservación. En el caso del comercio electrónico se refiere únicamente a los datos de carácter personal del cliente. Autores: Ranganathan y Ganapathy (2001), Oppenheim y Ward (2010), Stefani y Xenos (2011). CONFIANZA. La confianza se define como la esperanza que se tiene en algo o alguien. En el caso concreto del comercio electrónico, hace referencia a la esperanza que tiene el cliente online en que la compra realizada a través de un portal web se realice bajo sus expectativas. Autores: Kaplan y Nieschwietz (2003), Oppenheim y Ward (2010), Hong y Cho (2011).

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3 Modelo de Evaluación Propuesto El modelo propuesto ha sido resultado de una exhaustiva revisión bibliográfica y de un Método Delphi realizado por expertos en Marketing Online en España. Adicionalmente, se ha realizado un pre-test para conocer el sentir de los usuarios de portales de moda online. La Figura 1 ilustra el modelo de evaluación propuesto. La recogida de información se ha llevado a cabo a través de encuestas personales realizadas a compradores habituales en Internet. Las escalas para la evaluación de portales web fueron sometidas a un pre-test con 50 clientes habituales en la compra de artículos por Internet, con la finalidad de poner a prueba la correcta comprensión de las preguntas y añadir, eliminar o modificar en su caso, la composición del cuestionario final. El universo objeto de estudio ha sido definido como el conjunto de individuos mayores de 18 años que son compradores habituales en Internet y que pertenecen al entorno geográfico de España.

Fig. 1 Modelo de Evaluación Calidad del Servicio en Portales Web B2C.

Para determinar la utilización del modelo de evaluación de portales web B2C se ha evaluado la unidimensionalidad, fiabilidad y validez de las escalas de medida. En la primera fase de validación se han considerado las variables estudiadas con todos los ítems que figuraban en el cuestionario, manifestando este análisis exploratorio la necesidad de eliminar algunos de ellos para optimizar la composición de las escalas. Para ello, se ha utilizado el paquete estadístico SPSS versión 19 para Windows. Como resultado de este pre-test se ha realizado un análisis factorial exploratorio de componentes principales con rotación Varimax y un análisis de fiabilidad mediante coeficiente de α de Cronbach. En la Tabla 2 se muestran los resultados obtenidos de este estudio. 1148

Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Tabla 2 Resultados obtenidos Análisis Factorial y α Crombach DIS

INF

GAR

OFE

PER

SPA

SES

CON

% Información Explicada

59,3

68,4

65,7

54,4

52,5

65,1

90,6

82,1

α Crombach

0,83

0,90

0,87

0,75

0,63

0,81

0,89

0,79

El coeficiente de α de Cronbach, indicador utilizado para determinar la fiabilidad de las escalas, tal como se puede ver en la tabla anterior, supera el valor umbral 0,6 recomendado en estudios exploratorios (Hair et al. 1999) en todas las variables propuestas. Además, en todos los casos, dichas variables presentan un porcentaje acumulado de varianza explicada superior al 50%.

4 Metodología La metodología utilizada en esta investigación se basa en los sistemas de inferencia borrosos de ayuda a la decisión. Éstos, se fundamentan en la Teoría de conjuntos borrosos desarrollada por Zadeh (1965), permitiendo incorporar la incertidumbre asociada a los procesos de decisión, haciendo que éstos se aproximen mejor a la realidad (Martin y Sanz, 2005). En los sistemas de inferencia borrosos, las variables, de tipo lingüístico, permiten procesar información tanto cualitativa como cuantitativa dado que toman como valores etiquetas asociables a conceptos del lenguaje común. Esto contrasta con las variables numéricas tradicionales cuyos valores son exclusivamente números (Ponce, 2011). En nuestro caso, la evaluación de la calidad de e-servicio percibida -por expertos o usuarios- presenta un alto nivel de subjetividad. Por este motivo, el uso de etiquetas de tipo lingüístico permitirá una mejor adaptación de los criterios de calificación dados en la evaluación de portales web B2C. Además, se probará que el diseño de un sistema borroso en el ámbito del comercio electrónico B2C, y más en concreto en la evaluación de sus portales web, permite una mejor interpretación de la base de conocimiento insertado en el sistema de decisión, mejorando así los resultados obtenidos en la salida del modelo propuesto.

4.1 Sistemas de Inferencia Borrosos En nuestro caso, para poder aplicar los sistemas de inferencia borrosos, hemos utilizado la aplicación Matlab fuzzy logic toolbox ® versión 2.0. (Mamdani and Gains, 1981). 1149


Para realizar la inferencia se requiere una base de conocimiento constituida a partir del saber hacer de un experto en el problema, capaz de explicar el funcionamiento del sistema a través de un conjunto de reglas lingüísticas construidas con las variables de entrada y de salida. Así, en primer lugar, es necesario definir el rango y la forma de las etiquetas en que se particionan los dominios de las variables del sistema para poder definirlas de forma borrosa. Los sistemas de decisión borrosos de tipo Mamdami, apoyados en lo anterior, permiten realizar inferencias de este tipo en un proceso que consta de cinco etapas (Chen & Klein, 1997): Borrosificación, Aplicación de componentes borrosos a los antecedentes, Implicación al consecuente de cada regla, Agregación de consecuentes y Desborrosificación. Adicionalmente se establecerá la adecuada secuenciación de los subsistemas borrosos integrantes del modelo y se incorporará el conocimiento de evaluación en forma de reglas condicionales para cada subsistema de calificación (de modo que permita la asignación intuitiva de etiquetas lingüísticas en todas sus variables). La Figura 2 representa las etiquetas empleadas para las variables de entrada y de salida, respectivamente:

Fig. 2 Definición de etiquetas.

Posteriormente, se definen las cuatro bases de reglas a utilizar para cada subsistema de evaluación acudiendo al conocimiento del experto: Calidad Web, Servicio Ofertado, Seguridad en el Servicio, y Evaluación Final (ver Fig. 3).

Fig. 3 Bases de reglas para cada uno de los subsistemas parciales y final.

A modo de ejemplo, la celda sombreada de la tabla relativa a la seguridad expresaría la regla: si la valoración de la seguridad en los pagos es media, la privacidad es baja y la confianza es alta, entonces la calificación final de la seguridad será media. Tras diseñar un sistema borroso, puede inferirse la valoración de un portal web según los valores “crisp” de sus variables de entrada. Los mapas de inferencia dados por el modelo permiten analizar fácilmente la congruencia de las evaluaciones obtenidas (en ellos las valoraciones de las variables de salida vienen dadas por la 1150


altura de la superficie en cada punto). Así por ejemplo, en la Figura 4 se muestra el mapa de soluciones de evaluación del subsistema “Calidad Web”.

Diseño

Información

Fig. 4 Mapa de soluciones del subsistema “Calidad Web”.

Al analizar la evaluación de la calidad de la web en función de la información recibida por el usuario y del diseño, se puede observar que debido al conocimiento insertado en las reglas, si el diseño es bajo y la calidad de la información no es la adecuada, se obtendrá una mala calificación de la calidad web. Esta disconformidad sobre la calidad del portal web puede deberse a una falta de adaptación del diseño e información al cliente debido a: la dificultad para navegar en el portal, el uso de excesiva información o poca precisión sobre el producto requerido o que la información se encuentre en un idioma diferente al del cliente potencial. Sin embargo, se observa cómo al crecer la valoración dada al diseño y a la información, la calificación de la calidad web sube notoriamente (en mayor grado para la variable “Diseño”). Este análisis de podría extender al resto de variables (tanto de entrada como de salida) del modelo de evaluación propuesto.

5 Conclusiones y Ampliaciones Futuras En el presente estudio se ha realizado un análisis de las principales variables utilizadas en la evaluación de portales web del sector textil. Para ello, se ha realizado una revisión bibliográfica exhaustiva, junto con un método Delphi y un pre-test. Una vez considerada la adecuación de las diferentes variables, se ha realizado un estudio de mercado a usuarios habituales en la búsqueda/compra de artículos de moda a través de Internet, consiguiendo así la validación del modelo propuesto. Una vez validado el modelo propuesto, se ha analizado la incertidumbre asociada a los procesos de evaluación de este tipo de portales web. Como resultado, se ha conseguido un modelo, fundamentado en los sistemas de inferencia borrosos, capaz de mejorar la interpretación de la base de conocimiento inducido en el sistema de decisión, mejorando así el comportamiento frente a otros sistemas más simples. Como futuras líneas de investigación se pretende fusionar los sistemas borrosos con redes neuronales a fin de lograr una base de conocimiento más dinámica. 1151


6 Referencias Adjei M, Clark M (2010) Relationship marketing in a B2C context: the moderating role of personality traits. Journal of Retailing and Consumer Services. 17:73-79. Alpar P (2001) Satisfaction with a web site: It´s measurement, factors and correlates. Working Paper No. 99/01. Philipps-Univesität Marburg, Institute für Wirtschaftsinformatik. Bauernfeind U, Mayr T, Zins A (2006) A conceptual model for quality dimensions for B2C recommender systems. ECIS Proceedings, 1007-1018. Brown I, y Jayakody R (2008) B2C e-Commerce success: a test and validation of a revised conceptual model. Electronic Journal Information Systems Evaluation. 11:167-184. Cao M, Zhang Q,Seydel J (2006) B2C e-commerce web site quality: an empirical examination. Industrial Management & Data Systems, 105:645-661. Chang L, Sangaje L (2002) A cognitive map simulation approach to adjusting the design factors of the electronic commerce web sites. Expert Systems with Applications, 24:1-11. Chen, CB, Klein CM (1997) An efficient approach to solving Fuzzy MADM Problems. Fuzzy Sets and Systems. 88:51–67. Evanschitzy H (2004) E-satisfaction: a re-examination. Journal of Retailing. 80:239-247. Francis J, White L (2002) PIRQUAL: A escale for measuring customer expectations and perceptions of quality in Internet retailing. In K.Evans and L. Scheer (Eds), 2002. Marketing educator’s conference: Marketing theory and applications. 13:263-270. Hong IB, Cho H (2011) The impact of consumer trust on attiutdinal loyalty and purchase intentions in B2C marketplaces: Intermediary vs seller trust. International Journal of Information Management. 31:469-479. Joia LA, Barbosa de Oliveira LC (2008) Development and testing of an e-commerce web site evaluation model. Journal of Electronic Commerce in Organizations. 6:37-53. Kaplan SE, Nieschwietz RJ (2003) A Web assurance services model of trust for B2C ecommerce. International Journal of Accounting Information Systems. 4:95-114. Koutsabasis P, Stravraskis M, Viorres N, Darzentas JS, Spyrou T, Jarzentas J (2008) A descriptive reference framework for the personalization of e-business applications. Electron Commerce Res. 8:173-192. Kuo HM, Chen CW, Chen CW (2011) A study of merchandise information and interface design on B2C websites. Journal of Marine Science and Technology. 19:15-25. Lin HF (2009) An application of fuzzy AHP for evaluating course website quality. Computers & Education. 10:1016. Madu CN, Madu AA (2002) Dimensions of e-quality. InternationalJournal of Quality & Reliability Management. 19:246-258. Mamdani EH, Gaines BR (1981) Fuzzy reasoning and its applications, NY. Academic Press. Martin B, Sanz A, García A (2005) Redes Neuronales y Sistemas Borrosos. 3º Ed.. RA-MA. Melián L, y Padrón V (2005) Quality in e-commerce B2C: perceptions and expectations. Conferencia IADIS Ibero-Americana. Meziane F, Nefti S (2006) Evaluating E-commerce trust fuzzy logic. School of Computing, Science and Engineering. University of Salford. United Kingdom. Nielsen J, Loranger H (2006) Prioritizing Web Usability. New Riders. Berkeley. Oppenheim C, Ward L (2010) Evaluation of web sites for B2C e-commerce. Aslib Proceedings. 58:237-260. Pires, GD., Aisbett J (2003) Relationship between technology adoption and strategy in businessto-business makets. The case of e-commerce, Industrial Marketing Management. 32:291-300. Ponce, P (2011) Inteligencia Artificial con aplicaciones a la ingeniería. Marcombo. Barcelona. Ranganathan C, Ganapathy S (2001) Key dimensions of business-to-consumer web sites. Information& Management. 39:457-465.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Santos J (2003) E-service quality: a model of virtual service quality dimensions. Managing Service Quality. 13:233-246. Stefani A, y Xenos M (2011) Weight-modeling of B2C system quality. Computer Standards & Interfaces. 33:411-421 Sun C, Lin G (2009) Using fuzzy TOPSIS method for evaluating the competitive advantages of shopping websites. Expert Systems with Applications. 36:11764-11771. Venkataiahgari AK, Atwood JW, Debbabi M (2006) A survey of secure B2C commerce for multicast services. IEEE CCECE/CCGEI. Concordia University. Montreal. Yang Z, Peterson R, Huang L (2000) Taking the pulse of Internet pharmacies. Marketing Health Services. 21:4-10. Zadeh, Lofti A. (1965) Fuzzy Sets. Information and control. 83:338-353

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SP-07 Educación

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Tendencias y Aseguramiento de la Calidad en la Educación Superior: Mapa Europeo y Caso de España Trend and Quality Assurance in Higher Education: European Map and Case of Spain. Gonzalez Lasquibar X1, Ruiz de Arbulo López P2, Landeta Manzano B3, Basañez Llantada A4, Insunza Araceta G5 Abstract This paper discusess how higher education institutions are facing the quality management. At the end of the last decade of the twentieth century a number of trends emerged that caused great concern about the quality in the field of European higher education. It also exposes a simple of ítems or tools quality control employees in different European higher education systems, including the higher education system in Spain.

1

Xabier Gonzalez Lasquibar (e-mail: [email protected]) Dpto. de Organización de Empresas. ETS de Ingeniería de Bilbao, Universidad del País Vasco (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 2

Patxi Ruiz de Arbulo Dpto. de Organización de Empresas. ETS de Ingeniería de Bilbao, Universidad del País Vasco (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 3

Beñat Landeta Manzano Dpto. de Organización de Empresas. ETS de Ingeniería de Bilbao, Universidad del País Vasco (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 4

Aitor Basañez Llantada Dpto. de Organización de Empresas. ETS de Ingeniería de Bilbao, Universidad del País Vasco (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. 5

Gaizka Insunza Araceta Dpto. de Organización de Empresas. ETS de Ingeniería de Bilbao, Universidad del País Vasco (UPV/EHU), Alda Urquijo s/n, 48013 Bilbao, Spain. * Este trabajo se deriva de la participación de sus autores en el proyecto de investigación de la Universidad del País Vasco UPV/EHU titulado “Determinantes y características de las empresas innovadoras de alto crecimiento en la CAPV“ NUPV11/08

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Resumen En el trabajo se analiza la gestión de las instituciones de educación superior centradas en el ámbito de la calidad. A finales de la última década del siglo XX emergieron una serie de tendencias que provocaron una gran preocupación sobre la calidad en el sector de la educación superior Europea. Además se expone una muestra de los elementos o herramientas de control de calidad más comunes en los diferentes sistemas de educación superior europeo, incluido el sistema de educación superior de España.

Keywords: Trends, Quality Assurance, Assessment, Accreditation, High Education. Palabras clave: Tendencias, Aseguramiento De La Calidad, Evaluación, Acreditación, Educación Superior.

1 Introducción La Universidad Europea, desde su origen, la primogénita universidad de Bolonia, creada en el siglo XI (Teichler, 2007), pasando por las universidades tradicionalmente conocidas (Oxford y Cambridge) se esfuerza por ofrecer a sus alumnos una enseñanza de calidad. Una calidad que tradicionalmente solo era accesible para la élite. A finales de la década del siglo pasado se ha apreciado una obsesión por introducir la cultura de la calidad en las universidades actuales. Agentes involucrados en este sector, como el gobierno, las propias instituciones, organismos como la UNESCO, el BANCO MUNDIAL, y agencias involucradas han contribuido a esta difusión. El trabajo presente muestra las tendencias emergentes a finales del siglo XX, tendencias que son efecto de la globalización y que provocan profundas transformaciones en la gestión y estructura de los diferentes sistemas de educación superior. Tendencias que han favorecido la emergente aparición y preocupación por la calidad. Este trabajo recoge las diferentes actividades a desarrollar dentro del proceso de aseguramiento de la calidad. Actividades que son consideradas herramientas de control de calidad y son comunes en algunos países europeos. Por lo que a lo largo del texto se verá como el aseguramiento de la calidad y la Educación superior forman una estrecha relación.

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2 Metodología En este trabajo se ha realizado una búsqueda literaria de los aspectos centrales del trabajo, como son, tendencias, sistemas de aseguramiento y sistemas de evaluación. Para ello, se ha acudido sobre todo a las páginas de los organismos referentes u/o involucrados en el tema como son la ENQA, ANECA, UNESCO. Además también nos hemos ayudado de trabajos realizados por expertos en el tema como López Segrera, Bernhard, Olaskoaga y Barrenetxea.

3 Tendencias A nivel mundial, con excepción de los países menos desarrollados (Trow, 1974), la educación superior se enfrenta a problemas similares y sufre cambios en una dirección común. En la década de los 90, efecto de la globalización, emergen una serie de tendencias en el sistema de educación superior europeo: Masificación: Este fenómeno mundial consiste en el crecimiento o expansión cuantitativa de la masa estudiantil y emerge en Europa en la década de los 60. Se produce a consecuencia del efecto provocado por la globalización, reducción de la financiación pública y la emergente aparición de las TICs (López Segrera, 2005; 2008; Bernhard, 2012); Trow, M (1974). La UNESCO para la medición de este fenómeno emergente, emplea un indicador; la tasa bruta de matrícula (TBM), que mide el número de estudiantes en edad de universitaria. La tasa bruta de matrícula (TBM) a nivel mundial pasó de 13 millones de estudiantes universitarios en 1960 a 137 millones en el 2005, 159 millones en 2008, siendo superiores las previsiones de la Unesco para 2020 (UNESCO, 2007; 2010). En la siguiente tabla se muestran datos relativos a la TBM (tasa bruta de matrícula), variable que mide la masa estudiantil en los países considerados referentes por el enfoque que estos países emplean en su gestión de la calidad (UNESCO, 2010): Tabla 1 Masificación estudiantil Matrícula total 2008

TBM 1999

TBM 2008

Austria

285.000

54%

55%

Finlandia

310.000

82%

94%

Reino unido

2.329.000

60%

57%

España 1.781.000 57% Fuente: Elaboración propia adaptado de UNESCO 2010.

71%

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En la tabla se puede apreciar que en el periodo estudiado (1999-2008), período anterior a la crisis actual que sufrimos, la mayoría de los países han sufrido un crecimiento de la tasa cuantitativa estudiantil en edad universitaria, siendo el crecimiento más destacado en España. El sistema de educación superior convive con la emergente aparición de un número creciente de proveedores, estudiantes, programas y redes de colaboración. Esto es debido a las fuerzas globales del mercado; fuerzas sociales, económicas y políticas. Las universidades públicas tradicionales no cubren con la demanda total, por lo que surgen nuevas instituciones ante esta oportunidad de mercado. Las universidades tradicionales y las de nueva creación deben de satisfacer las necesidades de una masa estudiantil heterogénea por lo que la universidad debe de adecuarse a las demandas del mercado. Como consecuencia de esta tendencia nacen las próximas tendencias descritas. Diversificación: Las fuerzas globales dan lugar a la aparición de instituciones con ofertas educativas diversificadas (López Segrera, 2005; 2008). Emerge una educación superior especializada. El sector de la educación superior se oferta en diferentes tipos de instituciones (públicas, privadas), especializadas en (docencia, investigación), de diferentes áreas (administración de negocios, humanidades, ciencias), de diferente audiencia (estudiantes jóvenes, a tiempo parcial, educación a distancia, educación de adultos, educación permanente) (Lemaitre y Pires, 2008), etc. Tabla 2 Diversificación de instituciones Público

Público subvencionado x gobierno

Privado subvencionado

Austria

84,1%

15,9%

Sin datos-

Alemania

91,1%

8,9%

Sin datos-

Finlandia

86,1%

13,9%

Sin datos-

Reino Unido

-

100%

Sin datos-

España 85,9% 2% Fuente: Elaboración propia basado en UNESCO, 2010.

12%

Los datos de la tabla indican que en la mayoría de los países analizados destacan la presencia de las instituciones públicas, excepto en el Reino Unido, donde todas las instituciones universitarias son privadas. En el caso de España señalar que existen instituciones concertadas, es decir, instituciones privadas ligeramente subvencionadas, como la universidad VIC de Barcelona. Privatización: Como consecuencia de la crisis de los 70 y 80 los gobiernos inician una desinversión en las instituciones de educación superior, lo cual dio lugar a una diversidad de soluciones financieras emergentes demandadas a los diferentes beneficiarios involucrados en el área analizada (López Segrera, 2005); tasas de matrícula, cuotas, etc. 1160


En opinión de López Lamarra (2012) estas instituciones privadas se caracterizan por su falta de criterio de calidad y pertinencia institucional. Internacionalización: El crecimiento de estudiantes universitarios que cursan sus estudios fuera de su país de origen ha crecido a finales del siglo XX y principios del siglo XXI; pasaron de 1 millón en 1995 a 1 millón 900 mil en 2005 (López Segrera, 2005). Tabla 3 Internacionalización. Estudiantes del país dado estudiando en el extranjero

Provenientes del extranjero

Tasa de estudiantes %

Austria

10.241

53.396

18,7%

Alemania

83.524

189.347

Sin datos-

Finlandia

6.502

11.303

3,7%

Reino Unido

21.992

341.791

14,7%

España 21.607 37.726 Fuente: Elaboración propia basado en UNESCO, 2010.

2,1%

La tabla muestra que el país europeo con mayor número de estudiantes es el Reino Unido, favorecido por la lengua anglosajona. Todas estas tendencias obligan a las instituciones de Educación superior a actualizarse mediante el rediseño de sus estructuras y modelos de gobierno y gestión, teniendo como objetivos, la competitividad (Brunner, 2011) y la adecuación a las exigencias sociales y económicas existentes.

4 EEES y Aseguramiento de la Calidad. Las tendencias descritas han provocado una presión por establecer mecanismos para asegurar la calidad. En la década de los 90 la calidad adquiere gran protagonismo, inicialmente en la industria pero expande su protagonismo al sector de la educación superior Matseleng Allais (2009), por ello, autores como Bernhard (2011) y Olaskoaga et. al. (2012), califican la última década del siglo XX como la “década de la calidad” o “década del discurso de la calidad” respectivamente. Los Stakeholders (Freedman, 1994) o agentes del sistema de educación superior; las propias instituciones, agencias de calidad, el propio gobierno, etc. toman medidas o iniciativas para adecuarse a los cambios producidos. La iniciativa más destacada es el proceso convergente Europeo que arranca en Bolonia (1999). Este proceso formado por una serie de reuniones bianuales entre los Ministros de educación Europeos, fijan como objetivos a alcanzar para el 2010 la comparabilidad, la compa-

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tibilidad, la transparencia y la flexibilidad de los diferentes sistemas de educación superior (Ginés Mora, 2003). Para poder culminar con éxito este proceso desarrollan una serie de planes, acuerdos y acciones alcanzados en las reuniones ministeriales celebradas a lo largo del proceso de Bolonia (Barrenetxea, 2005). Estas iniciativas se desarrollan a través del empleo de varias herramientas; en las siguientes líneas sólo se mencionan aquellas relacionadas con la tesis del trabajo (ENQA, 2013):  Promover la cooperación europea en el ámbito de la garantía de calidad (Berlín, 2003).  Desarrollo de la garantía de la calidad en los niveles institucional, nacional y europeo (Berlín, 2003).  Introducción de los estándares y directrices de garantía de la calidad (Bergen, 2005).  Creación del Registro Europeo de Garantía de Calidad (EQAR) (Londres, 2007).

4.1 Gestión de la Calidad En las universidades europeas conviven dos enfoques de gestión de calidad opuestos, el aseguramiento de la calidad y la mejora de la calidad. Biggs (2001) analiza los dos enfoques. El aseguramiento de la calidad se entiende como el conjunto de actividades planificadas y aplicadas para el cumplimiento de una serie de objetivos perfectamente tasados y basados en las necesidades demandantes de los clientes. El segundo de los enfoques, la mejora de la calidad, trata de establecer una serie de condiciones favorables para las universidades, y a los docentes que trabajan en ellas (Mijangos, et.al., 2011). Consiste en una reflexión constitucional con el objetivo de corregir debilidades identificadas. Cada uno de los enfoques se basan en diferentes principios, emplea diferentes herramientas o mecanismos de control de calidad y cuentan con diferentes objetivos (Mijangos, et. al., 2011). El enfoque retrospectivo (aseguramiento de la calidad) calificado por Biggs (2001), debe de rendir cuentas y debe de cumplir una serie de requisitos predeterminados por las agencias externas, y su principal herramienta es la evaluación externa. El segundo de los enfoques, calificado por Biggs (2001) como prospectivo (mejora de la calidad), consiste en una reflexión constitucional encaminado a conseguir el objetivo de calidad. Su principal herramienta es la auto-evaluación, aunque también emplee la revisión externa en un sentido más consultivo (Mijangos et. al., 2001). Como resultado de las presiones ejercidas por los stakeholders, un significativo número de países han adoptado sistemas de aseguramiento de la calidad. El aseguramiento de la calidad, conlleva una serie de procedimientos a emplear. En este 1162


epígrafe se citan los diferentes procedimientos o mecanismos de control de calidad existentes a nivel europeo. La ENQA (2003, citado en Barrenetxea, 2005: 387) realiza una clasificación de los diferentes tipos de evaluación según el método y objeto a analizar: Tabla 4. Métodos de evaluación Métodos de evaluación

Objetos

Evaluación

Materia

Acreditación

Programa

Auditoría

Institución

Benchmarking Tema Fuente: Elaboración propia en base a la ENQA (2003) y Barrenetxea (2005).

De la tabla se puede deducir que si combinamos ambas variables en la práctica existen 16 posibles combinaciones de tipos de evaluación (Barrenetxea, 2005: 387), pero realmente son 8 los principales tipos de evaluación empleados en Europa (ENQA, 2013). En este epígrafe se recogen datos empíricos (Bernhard, 2011; ENQA, 2013) sobre los diferentes procedimientos de aseguramiento de la calidad empleados en algunos países de Europa. En la siguiente tabla se muestra la foto actual de los enfoques adoptados actualmente por las diferentes agencias de calidad de los países estudiados. Tabla 5. Tipos de enfoques Indicadores comparativos

Enfoque

Austria

AAQA : Acreditación

Alemania

ACQUIN: Consejo de acreditación: meta-acreditación

Finlandia

FINHEEC: Auditorias

Reino Unido

QAA: Evaluación (antes de 2001/2002) A partir de 2001/2002 Revisiónevaluación externa y auditoría institucional Inglaterra e Irlanda del norte (auditoría institucional); Escocia (evaluaciones institucionales); País de Gales (revisiones institucionales).

España

ANECA: Evaluación externa e interna institucional, programas y materia.

Acreditación títulos. Fuente: adecuado desde Bernhard 2011 y ENQA, 2013.

En la tabla se puede apreciar que los diferentes países estudiados difieren en algunos aspectos específicos de su sistema de aseguramiento de la calidad. El modelo centro europeo desarrollado por Alemania y Austria tiende a una única agencia y hacia la acreditación; Finlandia como modelo referente en los últimos años tien-

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de a la auditoría de procesos de calidad, Reino Unido tiende hacía la evaluación, existiendo diferencias entre los países miembros y España tiende a la evaluación.

4.2 Caso de España La primera experiencia española fue a inicios de los 90, después de diversos proyectos pilotos exitosos, tanto a nivel nacional como a nivel de Europa, se estableció el I Plan Nacional de Evaluación de la Calidad de las Universidades (PNECU) en 1995, vigente hasta el 2001. Este plan contenía la metodología de los proyectos pilotos exitosos desarrollados con anterioridad: Una auto-evaluación seguida de una evaluación externa a través de peer review (visita externa de colegas de profesión) y la publicación de un informe final. El éxito de este plan provocó la extensión de la cultura de la calidad por las universidades españolas. A mediados del 2001 se inició el II Plan de Calidad de las universidades (PCU), el cual bajo la administración de la nueva Ley de Universidades (LOU) estableció que los planes de estudio debían someterse a evaluación, certificación y acreditación por la nueva Agencia Nacional de Evaluación de la Calidad y Acreditación (ANECA) (Ginés Mora, 2005), agente más representativo de la calidad en el sistema de educación superior español, creada el 19 de Julio del 2004: se trata de una fundación estatal cuyo objetivo es contribuir a la mejora de la calidad de la educación superior a través de la evaluación, certificación y acreditación de enseñanzas, profesorado e instituciones (ANECA, 2012). Este organismo cuenta con una serie de programas a través de los cuales realiza sus funciones reguladoras: Programa AUDIT: Orienta a los centros universitarios en el diseño de sistemas de garantía interna de calidad. Programa VERIFICA: Evalúa las propuestas de los planes de estudio de títulos diseñados en consonancia con el Espacio Europeo de Educación Superior (ANECA, 2013). Programa MONITOR: realiza un seguimiento del título oficial para comprobar su correcta implantación y resultados. Programa DOCENTIA: Valoración de la garantía de la calidad del profesorado. Programa PEP: Evalúa el Curriculum Vitae de los solicitantes para el acceso a las figuras de profesor universitario contratado. Programa ACADEMIA: Evalúa el Curriculum Vitae para acceso a los cuerpos de funcionarios docentes universitarios. Programa MENCIÓN: Evalúa a los programas de doctorado que optan a una Mención hacia la Excelencia.

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5 Conclusiones Se aprecia una preocupación sobre la calidad a finales del siglo XX. Consecuencia de las fuerzas del mercado. Esta preocupación se ve reflejada en el comportamiento por parte de las IES quienes se ven obligados a realizar cambios estructurales y de gestión, así como la presión ejercida por los diferentes stakeholders. Los sistemas de aseguramiento difieren en aspectos específicos, aunque existen elementos comunes que configuran un modelo internacional: El sistema de aseguramiento de la calidad es gestionado por una agencia más o menos autónoma de carácter público. El proceso de evaluación o acreditación se inicia con la auto-evaluación y se complementa con una visita de pares externos. El proceso es cíclico. También se aprecia elementos comunes más controvertidos: El procedimiento se focaliza en los programas o instituciones o, en ambos. Los resultados de la evaluación o acreditación sirven para el gobierno como criterio para la asignación de recursos públicos.

6 Referencias Barrenetxea, M (2005). Modelos de calidad y evaluación de la educación superior en la Unión Europea (Tesis doctoral). Bernhard, A. (2011). National Quality Assurance Systems in Comparison. International Journal for Cros-disciplinary Subjects in Education(IJCDSE).vol2.Issue4. Bernhard, A. (2012). Quality Assurance in an International Higher Education Area. Humanities, social sciences and law. Biggs, J. (2001). The reflective institution: assuring and enhancing the quality of teaching and learning. Higher Education. 41, pp. 221-238. Brunner, J.J. y Peña, C. (2011). El conflicto de las universidades entre lo público y lo privado. Ediciones Universidad Diego Portales. Santiago, Chile. ENQA. (2009). Standards and Guidelines for Quality Assurance in the European Higher Education Area. ENQA. (2012). Quality procedures in the European Higher Education Area and Beyond- visions for the future. Fernández Lamarra, N. (2012). “Universidad y Calidad en América Latina en perspectiva comparada. Interrogantes y desafíos”. Avaliacao. V. 17, n. 3, pp. 661-688 Ginés Mora, J (2003). Trends in Quality Assurance in the Bologna Context. Guest editor European Journal of Education, 38, 3. Lemaitre,M y Pires, S.(2008).Sistemas de acreditación y evaluación de la Educación Superior en América Latina y Caribe. www.iesalc.unesco.org López Segrera, F. (2005). Posibles escenarios mundiales de la educación superior. Perfiles educativos.vol. XXVII (109-110). pp 140-165. López Segrera, F (2008). Tendencias de la educación superior en el mundo y en América latina y el Caribe. Sorocaba

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Matseleng Allais, S. (2009). “Quality assurance in education”. Centre for Education Policy Development. Mijangos, J. et. al., (2011). Enseñanza Universitaria de Calidad: Profesorado, Alumnado e Institución. Proyecto de Investigación UPV/EHU. Olaskoaga, J. e Intxaurburu, G. (2000). Iniciativas y experiencias europeas en la configuración de espacios regionales de colaboración Universidad-empresa. Revista de Estudios Regionales.209-226 Olaskoaga, J; Marúm, E.; Rosario, V y Pérez, D. (2012). Universidades en Movimiento. Una revisión de la literatura empírica sobre las opiniones y las actitudes de los docents antes de las transformaciones recientes de las organizaciones universitarias. Organisation for Economic Co-operation and Development (OECD). (2010). Programme on Institutional Management in Higher Education (IMHE). Testing student and university performance globally.www.oecd.org. Teichler, U (2007). Higher Education Systems. Sense Publishers. Trow, M. (1974). Problems in the Transition from Elite to Mass Higher Education. OECD, pp.51-101. UNESCO (2007) Global Education Digest. UIS. Montreal. UNESCO. (2010).Compendio mundial de la educación 2010. Instituto de estadística de la Unesco. Canadá

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Satisfacción en la Utilización del Video por el Discente en su Proceso Activo de Aprendizaje. Una Experiencia en el Contexto de los Grados en Ingeniería de Telecomunicación. Satisfaction in the Use of Video by the Learner in Active Learning Process. An Experience in the Context of Telecommunication Engineering Degrees. Pérez-Aguiar W1, Martínez-Núñez M2 Abstract The use of video among university lecturers is increasing with the development of the European Higher Education Area. This paper argues that it is time to also be a tool used by the learner to achieve their learning purposes. From this perspective, we discuss the advantages that this technology may have for our students and we propose two hypotheses for verification, the first related to the development of social networks, the second has to do with empathy that develops in the workgroup. Then, we present and discuss the results.

Resumen El uso del video entre los docentes universitarios está aumentando con el desarrollo del Espacio Europeo de Educación Superior. En este trabajo se mantiene que ha llegado la hora de hacer que también sea una herramienta utilizada por el discente para conseguir sus fines de aprendizaje. Desde esta perspectiva, se discuten las ventajas que esta tecnología pueda tener para nuestros alumnos y se proponen dos hipótesis para su verificación, la primera relacionada con el desarrollo de las redes sociales; la segunda, tiene que ver con la empatía que se desarrolla en el grupo de trabajo. Seguidamente, se presentan y discuten los resultados obtenidos.

1Waldo

Pérez-Aguiar ( e-mail: [email protected]) Departamento de Ingeniería de Organización E.U.I.T de Telecomunicación, Universidad Politécnica de Madrid Crta. Valencia km. 7, 28031 Madrid (España)

2Margarita

Martínez-Núñez ( e-mail: [email protected]) Departamento de Ingeniería de Organización E.U.I.T de Telecomunicación, Universidad Politécnica de Madrid Crta. Valencia km. 7, 28031 Madrid (España)

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Keywords: Video, Teacher education, Empathy, Learning achievement, Customer satisfaction Palabras clave: Video, Educación, Empatía, Aprendizaje, Satisfacción del cliente

1 Introducción En este trabajo se pretende valorar la satisfacción del estudiante en la realización de actividades audiovisuales, en particular, la grabación de videos en grupos de trabajo, como parte de su proceso de aprendizaje. La satisfacción del estudiante en el proceso de aprendizaje va cobrando un interés creciente en la literatura sobre innovación educativa, pues se han realizado estudios tanto de carácter general (Chien, 2007) como circunscritos a determinadas áreas del saber (Ropponen, 2009) o contextos educativos y tecnológicos específicos, como la TV interactiva (Pool, 1996) o e-learning (Lee et al, 2007; Bolligery y Wasilik, 2009), o aspectos concretos, como el espacio físico en que se imparte la clase (Hill y Epps, 2010). Así, conseguir aumentar la satisfacción de los alumnos se ha convertido en una tarea importante, tanto para los profesores como para los gestores de la educación (Chien, 2007), máxime si tenemos en cuenta que existe una fuerte correlación entre la satisfacción percibida y otros aspectos muy relevantes del proceso de aprendizaje, como la motivación por aprender (Chen y Chih, 2011) o los factores que inciden en la calidad de la enseñanza (Guolla, 1999). La preocupación por la satisfacción obtenida en el proceso de aprendizaje supone conceptualmente equiparar a la institución educativa con una empresa de servicios, en la que el estudiante es el consumidor y cliente, aunque también productor y producto (Guolla, 1999). Para el trabajo que aquí se presenta, es relevante la concepción del estudiante en su rol de productor, o co-productor de su propia educación, mediante la participación en un conjunto de actividades (Kotzé y Plessis, 2003); ahora el estudiante toma una conciencia activa y responsabilidad de su proceso de aprendizaje, a la vez que él es, en gran medida, constructor de su propia satisfacción, calidad y valor en el proceso educativo (Bitner et al, 1997). Desde esta perspectiva, el profesor se concibe como un recurso en este proceso. Precisamente con la implantación del Espacio Europeo de Educación Superior, la docencia en las Universidades está incorporando metodologías, técnicas y herramientas que sitúan, más que nunca, al discente en el centro del proceso educativo, lo que supone, precisamente, potenciar su rol de productor. Ahora se espera que el alumno adquiera el protagonismo de su propio aprendizaje; paralelamente, los docentes nos vemos en la obligación de arbitrar los mecanismos que faciliten su implicación en este proceso. Programar la realización de actividades en las que el alumno deba grabarse y explicar su trabajo a sus compañeros y / o al profesor supone avanzar varios niveles en su grado de participación. Por ejemplo, 1168


Fritschner (2000: 354) ha identificado en su estudio seis niveles de participación de los estudiantes en las aulas de grado: Nivel uno: los estudiantes asisten a clase, se mantienen despiertos y ocasionalmente prestan atención. Nivel dos: los estudiantes asisten a clase, tomar notas y realizar tareas. Nivel tres: los estudiantes toman apuntes reflexivamente. Nivel cuatro: los estudiantes hacen preguntas y comentarios, a la vez que participan en las discusiones en clase. Nivel cinco: los estudiantes hacen trabajos o preguntas adicionales. Nivel seis: Los estudiantes hacen presentaciones orales, es decir, se convierten en profesores de sí mismos. Por tanto, la utilización del video para explicar el trabajo realizado supone avanzar en su grado de participación hasta el nivel 6, simplemente, por el propio diseño de la actividad. Sin embargo, aunque el video se está convirtiendo en una herramienta de enseñanza muy utilizado entre los educadores de Ingeniería de Organización y Dirección de Operaciones en el ámbito académico y empresarial, siempre se analiza como recurso del docente, no como actividad del discente. En efecto, la literatura científica sobre educación se ha ocupado del efecto y consecuencias de su incorporación en la actividad del docente; sin embargo, poco o nada se ha estudiado hasta la fecha sobre la utilización del video por el discente, como complemento para afianzar sus conocimientos teóricos y profundizar en la adquisición de competencias. Ciertamente, diversos estudios se ocupan de los factores de éxito, de la satisfacción y de la empatía del alumno ante la incorporación del vídeo por parte del docente en el proceso educativo en general (Cennamo, 1993; Cennamo et al, 1991; Choi et al, 2010) o sobre algunas disciplinas en particular, como educación física o medicina. Aunque Clark (1983, 1994) mantiene que el medio utilizado, ya sea video o texto, no afectan al aprendizaje ni a la satisfacción obtenida, planteamiento replicado por Kozma (1994), la evidencia aportada, entre otros por (Cennamo, 1992), indica que los medios utilizados para el aprendizaje presentan una dificultad diferente, que en orden decreciente son: libros, ordenadores, televisión y video interactivo. Sin embargo, la utilización del video por parte del alumno como una actividad más en sus asignaturas ha recibido muy poca atención. La incorporación del video utilizado por el alumno puede entenderse como la evolución natural, resultado del avance tecnológico en el que toda la sociedad se ve afectada. Un primer salto en esta evolución fue puesto de manifiesto por Gioia y Bass (1985-1986) cuando afirmaron que dado que los estudiantes universitarios "se han criado en un ambiente intensivo en televisión, películas y videojuegos" han desarrollado estilos de aprendizaje donde la comprensión se produce principalmente a través de imágenes visuales. Es en este contexto donde la utilización del video por el profesor, en las aulas y fuera de ellas, como parte del proceso de aprendizaje cobra todo el sentido. El segundo salto ha venido de la mano de la reciente incorporación de las redes sociales (tuenty, facebook…) y las plataformas de contenidos audiovisuales (you1169


tube, flickr…) a los hábitos culturales y cotidianos de los estudiantes, como forma habitual de relacionarse entre amigos, conocidos y también, desconocidos, permite incorporar el video a la docencia desde una perspectiva distinta. Igual que hace veinte años, el estudiante estaba muy familiarizado, vía televisión, con los contenidos audiovisuales, en nuestros días es habitual la grabación y subida a Internet de escenas y momentos cotidianos. En la mayoría de los casos, estas grabaciones quedan en abierto, visibles para el resto del mundo. Desde esta perspectiva, cabe distinguir dos estados del alumno que denotan diferente grado de asimilación e interiorización del nuevo paradigma audiovisual y social: el inmigrante digital y el nativo digital. Para el primero, las redes sociales y plataformas digitales se han convertido en parte esencial de su vida, pues pasa mucho tiempo al día comunicándose con quien le interesa e informándose de lo que necesita, disfrutando de su ocio, viendo videos y fotos, leyendo blogs, etc. El nativo digital tiene estos comportamientos mucho más arraigados, hasta el punto de sustituir a otros más clásicos; además, crea contenidos, escritos o audiovisuales que sube a las correspondientes plataformas. Los aspectos positivos de estos cambios culturales y de hábitos deben ser aprovechados por el docente e integrarlos en el proceso educativo. Ahora, no se trata de que el alumno reciba diversos contenidos en formato audiovisual, si no que más bien debe utilizarlos para generar contenidos, y así, de una manera proactiva, asentar sus conocimientos, a la vez que acreditar y consolidar determinadas competencias transversales. En la actualidad, grabar contenidos de todo tipo es muy accesible, cualquier smartphone dispone de una cámara con la calidad mínima aceptable. Así, ahora es posible incorporar a las guías de las asignaturas de los títulos de grado actividades en las que el discente deba grabarse a sí mismo, de manera individual o por equipos, mientras realiza la presentación de un trabajo en el que se ponen en juego destrezas y habilidades adquiridas durante el curso.

2 Cuestiones a Investigar Las cuestiones relevantes en este estudio son las siguientes: 1. El grado de familiaridad del alumno con la actividad en redes sociales, blogs y plataformas de contenidos audiovisuales repercute favorablemente en el grado de satisfacción obtenido en la actividad de grabarse una presentación en video, dentro de la asignatura de Economía y Dirección de Empresas. 2. La empatía que el alumno ha desarrollado con sus compañeros de equipo repercute favorablemente en el grado de satisfacción obtenido en la actividad de grabarse una presentación en video, dentro de la asignatura de Economía y Dirección de Empresas.

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3 Metodología En las líneas que siguen se presentan los resultados del estudio realizado en la EUIT de Telecomunicación de la UPM a los estudiantes de la asignatura de Economía y Dirección de Empresas, que se cursa en el quinto semestre sobre la satisfacción que les ha producido la realización y presentación de un video académico. Aquí se presentan los resultados de tres títulos de grado: Sonido e Imagen, Telemática y Electrónica de Comunicaciones. A lo largo del curso, los estudiantes, agrupados en equipos de cuatro personas, deben ir realizando diversas actividades acumulativas que dan lugar a un trabajo de curso, el cual culmina con una presentación oral que debe grabarse en video y cuya evaluación forma parte importante de la nota final. Una vez entregado el trabajo se les ha pasado una encuesta sobre la satisfacción obtenida con la actividad. Cada pregunta se contesta con 5 respuestas, escala Likert, desde Nada de Acuerdo hasta Muy de Acuerdo. Se trata de un estudio exploratorio, en que se han tratado solo dos cuestiones, siendo intención de los autores la posterior ampliación de la investigación a otros aspectos relevantes que de momento no han sido abordados.

4 Diseño de la Investigación y Procedimiento de Recolección de Datos El número de alumnos participantes en la encuesta fue de 60. Dos personas dejaron de contestar a algunas preguntas, por lo que el número de casos válido asciende 58. Se realizó en horario de clase, haciendo que coincidiera con la preceptiva encuesta sobre el profesorado y la asignatura, el último día de clase. Se quiso determinar, en primer lugar, la satisfacción producida por la actividad de grabarse a sí mismos en video como una más de las actividades de la asignatura. Para ello se les hizo contestar a un primer bloque de 9 preguntas, todas relacionadas con la satisfacción o la afinidad de dicha actividad. Table 1 La actividad de grabación de un vídeo en la asignatura Economía y Dirección de Empresas 1 2 3 4 5 6 7 8 9

Me ha parecido muy útil Me ha permitido aprender cosas nuevas Ha aumentado mi capacidad para transmitir mis conocimientos a terceros Me ha permitido descubrir aspectos desconocidos sobre mi persona Me ha permitido descubrir aspectos desconocidos sobre mis compañeros Me ha resultado positiva en algunos aspectos No me ha servido para aprender nada Me ha gustado No me ha aportado nada interesante

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Seguidamente se necesitaba conocer la empatía, definida como ''la capacidad afectiva dentro de la socialización en el desarrollo o la comprensión de otro estado emocional o condición, que es idéntica o muy similar a lo que la otra persona se siente o se espera que se sienten'' (Choi, 2010: 553), que a lo largo del curso se ha generado entre los miembros del equipo. Las preguntas del segundo bloque fueron las siguientes: Table 2 En la actividad de grabación de un vídeo en la asignatura Economía y Dirección de Empresas, mis compañeros/as 10 11 12 13 14

Me han ayudado mucho Se negaron a dedicarle más tiempo Han puesto problemas inexistentes Han corregido mis defectos Son un motivo para que yo lo haga mejor

Un tercer bloque trata de medir el grado de afinidad a la utilización de redes sociales, blogs y plataformas de contenidos multimedia. Las preguntas fueron las siguientes: Table 3 Sobre mi actividad en Redes Sociales, blogs y plataformas digitales 15 16 17 18 19

Entro con frecuencia en mis perfiles en Redes Sociales (Facebook, Tuenti, etc.) Hago comentarios con frecuencia en mi perfil en redes sociales (Facebook, Tuenti, etc.) Consulto y leo con frecuencia blogs sobre los temas de mi interés Hago comentarios en los blogs sobre temas de mi interés frecuentemente Soy responsable de un blog o participo habitualmente en él

5 Tratamientos Antes de comenzar los cálculos se transpusieron los valores de aquellas preguntas que, por estar en negativo, su significación iba en sentido contrario al general. Se analizó en primer lugar la fiabilidad de la escala. Los bloques primero, segundo y tercero obtuvieron respectivamente un α de Cronbach de 0’89, 0’78 y 0’80 respectivamente. Seguidamente, se realizó una reducción de las dimensiones de cada bloque, lo cual se hizo mediante conglomerados jerárquicos, en los que se utilizó la distancia euclidea al cuadrado para definir las distancias iniciales y el método de Ward para establecer la posición de cada nuevo conglomerado. Los resultados arrojaron la existencia de tres conglomerados en el primer bloque, los cuales se han definido como: el renegado, el moderado y el entusiasta. La siguiente tabla informa de las medias y error típico de cada pregunta:

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 4 El grupo de afinidad a la actividad de video La actividad de grabación de un vídeo 1 2 3 4 5 6 7 8 9

Me ha parecido muy útil Me ha permitido aprender cosas nuevas Ha aumentado mi capacidad para transmitir mis conocimientos a terceros Me ha permitido descubrir aspectos desconocidos sobre mi persona Me ha permitido descubrir aspectos desconocidos sobre mis compañeros Me ha resultado positiva en algunos aspectos No me ha servido para aprender nada Me ha gustado No me ha aportado nada interesante

Renegado Med. E.tip. 1,2 0,13

Moderado Med. E.tip. 2,45 0,13

Entusiasta Med. E.tip. 3,67 0,159

1,2

0,13

2,18

0,13

3,80

0,145

1,4

0,22

2,82

0,16

3,73

0,22

1,8

0,33

1,85

0,17

3,67

0,32

2

0,36

2,30

0,22

3,33

0,29

1,6

0,22

3,09

0,11

3,73

0,18

2 1,1 2,90

0,29 0,1 0,379

3,82 2,64 3,76

0,15 0,16 0,16

4,47 3,87 4,60

0,16 0,215 0,131

El renegado responde con un patrón negativo a todas las preguntas, sin llegar a vislumbrar un solo aspecto positivo de la actividad. El entusiasta es justo lo opuesto, le ha gustado la actividad y considera que ha sido muy interesante. El moderado, entre los dos grupos anteriores, aprecia las virtudes, pero también denuncia los puntos débiles de la actividad. También al segundo bloque se le sometió a una reducción de dimensiones. Se encontró: Table 5 El grupo de empatía a sus compañeros de equipo En la actividad de grabación de un vídeo en la asignatura Economía y Dirección de Empresas, mis compañeros/as 10 Me han ayudado mucho 11 Se negaron a dedicarle más tiempo 12 Han puesto problemas inexistentes 13 Han corregido mis defectos 14 Son un motivo para que yo lo haga mejor

Empatía baja

Empatía alta

Media

Error tip.

Media

Error tip.

2,51 4,11 4,35 2,16 2,38

0,16 0,18 0,17 0,16 0,16

4,17 4,57 4,74 3,48 4,26

0,15 0,12 0,09 0,15 0,13

Como puede comprobarse, aunque existe un ambiente generalizado de camadería en nuestra Escuela, el estudiante con poca empatía siente una menor ayuda que quien tiene una empatía alta, no se sienten ayudados por los compañeros y tampoco piensan que es un motivo para mejorar. La reducción de dimensiones de la afinidad social también llevó a la identificación de tres grupos, de afinidad baja, media y alta respectivamente:

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 6 El grupo de orientación a las redes sociales Sobre mi actividad en Redes Sociales, blogs y Baja plataformas digitales Med

Media

Alta

E.tip.

Med. E.tip.

Med.

E.tip.

15

Entro con frecuencia en mis perfiles en 3,14 Redes Sociales (Facebook, Tuenti, etc.)

0,24

4,27

0,19

4,69

0,15

16

Hago comentarios con frecuencia en mi perfil en redes sociales (Facebook, Tuenti, etc.)

1,64

0,15

3,09

0,271 3,94

0,23

17

Consulto y leo con frecuencia blogs so2,36 bre los temas de mi interés

0,20

4

0,19

4,31

0,22

18

Hago comentarios en los blogs sobre temas de mi interés frecuentemente

1,32

0,10

2,27

0,19

3,38

0.26

19

Soy responsable de un blog o participo habitualmente en él

1,05

0,45

1,09

0,91

3,63

0,30

Vemos que cada grupo indica, esencialmente, una utilización más esporádica o intensiva de las redes y plataformas.

6 Análisis de datos Dado que se trata de un estudio exploratorio, para verificar la primera hipótesis, se ponen en común los conglomerados obtenidos en el apartado anterior, la afinidad a la actividad de video con la afinidad al social media. Table 7 Afinidad a la actividad de video y al uso social media

Afinidad a la actividad de video Total

Renegado Moderado Entusiasta

Afinidad al uso social media Baja Media Alta 4 5 1 15 12 6 2 5 8 21 22 15

TOTAL 10 33 15 58

A simple vista no parece detectarse una relación entre ambas variables. Además, el estadístico chi-cuadrado de Pearson con un valor de 9.578 y 4 grados de libertad tiene un nivel de significación de 0,048, sería precipitado aceptar o rechazar la hipótesis nula de independencia de las variables. Sin embargo, los valores del estimador d de Somers pueden ser más esclarecedores:

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Table 8 d de Somers d de Somers

0,288

0,106

T aproximad ab 2,651

0,271

0,101

2,651

0,008

0,308

0,113

2,651

0,008

Error típ. asint.a

Valor

Simétrica Afinidad a la actividad de video dependiente Afinidad uso social media dependiente

Sig. aproximad a 0,008

Dado que el nivel crítico de las tres versiones del indicador (Sig. aproximada) están por encima de 0,05 se puede aceptar la hipótesis nula de independencia entre la satisfacción que produce la grabación de un video como actividad de clase y la actividad que los estudiantes mantienen en redes sociales. La segunda hipótesis a contrastar presenta la siguiente tabla de contingencia: Table 9 Afinidad a la actividad de video y empatía con los compañeros de grupo Afinidad a la actividad de video

Empatía con los compañeros de grupo

TOTAL

Baja

Alta

Renegado

8

2

10

Moderado

21

12

33

Entusiasta

8

7

15

Total

37

21

58

En esta ocasión, el estadístico chi-cuadrado de Pearson ofrece resultados más claros. Con un valor de 1.848 y 2 grados de libertad, presenta un nivel de significación de 0,397, muy superior al 0,05 por lo que tenemos que concluir que las variables estudiadas no están relacionadas.

7 Conclusión y Discusión Los dos resultados obtenidos parecen ser cuanto menos chocantes. Por un lado, la mayor familiarización del alumno con las tecnologías relacionadas con el video y su incorporación al día a día merced a la masiva utilización de las redes sociales y plataformas de contenidos audiovisuales no cambian su posición frente a la incorporación de esta herramienta en el aula. Por otro lado, la mayor empatía que surge entre los miembros del grupo tampoco es un factor que intervenga en la predisposición del alumno a acometer este tipo de actividades. Ambos resultados pueden calificarse de paradójicos. Sin embargo, son muchas las ocasiones en que la ciencia ha avanzado tras cierto periodo de tiempo detenida

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parcialmente, en ocasiones durante cientos de años, hasta que surge la clarividencia que permite resolver la paradoja. Estas conclusiones quizá no aportan respuestas contundentes, pero sí plantean muchas incógnitas que señalan nuevos caminos. Así, por una parte surge la duda sobre la replicación, es decir, si al repetir la investigación con las mismas o muy parecidas conclusiones los resultados también se repetirán. Por otro lado, se requiere conocer qué aspectos o factores determinan la predisposición del alumno ante esta actividad, con carácter previo, como los que inciden en la percepción que tenga sobre su utilidad, ya en el momento de la realización.

8 Referencias Bitner, Mary Jo; Faranda, William T; Hubbert, Amy R; Zeithaml, Valarie A., (1997) Customer contributions and roles in service delivery, International Journal of Service Industry Management 8. 3: 193-205. Bolliger, D.U.; Wasilik, O.( 2009) Factors influencing faculty satisfaction with online teaching and learning in higher education, Distance Education, 30: (1) 103-116. Cennamo, K.S. (1992) "Students' perceptions of the ease of learning from computers and interactive video: an exploratory study", Journal of Educational Technology Systems, Vol. 21, pp. 251-63. Cennamo, K.S. (1993) "Learning from video: factors influencing learners' preconceptions and invested mental effort", Educational Technology Research and Development, Vol. 41 No. 3, pp. 33-45. DOI: 10.1007/BF02297356 Cennamo, Ks; Savenye, Wc; Smith, Pl (1991) Mental Effort And Video-Based Learning - The Relationship Of Preconceptions And The Effects Of Interactive And Covert Practice, Educational Technology Research And Development Volume: 39 Issue: 1 Pages: 5-16 Doi: 10.1007/Bf02298103 Chen, P.S.; Chih, J.T. (2011) The Relations between Learner Motivation and Satisfaction with Management Training: An Empirical Study in Taiwan, International Journal of Management, 28 (1): 77-90. Chien, T.K. (2007) Using the learning satisfaction improving model to enhance the teaching quality, Quality Assurance in Education, 15 (2): 192-214, DOI 10.1108/09684880710748947 Choi, H. (2007) College students’ perceptions of learning and knowledge transfer in problembased video instruction: A case study. Journal of Learning Design, 2(2), 105–115. Choi, H., & Johnson, S. D. (2005) The effect of context-based video instruction on learning and motivation in online courses. The American Journal of Distance Education, 19(4), 215–227. Choi, H., & Johnson, S. D. (2007) The effect of problem-based video instruction on learner satisfaction, comprehension and retention in college courses. British Journal of Educational Technology, 38(5), 885–895. Clark, R. E. (1983) Reconsidering research on learning from media. Review of Educational Research, 53(4), 445–459. Clark, R. E. (1994) Media will never influence learning. Educational Technology Research and Development, 42(2), 21–29. Fritschner, L.M. (2000): Inside the undergraduate college classroom: Faculty and students differ on the meaning of student participation, The Journal of Higher Education 71, (3): 342-362.

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Book of Proceedings of the 7th International Conference on Industrial Engineering and Industrial Management - XVII Congreso de Ingeniería de Organización. Guolla, M. (1999) “Assessing the teaching quality to student satisfaction relationship: applied customer satisfaction research in the classroom”, Journal of Marketing Theory and Practice, Vol. 7 No. 3, pp. 87-97. Gioia, D. and Brass, D. (1985-1986) "Teaching the TV generation: the case for observational learning", Organizational Behavior Teaching Review, Vol. 10 No. 2, pp. 11-18. Hill, M.C.; Epps, K.K. (2010): The impact of physical classroom environment on student satisfaction and student evaluation of teaching in the university environment, Academy of Educational Leadership Journal, 14 (4): 65 – 79. Kotze, T G; u Plessis, P J,. (2003) Students as ‘co-producers’ of education: A proposed model of student socialisation and participation at tertiary institutions, Quality Assurance in Education; 11, 4, pp. 186 – 201. Kozma, R.B. (1991) "Learning with media", Review of Educational Research, Vol. 61, pp. 179211. Kozma, R.B. (1994) "Will media influence learning: reframing the debate", Educational Technology Research and Development, Vol. 42 No. 2, pp. -19. Marx, R.D; Frost, P.J. (1998): Toward optimal use of video in management education: examining the evidence, The Journal of Management Development 17. (4): 243-250. Pool, P. (1996) Teaching via interactive television: An examination of teaching effectiveness and student satisfaction, Journal of Education for Business; Nov/Dec; 72, 2: 78-80 Proserpio, L.; Gioia, DA (2007) Teaching the virtual generation, academy of management learning & education volume: 6 issue: 1 pages: 69-80 Published: MAR 2007 Ropponen, A. (2009) Experiences of learning and satisfaction with teaching of basic courses of ergonomics over Internet--the Ergonetti program, Education and Information Technologies, 14 (1): 81-88. Shyu, H. C. (2000) Using video-based anchored instruction to enhance learning: Taiwan’s experience. British Journal of Educational Technology, 31(1), 57–69.

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Aplicación de la Tecnología BPMS en la Gestión de los Procesos Relacionados con la Actividad Docente en un Centro Universitario Application of BPMS Technology in Process Management Related to Educational Activity in a University Center Pardo JE1 , Mejías AM2 Abstract This paper presents a research project that is developing in order to analyze and foster the use of technology BPMS in processes management related to educational activities that involve a University School. It is intended to briefly reengineering management process through this technology in the management and maintenance tasks in the computer rooms. The aim is to achieve increased efficiency and improve the perception of those agents involved, whether they should develop these processes as those that are the recipients services offered through them.

Resumen En esta comunicación se presenta el proyecto de investigación que está desarrollando con el objeto de analizar y fomentar el uso de la tecnología BPMS en la gestión de los procesos relacionados con la actividad docente a los que tiene que hacer frente un centro universitario. A través de esta tecnología, se pretende realizar una breve reingeniería del proceso de gestión de las aulas informáticas. El objetivo es de conseguir incrementar su eficiencia y mejorar la percepción de los agentes implicados, tanto los que deben desarrollar estos procesos como aquellos otros que son los receptores de los servicios que se ofrecen a través de los mismos.

1Juan

E. Pardo Froján ( e-mail: [email protected]) Grupo OSIG. Dpto. de Organización de Empresas y Marketing. Escuela de Ingeniería Industrial. Universidad de Vigo. C/Maxwell 9, Campus Lagoas-Marcosende, 36310 Vigo. 2Ana

Mª Mejías Sacaluga ( e-mail: [email protected]) Grupo OSIG. Dpto. de Organización de Empresas y Marketing. Escuela de Ingeniería Industrial. Universidad de Vigo. C/Maxwell 9, Campus Lagoas-Marcosende, 36310 Vigo.

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Keywords: Business Process Management System (BPMS), Process Reengineering, Modeling. Palabras clave: Procesos de Negocio, Reingeniería de Procesos, Herramientas BMPS, Modelización.

1 Introducción La actividad empresarial, en particular la industrial, se caracteriza por la existencia de dos clases de procesos fundamentales: los productivos y los relativos al negocio. Durante mucho tiempo los procesos productivos han ocupado el foco de atención principal en sus estrategias, al considerar que en éstos reside una buena parte de su productividad. En este escenario, no es de extrañar el auge que han tenido las herramientas orientadas hacia esta actividad, como ha ocurrido con los sistemas ERP. Sin embargo, es importante reflexionar sobre uno de los principales problemas de la economía española, la incapacidad para lograr el crecimiento económico a través de mejoras en la productividad. Esto se debe, en gran parte, a la poca importancia que se ha dado a los procesos de gestión o de negocio. Cada vez más, las empresas son conscientes de que los procesos de gestión consumen una gran cantidad de recursos y son poco eficientes y, por tanto, repercuten de forma negativa en sus resultados. Otra realidad que se detecta es que existe un gran desconocimiento en las organizaciones de qué se hace, cómo se hace, por qué se hace, quién lo hace,… Este aspecto, si cabe, se presenta en mayor medida en aquellas organizaciones o instituciones, como las universitarias, con una clara orientación al desarrollo de procesos, lo que no deja de ser una aparente contradicción. En los últimos años, la gestión de los procesos se ha convertido en un enfoque indispensable en la estrategia de las empresas/organizaciones al considerarse como un factor clave para la innovación y para el aumento de la productividad de su actividad. Por dicha razón, la aparición de la tecnología BPMS representa una gran oportunidad para la consecución de estos dos objetivos. La visibilidad que se tiene de los procesos, la automatización de los mismos y el control y seguimiento, son algunas de las claves que permiten a las empresas innovar y desarrollar procesos eficientes (Fingar et al., 2003). Los beneficios no son solamente de carácter económico, sino que además consiguen una mayor implicación del personal; saber lo que se hace, para qué sirve y qué consecuencias tiene en el resto de la organización supone un gran estímulo para cualquier trabajador. Por otra parte, la imagen que proyecta una empresa que desarrolla sus procesos de una manera ágil y eficiente le confiere un plus que diferencia a las empresas líderes.

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2 Objetivos del Trabajo El objetivo de este trabajo es aplicar la tecnología BPMS en algunos de los procesos relacionados con la actividad docente de un centro universitario. La realidad de los centros educativos, en particular los de enseñanza universitaria, se caracterizan por una gran diversidad de procesos, algunos con una enorme complejidad, y por una falta generalizada de recursos para acometer dichos procesos de una forma satisfactoria. No es de extrañar que, ante este escenario, algunas instituciones universitarias vean en las herramientas BPMS un gran potencial para mejorar la eficiencia de sus procesos y se hayan marcado una estrategia orientada hacia el uso de estas herramientas. Otro aspecto, sin duda de gran interés, es la necesidad de visualizar los procesos de una manera clara para llegar a comprender el alcance de los mismos. Existe una percepción generalizada de que las tareas que se llevan a cabo dentro de las instituciones educativas no están bien definidas y que consumen una cantidad enorme de recursos, con unos resultados y un nivel de eficiencia muy bajos, sin entrar en el bajo nivel de satisfacción que generalmente manifiestan los usuarios de estos servicios. Para alcanzar este objetivo es necesario entender el alcance de la orientación hacia los procesos de negocio y los beneficios que ésta pueden suponer para la institución. Por ello, dada la enorme cantidad y diversidad de procesos a los que se ve sometida la actividad docente propia de un centro universitario (configuración del plan de horarios, calendario de exámenes, organización de grupos, gestión de recursos tales como laboratorios y aulas informáticas,…) es necesario elegir, en una primera fase, aquellos procesos que permitan entender claramente las ventajas de este enfoque y la utilidad de la tecnología BPMS, para luego extenderlo al resto de los procesos de la organización.

2.1 Ámbito del Trabajo Este proyecto de lleva a cabo en un centro universitario con más de cuatro mil alumnos, lo que hace que la dimensión de los procesos sea de una gran complejidad ya sólo por el importante número de agentes que suelen intervenir en ellos y la enorme variedad de situaciones que se presentan. Una de las características de este centro, al tratarse de una Escuela de Ingeniería industrial, es la existencia de una considerable actividad relacionada con la docencia en su acepción práctica, es decir, aquella que se realiza al margen de las sesiones magistrales. La docencia práctica presenta, de forma resumida, dos tipologías: aquella que desarrolla en laboratorios propios de las materias básicas de corte experimental y, las segundas, las que tienen lugar en aulas informáticas apoyadas por programas generales y/o específicos, donde los alumnos aprenden a manejar herramientas que les permiten

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aplicar aquellas conocimientos desarrollados en las clases de teoría. Es en la gestión de estas últimas donde se centra este trabajo. El Centro cuenta con 15 aulas informáticas, con una capacidad media de 30 puestos, que debe gestionar para atender las necesidades de los contenidos desplegados en las titulaciones que se imparten en la misma de forma satisfactoria atendiendo todas las peticiones demandas de los docentes que van a hacer uso de las mismas a lo largo del curso académico.

2.2 Características del Proceso Si bien el Centro cuenta con una dotación de equipos y de programas que establece en función de unas necesidades, a lo largo del curso se presentan peticiones particulares por parte de los docentes para que se lleve a cabo la instalación de ciertos paquetes o programas informáticos que van a utilizar en el desarrollo de sus prácticas. Estas peticiones son canalizadas a través de un responsable que las analiza y determina la viabilidad y la aprobación de las mismas. En último término, la instalación de los programas se lleva a cabo a través del personal destinado a las labores de mantenimiento de las aulas (generalmente becarios informáticos). Debido al importante número de peticiones y al elevado número de equipos, es imprescindible disponer de un enfoque que sea adecuado pero, además, es necesario contar con un cierto soporte que permita su puesta en práctica. Por otra parte, además de las peticiones de software, están las incidencias que se producen a diario como consecuencia de la actividad que en ellas se desarrolla. La enorme carga que se tiene de peticiones a lo largo de todo el curso se ve agravada por dos cuestiones: el responsable de estas tareas es un miembro del equipo directivo que tiene que compatibilizar esta tarea con otras de la dirección y con las docentes. Por otra parte, el personal que atiende en último término las tareas a realizar es personal con una dedicación parcial y de alta rotación. Por ello, es muy importante definir un modelo de funcionamiento que sea ágil y que las personas puedan entender de forma rápida para que el proceso de adaptación sea lo más reducido posible.

3 La Tecnología BPMS. Características Principales Los sistemas BPM (Business Process Management), también conocidos como ‘Sistemas para la Gestión por Procesos’, constituyen un enfoque moderno de la tecnología de software empresarial para abordar la automatización y optimización del funcionamiento de las organizaciones de toda índole, ante la necesidad de dotarse de una eficacia que permita sobrevivir, prosperar y dar el adecuado servicio en un contexto de intensa competencia y constantes cambios. 1181


La finalidad de un BPM es descomponer la actividad global de una empresa u organización en un conjunto de ‘Procesos’ (entidades de funcionamiento relativamente independiente, aunque conectadas con las demás) que pueden ser analizadas con detalle y cuyas acciones repetitivas puedan ser automatizadas, tanto en lo concerniente a los sistemas como a las personas que intervienen, para optimizar tiempos, oportunidades y costes, sin perder la capacidad de adaptación constante y rápida a los cambios y conservando la coexistencia de métodos seguros con la necesaria flexibilidad para facilitar la intervención activa y fundamental de las personas en los procesos (Freund et al., 2011). Sin entrar demasiado en el detalle de lo que es la tecnología BPMS, en este apartado y para situar nuestro escenario, daremos unas breves referencias sobre los aspectos más relevantes de estas plataformas de trabajo utilizadas para dar soporte a la gestión de los procesos y permitir su automatización. Generalmente, estas herramientas se caracterizan por disponer de un modelizador o workflow que permite la construcción del diagrama que define un determinado proceso (construir el mapa del proceso). Conviene señalar que la gran mayoría de los BPMS ha adoptado para la modelización de sus Clases de Procesos el estándar internacional, llamado BPMN (Business Process Modeling Notation) definido por la organización OMG (Object Management Group). Esta notación permite ser ‘mapeada’ a BPEL4WS (Business Process Execution Lenguaje for Web Sevices), también llamado BPEL, que es el lenguaje XML estándar para la ejecución de procesos. Esta cuestión es muy importante ya que permite exportar/importar el modelado de los procesos de unos sistemas a otros evitando así una atadura a una determinada herramienta.

3.1 Principales Alternativas. Solución Adoptada Aunque el Centro Universitario donde se lleva a cabo este trabajo ha materializado un acuerdo de colaboración con una de las principales compañías de desarrollo de esta tecnología a través de su producto ‘Sistema Empresarial AuraPortal’ (uno de los más valorados por la prestigiosa consultora Gatner), dado el escenario actual de importantes restricciones presupuestarias en el que se mueven las universidades españolas, parece más idóneo un planteamiento basado en la utilización de sistemas de perfil libre. Para este trabajo se ha realizado una breve revisión de este tipo de herramientas encontrándonos con algunas soluciones de gran alcance. Sin pretender ser exhaustivos, entre los principales sistemas existentes encontramos tres que podrían encajar en el desarrollo de este trabajo: BonitaSoft, Intalio y BizAgi. Conviene matizar que las alternativas de software libre no son, en general, completamente gratuitas. Si bien suele existir una versión comunitaria (con prestaciones más limitadas, o alguno de los componentes sin ningún coste), las versiones de corte más empresarial están sujetas al pago de un licenciamiento o de algún 1182


tipo de abono, aunque con unos costes bastante asequibles. Para este proyecto se ha optado por la suite de BizAgi. Este sistema ofrece el componente ‘modeler’ de forma libre. Este componente es básico dentro de un proyecto de estas características, una de las principales razones por la que se ha seleccionado. Otra de las razones es que BizAgi utiliza la notación estándar para Gestión de Procesos de Negocio (BMPN) a la que anteriormente nos referimos. Además, el modelado de sus procesos es relativamente sencillo y a partir de esta notación se puede definir un diagrama de procesos de negocio sin necesidad de ser un experto en tecnologías de la información. Por último, dentro de la complejidad que presentan estos sistemas, BizAgi muestra un entorno de trabajo, en general, bastante amigable.

3.2 Principales Características de la Herramienta Al margen de poseer un buen modelizador basado en la notación estándar BPMN, el software BizAgi presenta otras características que le confieren una gran versatilidad y lo colocan en una buena posición dentro de las soluciones existentes en el mercado. El concepto BPM de Bizagi consiste en generar automáticamente una aplicación Web partiendo del diagrama de flujo del proceso sin necesidad de conocimientos de programación. BizAgi maneja el ciclo de vida completo de los procesos de negocio: Modelización, Ejecución y Mejora Continua. Cada una de estas etapas es administrada mediante distintos componentes que permiten, mediante un entorno gráfico y dinámico, construir una solución basada en procesos.

Fig. 1 Ciclo de Vida de los Procesos contemplado por BizAgi.

Entre las principales características cabe señalar las siguientes:  Las reglas de negocio se manejan en base a un estándar xPath basado en XML. Este lenguaje permite el manejo de tareas complejas.

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 Potente manejo de expresiones. Condiciones o reglas que se deben cumplir dentro de la organización.  Manejo de políticas. Las políticas son las reglas empresariales que se aplican para los procesos de negocio.  Definición de vocabulario. Se pueden ir agregando de forma dinámica todas las expresiones que se requieren para el funcionamiento de los procesos de la organización, construyéndose su propio vocabulario.  Se puede establecer la estructura jerárquica de la empresa, se pueden dar de alta las áreas, la ubicación geográfica, la posición dentro del organigrama y los roles que desempeña una persona en la organización (cada usuario puede tener una o más posiciones).  Existen validaciones para asegurarnos que los datos introducidos sean los correctos. Además, la solución BiZagi presenta una serie de ‘ambientes’ que permiten ir dando los pasos de una manera estructurada. El primer ambiente es el de desarrollo, en el que se define el modelado del proceso. Tras esta primera etapa, se pasa al siguiente nivel, el de prueba, donde se puede visualizar el resultado del proceso de modelización anteriormente realizado. Una vez superado el nivel de prueba, el siguiente paso es pasar al ambiente de producción, donde realmente está preparado para funcionar en toda su extensión con todas las funcionalidades.

Fig. 2 Diagrama del modelado de un proceso a través del modeler de la herramienta BiZagi.

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4 Enfoque metodológico Para llevar a cabo la aplicación de la tecnología BPMS al proceso de gestión de las aulas informáticas de un centro universitario, cuyas características han sido descritas en epígrafes anteriores, es necesario contar con un planteamiento metodológico adecuado. Para este trabajo se han seguido, teniendo en cuentas las recomendaciones de los expertos en este campo (Jeston and Nelis, 2008), las etapas que se recogen en los siguientes apartados:  Análisis detallado del proceso a desarrollar.  Construcción del Diagrama de Procesos basándose en la notación estándar (BPMN).  Datos del Proceso. Debe identificarse de una manera clara y precisa toda la información que afecta al proceso estudiado.  Identificación y creación de formas.  Establecimiento de las Reglas de Negocio que afectan al proceso.  Asignación de recursos (qué se va a hacer, quién, cuándo y cómo lo va a desarrollar).  Posible Interconexión con otros sistemas (SOA).  Verificación del proceso. Comprobación del modelo en un ambiente de prueba.  Puesta a punto del proceso.  Realizar el paso de la etapa de producción.  Aplicación Web de Implementación.  Establecimiento de Indicadores de Gestión del Proceso.

5 Primeros Avances y Conclusiones A pesar de que el proyecto todavía se encuentra en fase de desarrollo y, por tanto, debemos ser prudentes, los resultados obtenidos hasta el momento permiten poner de manifiesto una serie de aspectos que consideramos muy interesantes. Todavía existe un gran desconocimiento de este tipo de herramientas en los entornos de las instituciones universitarias donde, paradójicamente, el volumen de procesos que se desarrollan es muy elevado. Además, con el nuevo marco al que se ven sometidos los centros universitarios por los procesos de acreditación, hacen necesario desarrollar un enfoque orientado hacia los procesos. Tras la construcción de un primer modelo se ha podido comprobar como los usuarios entienden mejor las tareas que hacen y el sentido de las mismas. Quizás la mayor aportación de este trabajo es que ha puesto la primera semilla para crear una cultura de trabajo orientada hacia los procesos y se ha despertado la sensibilización hacia estos temas. Fruto de este proyecto de han derivado una serie de acti1185


vidades formativas que está previsto acometer en el futuro con el objeto de manejar estas herramientas.

6 Referencias Business Process Modeling Notation (BPMN) Information. OMG & BPMI. http://www.bpmn.org/ Fingar H, Smith H (2003) Business Process Management. The Third Wave. Meghan-Kiffer Press Freund J, Rücker B, Hitpass B (2011) BPMN 2.0. Manual de Referencia y Guía Práctica. BPM Center. Edición Hispana Jeston J, Nelis J (2008) Business Process Management. Practical Guidelines to Successful Implementacions, 2th Edition, Elsevier

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10-12th july, 2013

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2013

ISBN 846165410-2

ICIEOM

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Spain

2013

www.cio2013.org

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