Proceedings of the
15th European Conference on Knowledge Management Polytechnic Institute of Santarém Portugal
4-5 September 2014
Volume 1 Edited by Carla Vivas and Pedro Sequeira
A conference managed by ACPI, UK
The Proceedings of the 15th European Conference on Knowledge Management ECKM 2014 The Santarém School of Management and Technology Polytechnic Institute of Santarém, Santarém, Portugal 4‐5 September 2014
Volume One Edited by Dr Carla Vivas and Dr Pedro Sequeira
Copyright The Authors, 2014. All Rights Reserved. No reproduction, copy or transmission may be made without written permission from the individual authors. Papers have been double‐blind peer reviewed before final submission to the conference. Initially, paper abstracts were read and selected by the conference panel for submission as possible papers for the conference. Many thanks to the reviewers who helped ensure the quality of the full papers. These Conference Proceedings have been submitted to Thomson ISI for indexing. Further copies of this book and previous year’s proceedings can be purchased from http://academic‐bookshop.com E‐Book ISBN: 978‐1‐910309‐35‐3 E‐Book ISSN: 2048‐8971 Book version ISBN: 978‐1‐910309‐34‐6 Book Version ISSN: 2048‐8963 CD Version ISBN: 978‐1‐910309‐36‐0 CD Version ISSN: 2048‐898X The Electronic version of the Conference Proceedings is available to download from DROPBOX. (http://tinyurl.com/ECKM2014) Select Download and then Direct Download to access the Pdf file.
Published by Academic Conferences and Publishing International Limited Reading UK 44‐118‐972‐4148 www.academic‐publishing.org
Contents Paper Title
Author(s)
Page No.
Volume One
Preface
ix
Committee
x
Biographies
xiv
Learned Helplessness of Prisoners: Psychology and Knowledge Management Perspective
Juneman Abraham and Rigel Adiratna
1
The Management of Accounting and Taxation Knowledge in Portugal
Rute Abreu, Fátima David and Liliane Segura
8
Linking ICT to the Development of Knowledge‐Based Economy Pillars
Kamla Ali Al‐Busaidi
15
Developing a Learning Disabilities Preliminary Diagnosis Expert System
Ghitha Al‐Kalbani, Maryam Al‐Ajmi, Samia Al‐Fazari and Kamla Ali Al‐Busaidi
22
Zakat Expert System
Afaf Al‐Riyami, Asma Al‐Harthy , Khadija Al‐Amri and Kamla Ali Al‐Busaidi
31
6Investigation of Knowledge Management Support for Business Intelligence in the Saudi Public Sector
Hala Alrumaih and Nesrine Zemirli
39
A Knowledge Management Framework for the Effective Integration of National Archive Resources in China
Xiaomi An, Wenlin Bai, Hepu Deng and Wenrui Zhong
47
Comparison of the Intellectual Capital Between Finland and Spain
Nekane Aramburu, Josune Sáenz, Marta Buenechea, Mika Vanhala and Paavo Ritala
55
Knowledge Sharing Within Extended Enterprises: Case of Pierre‐Emmanuel Arduin, Julien Le Duigou, Diana Penciuc, Marie‐Hélène Abel and Benoît Eynard Product Lifecycle Management systems
63
Barriers in Knowledge Sharing vs the Ability to Create Tourism Supply Chains
Urszula Bąkowska‐Morawska
72
Knowledge Management in Public Administration: Brazil Versus Portugal
Fábio Ferreira Batista and Florinda Matos
82
Effect of ICT on Information Sharing in Enterprises: The Case of Ministry of Development
Özlem Gökkurt Bayram and Hakan Demirtel
94
Blueprinting a Knowledge Sciences Center to Support a Regional Economy
Denise Bedford, John Lewis and Brian Moon
102
Developing an Open Source, Adaptable and Sustainable Method for Conducting Knowledge Management Maturity Modeling and Assessment
Denise Bedford, Margaret Camp, Dessie Hein, Tyler Liston, Jeffery Oxendine and Dean Testa
111
Developing an Interactive View on Intra‐Organisational Knowledge Sharing
Madeleine Block and Tatiana Khvatova
120
Variations in Preferences for the use of Social Networks; Demographic Analysis of Posted Content
Pavel Bogolyubov, Andrey Artemiev, James da Lança, Jay Gopal and Boyka Simeonova
131
Ettore Bolisani, Enrico Scarso and Luca Giuman Wiki as a Knowledge Management System in a Small Project‐Based Company: Benefits, Issues and Managerial Challenges
138
Communities of Practice and Renewable Distributed Energy: The CIVIS Experience
Matteo Bonifacio, Andrea Capaccioli, Giacomo Poderi, Maurizio Marchese and Vincenzo D’Andrea
148
Putting Your Money Where Your Mouth is: Monetizing Knowledge Using Communication Roles
Karl Joachim Breunig and Hanno Roberts
156
i
Paper Title
Author(s)
Page No.
Knowledge Management in Municipalities: What Affects Customer Satisfaction?
Elisabeth Brito, Leonor Pais, Lisete Mónico and Liliana Jorge
164
Sustainability of Open Distance E‐Learning Institutions as Knowledge Producers: A Theoretical Perspective
Sheryl Buckley and Apostolos Giannakopoulos
173
The ICT Systems Developments in Maintenance – From Data Processing Into Knowledge Driven Approaches
Jaime Campos
182
The Specific Valorisation of Competitive Intelligence Profiling on the Software Industry
Alexandru Capatina and Gianita Bleoju
189
Knowledge Management Practices for Corporate Social Responsibility: A Family Business Perspective
Antonio José Carrasco Hernández and Daniel Jimenez Jimenez
198
Towards a Methodology for Lessons Learned Practice in Complex Product Development
Koteshwar Chirumalla
205
The Development of the Polish Qualifications Framework as an Application of Knowledge Management in Public Policy
Agnieszka Chłoń‐Domińczak Łukasz Sienkiewicz and Katarzyna Trawińska‐Konador
214
Designing and Testing an AHP Methodology to Prioritize Critical IC Elements for Product Innovation
Ricardo Costa and Ana Paula Ramos
223
Knowledge Management on PMO’s Perspective: A Sys‐ tematic Review
José Adson Cunha, José Figueiredo, Florinda Matos and João Thomaz
233
COBIT5 An Approach to Analysing an Organization’s Knowledge and Knowledge Management During due Diligence
Bostjan Delak, Nadja Damiji and Grzegorz Marek Majweski
242
Knowledge and Intellectual Capital in Smart City
Renata Paola Dameri, Francesca Ricciardi and Bea‐ trice D’Auria
250
Exploring the Impact of Mental Models on Teamwork and Project Performance
Brit‐Eli Danielsen, Rune Kristiansen Valle, Trine Marie Stene
258
KMSS: A Knowledge Management System for Senology
Souad Demighaand Corinne Balleyguier
268
The Knowledge Fecundity Framework: Enabling Integrative Knowledge Management Strategy
Sally Eaves
278
Knowledge Transfer – a Means to Manage the Interplay Between Changes and Time‐usage in Construction Projects
Anandasivakumar Ekambaram, Agnar Johansen, Jan Alexander Langlo and Pedro Rondón
288
A Conceptual Model to Design a Collective Intelligence System Supporting Technology Entrepreneurship
Gianluca Elia, Alessandro Margherita, Giuseppe Vella, Francesca Grippa and Andrea Cappilli
297
Virtual Communities of Practice – Experiences From VCoP
Martina Ergan, Tone Vold and Etty Nilsen
306
The Role of Competence Brokering in Regional Innovation and Development
Leif Estensen, Terje Bakken and Anandasivakumar Ekambaram
311
Knowledge Absorption in Organisations – Development of a Conceptual Process Model
Nina Evans and Rachelle Bosua
321
Epistemology: The Feeble Philosophical Foundation of Knowledge Management
Doron Faran
330
Engaging to Perform: Job Satisfaction as a Mediator
Pedro Ferreira and Elizabeth Real de Oliveira
336
Wiki as a Knowledge Management Tool: The Case of a Non‐Profit Administrative Entity
Vitor Hugo dos Santos Ferreira
343
ii
Paper Title
Author(s)
Page No.
The Role of Human Resource Management in Knowledge Management: The cases of Training and Ca‐ reer Management
Elisa Figueiredo, Leonor Pais, Samuel Monteiro and Lisete Mónico
353
Personal Knowledge Sharing: Web 2.0 Role Through the Lens of Generations
Zoltán Gaál, Lajos Szabó and Nóra Obermayer‐ Kovács
362
Shifting From a Local to Sector‐Based Strategy for Supporting the Sharing of Knowledge and Skills: The Case of 911 Emergency Call Centres
Charles Gagné and Georges Toulouse
371
Computer Assisted Reasoning as a Support for Knowledge Management
Johan Garcia
377
A Model to Measure the Contribution Degree of Know‐ How/Knowing‐That of the Organization
Sahar Ghrab, Ines Saad, Gilles Kassel and Faiez Gargouri
386
Developing a Community of Practice to Learn, Share and Improve in Emergency Management
Raquel Gimenez, Josune Hernantes, Leire Labaka, Jose Maria Sarriegi and Ana Laugé
395
Merging Knowledge Management with Project Management
Meliha Handzic and Nermina Durmic
402
An Empirical Comparison Study of the Effect of Chief Knowledge Management Officers and Knowledge Management Systems on Innovation and Financial Outcomes
Harold Harlow
410
Advancements, Challenges and Future Research in Knowledge Management: Results From a Global Expert Study
Peter Heisig
419
TSM: An Instrument That Supports Industrial Doctoral Projects
Ilona Heldal, Eva Söderström, Lars Bråthe and Robert Murby
428
The Crafting of Online Knowledge Construction
Inge Hermanrud
438
Volume Two
Knowledge Management in an Academic Context: A Framework for Successful Intranet 2.0 Implementation
Eli Hustad, Fredrik Kydland and Marit Aakre
444
Knowledge Management Practices and Firm Performance – Empirical Findings From Finland
Henri Inkinen and Aino Kianto
455
Organizational Culture and Knowledge Transfer: Evidence From the Bruneian Public Organization Employees
Md. Zahidul Islam, Mohammad Habibur Rahman, Ikramul Hasan and Hazri Bin Haji Kifle
463
Knowledge Elicitation Through Collaborative Modelling: A Case Study of the British Railway Industry
Mahsa Jahantab, Alexeis Garcia‐Perez and Siraj Shaikh
471
Culture and Performance: A Learning Orientation for the Daniel Jiménez‐Jiménez; Juan R. Fernández‐Gil; Micaela Martínez‐Costa Financial Sector
480
Managerial Factors Behind the Development of Trust in Inter‐Organizational Knowledge Networks
Rita Juceviciene and Giedrius Jucevicius
489
The Organisation’s Learning in the Multinational Company: What Kind of Knowledge Sources Does Influence It?
Palmira Juceviciene and Vyda Mozuriuniene
499
From Knowledge to Smart City: A Conceptual Study
Robertas Jucevicius and Giedrius Jucevicius
508
Knowledge Management – Time to Rethink the Discipline
Nowshade Kabir
516
iii
Paper Title
Author(s)
Page No.
Alexander Kaiser, Florian Kragulj and Stefan Gächter Recent Developments and Approaches to Knowledge Creation and Learning in Systems. A Proposal for Further Innovation The Impact and Possible use of the Zen Methods in Knowledge Management
Marcela Katuščáková
An Empirical Study of Knowledge Management Practices Yasmina Khadir‐Poggi and Mary Keating in Small Asset Management Firms Based In Ireland
524
531 539
Radwan Kharabsheh, Khalid Jarrar and Boyka Simenonva
547
Enabling Knowledge Creation: Does Employees’ Training Stimulate R&D Activities?
Tomasz Kijek and Marek Angowski
556
Process‐Oriented Knowledge Management in SMEs
Holger Kohl, Ronald Orth, Erik Steinhöfel
563
The Impact of Competitive Strategies on Responsive Market Orientation, Proactive Market Orientation, Learning Orientation and Organizational Performance
The Cause and Impact of the Development of Coworking Jaroslava Kubátová in the Current Knowledge Economy
571
The Role of Intellectual Capital in a Credit Cooperative: A Carmem Leal, Carla Susana Marques, Carlos Peixeira Marques and Elizomar Braga‐Filho Multivariate Analysis
578
Knowledge Management and Transfer: Modeling Inter‐ actions in Small Businesses
Monique Lortie, Idriss Kefi1 and Lise Desmarais
586
TK Aware Business Process Simulation: A Case Study With Slovenian High‐Achieving Company From the SME Sector
Grzegorz Marek Majewski, Boštjan Delak and Nadja Damij
593
The Collaborative Enterprise in the Knowledge Econo‐ my: Motivational Profiles
Simone Manfredi and Roberta Antonelli
601
Strategic Knowledge Management, Innovation and Per‐ formance: An Initial Study of Portuguese Footwear Companies
Carla Susana Marques, Carmem Leal, Carlos Peixeira Marques and Ana Rita Cardoso
609
The Influence of User eSkills on Online Health Care Ser‐ vices Success
Eva Martínez‐Caro, Juan Gabriel Cegarra‐Navarro and Antonio Juan Briones‐Peñalver
619
Knowledge Management in Multinational Companies: The Repatriates’ Role in the Competitive Advantage in Subsidiaries
Dora Martins and Eduardo Tomé
628
"Customer" Knowledge Management in Healthcare
Sara McCracken and John Edwards
637
Inter‐Organizational Knowledge Sharing Networks: A Study on a Business Network
Andreia Meireles, Leonor Pais and João Daniel
641
Development and Initial Validation of a Survey for Intel‐ lectual Capital in Universities
Patricia Mercado‐Salgado, Pedro Gil‐Monte and María del Rosario Demuner‐Flores
650
Impact of Knowledge Acquisition to Strategic Infor‐ mation Systems Plan Implementation in Ethiopia
Peter Mkhize
659
Storytelling and Leadership Skills of Managers
Ludmila Mládková
667
Knowledge Management Implementation in UK Public Sector
Sandra Moffet
676
From Data to Knowledge: KM Implementation in the UK Car Retail Industry
Sandra Moffett, Stephanie Conn ,Andrea Reid and Karise Hutchinson
684
Influence of Knowledge Management Practices on Mu‐ nicipalities’ Image Among Their Users
Lisete Mónico, Leonor Pais, Elisabeth Brito and Ornela Harris
692
iv
Paper Title
Author(s)
Page No.
Knowledge Management and HRM – Theoretical and Empirical Links
Samuel Monteiro and Leonor Pais
700
Polish National Knowledge Management Styles: Studies in Selected Companies Representing Creative Industries
Mieczysław Morawski
708
Alignment Model of Knowledge Management Strategies with Human Resource Strategies
Mirali Seyed Naghavi and Shahla Sohrabi
715
Critical Success Factors for Effective Knowledge Sharing: Integrating Intra‐Organizational Communication and KM Tools
Martin Nkosi Ndlela
724
Systematic Description of Nursing Actions Based on Goal Satoshi Nishimura, Yoshinobu Kitamura, Munehiko Sasajima,and Riichiro Mizoguchi Realization Model
730
Knowledge Management Perspectives: The Portuguese MNCs of Romania and Poland
Frederico Nunes and Carmina Simion
740
Maturity Model for Knowledge Management and Stra‐ tegic Benefits
Mírian Oliveira and Cristiane Drebes Pedron
748
Knowledge Management in Small and Micro Enterprises: Mirian Oliveira, Cristiane Drebes Pedron, Felipe Nodari and Rodolfo Ribeiro Applying a Maturity Model
757
Knowledge Sharing: Brazilian x Portuguese Companies
Mírian Oliveira, Carla Curado, Mario Romão and Antonio Carlos Gastaud Maçada
765
Modes of Information (Knowledge) Sharing: A Case Study
Gary Oliver
774
The use of social networks in undergraduate projects guiding: Mundus Spectaculum
Beatriz de Almeida Pacheco, Ilana deAlmeida Souza‐ Concilio, Simone Freitas
783
Deepening the Understanding of Knowledge Manage‐ ment Dimensions
Leonor Pais , Lisete Mónico, Nuno Rebelo dos San‐ tos and Sara Almeida
792
The Innovation Lessons: Organizational Narratives of Applied Knowledge in Technology‐Based Organizations
Margarida Piteira and Jorge Gomes
802
Managing Knowledge Generation at Universities
Evgeny Popov and Maxim Vlasov
811
Managing Hospitals: Who Knows Best, and at What Lev‐ el? Organizational and Operational Learning in Public Management Reforms
Vítor Raposo, Teresa Carla Oliveira and Diana Tarrafa
817
The Importance of Knowledge Management in the Suc‐ cession Process of Family Businesses
Paula Rodrigues, Ana Pinto Borges and Alberto Aleixo
826
Building Organisational Agility Through an Unlearning Context
José Roldán, Juan Gabriel Cegarra and Gabriel Cepeda
834
Antecedents and Consequences of Knowledge Man‐ agement Performance
José Roldán, Juan Real and Silvia Sánchez‐Ceballos
843
Fostering Knowledge Sharing Through Intrinsic Reward
Svetlana Sajeva
854
Volume Three
Smart Intangible Knowledge Assets Valuation
Maria‐Isabel Sánchez‐Segura, Alejandro Ruiz‐Robles, Fuensanta Medina‐Dominguez and Antonio Amescua Seco
862
Software Agents: Solution to KM Anxiety of Japanese in Limited Trust Situations
Thomas Schalow
868
Innovating Management or Managing Innovation, What Matters for the Brazilian SMEs?
Camilo Augusto Sequeira, Markus Will and Eloi Fernández y Fernández
874
v
Paper Title
Author(s)
Page No.
Evaluation Criteria of Experts for Knowledge Manage‐ ment System of a Business School
Gulzada Serzhan, Gulffarida Tulemissova, Svetlana Iskakova and Ermek Ramazanov
879
Dynamics of Innovation Networks: The Role of HEIs in Venture Creation
Jorge Manuel Marques Simões, António Anacleto Viegas Ferreira, Rodrigo Morais and Guida Coelho
885
Knowledge Management in Call Centres: The Work Team as Unit of Analysis
Cristina Souza de Castro, Leonor Pais and Lisete Mónico
893
KM Practices, Innovation Strategies and Firm Perfor‐ mance: Evidence From 16 European Economies
Inga Stankevice
903
Compliance ‐ why do People Follow Procedures?
Trine Marie Stene
912
Successful and Safe Operation ‐ A Combination of Indi‐ vidual, Team and Organization Training
Trine Marie Stene, Brit‐Eli Danielsen and Rune Kris‐ tiansen Valle
923
Integration of Knowledge Management into Business Process
Marta Christina Suciu, Cristina Andreea Florea and Ileana Teodorescu
932
Concept of Knowledge and Research: How to Study Tacit Vlastimil Švec, Radim Šíp and Jana Krátká Dimension of Knowledge
939
Inter‐Professional Learning for Teaching – Using Digital Tools
Ann Svensson and Gunilla Forssell Eriksson
946
Knowledge Transfer in Hub‐And‐Spokes Industrial Dis‐ tricts: Power and Socio‐Cultural Relationships in the Basilicata Oil District, Italy
Giovanna Testa
954
Development of the Knowledge Economy and Regional Innovation Policy: Russian Practice
Elena Tkachenko and Sergey Bodrunov
964
KM and Politics at the Highest Level: An Exploratory Analysis
Eduardo Tomé, Paula Figueiredo, Dora Martins3 and Klaus Bruno Schebesch
974
Aligning Knowledge Sharing Strategy With Organization‐ al and Cultural Contexts: An Information System Per‐ spective
Thierno Tounkara and Pierre‐Emmanuel Arduin
983
Knowledge Capital Earnings of a Company Listed on Warsaw Stock Exchange
Anna Ujwary‐Gil
994
Knowledge Sharing with International Residents in Times of Disaster: The Role of the Public Sector
Jiro Usugami
1001
Corporate Intellectual Capital Disclosure in the Baltic States: A Comparative Empirical Study
Lina Užienė
1010
The Port as a “Non Consensual” Organisation: An IC Management Perspective
José Vale, Manuel Branco and João Ribeiro
1020
Education Quality and Economic Performance in Europe
Ana Cláudia Valente, Isabel Salavisa and Sérgio Lagoa
1028
The Practice of Entrepreneurial Excellence: An Overview of Methodologies for Achieving Excellence in the Knowledge Economy Context
José Maria Viedma, Maria do Rosário Cabrita, Florinda Matos and Virgílio Cruz‐Machado
1037
Integrating Knowledge Management in a Business Strat‐ Carla Vivas, Pedro Sobreiro and Rui Claudino egy Process Operationalized Using Process Management Approach New Takes on Learning in Organizations When Using Role Play Simulation
Tone Vold, Sule Yildirim‐Yayilgan and Jan‐Oddvar Sørnes
vi
1045
1055
Paper Title
Author(s)
Page No.
Conceptual Framework for Development of Computer Technology Supporting Cross‐Linguistic Knowledge Dis‐ covery
Igor Zatsman, Nadezhda Buntman, Mikhail Kruzhkov, Vitaly Nuriev and Anna Zalizniak
1063
Critical Success Factors for Knowledge Management in SMEs in the KIBS Sector
Malgorzata Zieba
1072
PHD Research Papers
1081
Knowledge Sharing and Information Security: A Para‐ dox?
Ghosia Ahmed, Gillian Ragsdell and Wendy Olphert
1083
Effective Knowledge Management Using Tag‐Based Se‐ mantic Annotation for web of Things Devices
Mohammad Amir, Y. Fun Hu and Prashanti Pillai
1091
Information and Knowledge in Spanish Science and Technology Parks
Ivett Aportela Rodríguez
1099
Knowledge Sharing in Virtual Communities: A Compari‐ son of Three Different Cultures
Shahnaz Bashir, Abel Usoro and Imran Khan
1108
The Tension Between Competitive and Collaborative Forces in Agricultural Research: Impact on Knowledge Sharing Within a Public Research Organisation
Patricia Bertin, Jenny Fry and Gillian Ragsdell
1118
Trust and Employee Competence Utilization – Empirical Testing of a Model
Britta Bolzern‐Konrad and Ērika Šumilo
1127
Intellectual Capital as an Engine of Growth: Analysis of Causality for North Cyprus Economy
Behiye Çavuşoğlu
1137
Identification of Tacit Knowledge Associated With Expe‐ rience: A Chinese Software Industry Study
Hui Chen, Gillian Ragsdell and Ann O’Brien
1147
“Overcoming Trust Barriers: Evaluating Inter‐ Organisational Knowledge Sharing in UK Online Retail Sector”
Rozina Chohan, Mahmood Shah, Mitchell Larson and Mary Welch
1156
Knowledge Processes, Absorptive Capacity and Innova‐ tion: Contributions for a Systematic Literature Review
Vítor Costa and Samuel Monteiro
1164
Semantic‐Based Framework for Innovation Manage‐ ment
Lamyaa El Bassiti and Rachida Ajhoun
1173
Identifying Future Research Directions in Knowledge Management from a Latin American and the Caribbean Perspective: An Exploratory Study
Ernesto Galvis‐Lista, Lucía Rodríguez‐Aceves, Peter Heisig
1183
Knowledge Management in Lithuanian Innovative Busi‐ ness Organizations
Ingrida Girnienė and Zenona Atkočiūnienė
1193
A Possible Approach for Evaluating Knowledge Workers: Case Study in a Romanian's University
Maria Luminita Gogan
1202
An Innovative Model for Evaluating National Intellectual Capital
Maria‐Luminita Gogan
1211
Intellectual Capital and Human Capital, State of art and Proposal of Framework
Belkacem Iskhar and Latifa Mahdaoui
1219
MADM Methods in Practice: Linking Competencies to Employees' Appraisal and Total Reward
Katerina Kashi and Petra Horváthová
1229
The Role of Knowledge Management in Organisational Performance
Stanford Makore and Chuks Eresia‐Eke
1240
Perspectives and Implications of Sharing Processes Within Organisations: The Case Study
Tereza Otcenaskova and Vladimir Bures
1249
vii
Paper Title
Author(s)
Page No.
A Knowledge Creation Innovation for Web‐Knowledge‐ Base System Using Knowledge Management, and Data and Knowledge Engineering
Patcharaporn Paokanta, Napat Harnpornchai, Michele Cecarelli
1255
Knowledge Sharing Using web Mining for Categorization and Disambiguation of Structured and Unstructured Data
Leandro Ramos da Silva and Nizam Omar
1265
Good Practices in Virtual Leadership – The E‐3cs Rule (Communication, Trust and Coordination)
João Paulo Rodrigues da Silva Samartinho, Paulo Fernando Lopes Resende da Silva Jorge and Manuel Alves de Faria
1272
The Role of Brand Knowledge in the Creation of Cus‐ tomer Capital
Noelia Sánchez‐Casado; Anthony Wensley; Eva Tomaseti‐Solano and Juan‐Gabriel Cegarra‐Navarro
1283
Models for Describing Incident Knowledge Sharing Prac‐ tices: The Case Study of UK Hospital
Negar Monazam Tabrizi
1291
Knowledge Management in Open Innovation Context
Erika Tauraitė‐Kavai
1301
Application of Semantic Network for Knowledge Sharing in the Field of Marketing
Stanislav Vojir and Zdenek Smutny
1306
Transactive Memory System Measurement Methods – Review and Future Perspectives
Volker Wagner
1314
Masters Research Papers Leadership Role and Competencies of Managers in Knowledge Intensive Context
1323 Mustafa Doruk Mutlu
Work In Progress Paper
1325 1333
From Complex Maths to Simple Stories: A Knowledge Management Approach to Education
Nicole Bittel and Marco Bettoni
1335
The Knowledge Management Context of Cloud Based big Data Analytics
Irina Neaga and Shaofeng Liu
1339
Customer Capital Management in Business Intelligence Projects: An Exploratory Study
Lívia Vasconcelos, Florinda Matos and João Thomaz
1344
Late Submission Approach for Processes and Methods for The Integra‐ tion of Knowledge Transfer in Project Work
1349 Prof. Dr.‐Ing. habil. Christian‐Andreas Schumann; Dipl.‐Inf. Claudia Tittmann
viii
1351
Preface These proceedings represent the work of researchers presenting at the 15th European Conference on Knowledge Manage‐ ment (ECKM 2014). We are delighted to be hosting ECKM at the The Santarém School of Management and Technology ‐ Poly‐ technic Institute of Santarém, Portugal on the 4‐5 September 2014. The conference will be opened with a keynote from Nuno Manuel C.F. Guimarães, University Institute of Lisbon, Portugal. The second day will be opened by Rui Lança who is a consultant in the area of Team Coaching and Leadership in Portugal. ECKM is an established platform for academics concerned with current research and for those from the wider community involved in Knowledge Management, to present their findings and ideas to peers from the KM and associated fields. ECKM is also a valuable opportunity for face to face interaction with colleagues from similar areas of interests. The conference has a well‐established history of helping attendees advance their understanding of how people, organisations, regions and even countries generate and exploit knowledge to achieve a competitive advantage, and drive their innovations forward. The range of issues and mix of approaches followed will ensure an interesting two days. 264 abstracts were initially received for this conference. However, the academic rigor of ECKM means that, after the double blind peer review process there are 129 academic papers, 28 PhD research papers, 1 masters research pape, and 3 Work in Progress papers published in these Conference Proceedings. These papers reflect the continuing interest and diversity in the field of Knowledge Management, and they represent truly global research from some many different countries, including Algeria, Argentina, Australia, Austria, Belgium, Bosnia and Herzegovina, Brasil, Canada, China, Colombia, Czech Republic, Finland, France, Genova, Germany, Hungary, Indonesia, Iran, Israel, Italy, Japan, Jordan, Kazakhstan, Lithuania, Madrid, Mexico, , Morocco, Norway, Oman, Poland, Portugal, Romania, Russia, Russian Federation, Saudi Arabia, Slovakia, South Africa, Spain, Sweden, Switzerland, Thailand, Tunisie, Turkey, Turk‐ ish Republic of Northern Cyprus, UK, United Arab Emirates, USA. We hope that you have an enjoyable conference. Dr Carla Vivas and Dr Pedro Sequeira Co‐Conference Chairs September 2014
ix
Conference Committee Conference Executive Dr Carla Vivas, Polytechnic Institute of Santarém, Santarém, Portugal Pedro Sequeira, Polytechnic Institute of Santarém, Santarém, Portugal Dr Susana Leal, Polytechnic Institute of Santarém, Santarém, Portugal Maria Barbas, Polytechnic Institute of Santarém, Santarém, Portugal Mini track chairs Dr. Thomas Schalow, University of Marketing and Distribution Sciences, Kobe, Japan Assoc. Prof. Dr. Mustafa Sağsan, Near East University, Turkish Republic of Northern Cyprus Dave Snowden, Cognitive Edge Dr. Juan Gabriel Cegarra, Universidad Politécnica de Cartagena, Spain Dr. Gabriel Cepeda, University of Seville, Spain Dr Peter Heisig, Leeds University Business School, UK Dr Florinda Matos, Polytechnic Institute of Santarém, Portugal Dr Sandra Moffett, University of Ulster’s, Northern Ireland, UK Dr Jan M. Pawlowski, University of Jyväskylä, Finland Prof Aino Kianto, Lappeenranta University of Technology, Finland Dr Radwan Kharabsheh, Hashemite University, Jordan Committee Members The conference programme committee consists of key individuals from countries around the world working and researching in the Knowledge Management and IS community. The following have confirmed their participation: Mahmoud Abdelrahman (Manchester Business School, UK); Dr. Mohd Syazwan Abdullah (Universiti Utara Malaysia, Malay‐ sia); Habib Abubakar (African Development Bank Group, Tunisia); Pichamon Adulavidhaya (Bangkok University, Thailand); Dr. Ali Alawneh (Philadelphia University, Jordan); Dr. Abdallah Al‐Shawabkeh (University of Greenwich, UK); Prof. Dr. Eckhard Ammann (Reutlingen University, Germany); Albena Antonova (Sofia University, Bulgaria); Dr. Nekane Aramburu (University Of Deusto, San Sebastian, Spain); Dr. Derek Asoh ("Ministry of Government Services, Ontario, Canada); Ass Prof. George Balan (Romanian‐German University, Romania); Dr Tabarak Ballal (The University of Reading, UK); Dr. Joan Ballantine (Uni‐ versity of Ulster, UK); Dr. Pierre Barbaroux (French Air Force Academy / Research Center of the French Air Force, France); Prof. Dr. Aurelie Aurilla Bechina Arnzten (College University of Bruskerud, Norway); Prof. Julie Béliveau (University of Sher‐ brooke, Canada); Dr. David Benmahdi (Université Paris 8, France); Ass Prof. Maumita Bhattacharya (Charles Sturt University, Albery, Australia); Prof. Dr. Markus Bick (ESCP Europe Wirtschaftshochschule Berlin, Germany); Heather Bircham‐Connolly (University of Waikato, Hamilton, New Zealand); Dr. Claudia Bitencourt (Universidade do Vale do Rio dos Sinos , Brazil); Nicole Bittel (Swiss Distance University of Applied Sciences, Switzerland); Pavel Bogolyubov (Lancaster University Manage‐ ment School, Dpt. of Management Learning and Leadership, UK); Prof. Karsten Böhm (University of Applied Sciences, Kuf‐ stein, Austria); Dr. Ettore Bolisani (University of Padua, Vicenza, Italy); Prof. Ionel Bostan (University of Iasi, Faculty of Eco‐ nomics, Romania); Prof. Constantin Bratianu (Academy of Economic Studies, Bucharest, Romania, Romania); Dr. Antonio Juan Briones (Universidad Politécnica de Cartagena, Spain); Prof. Elisabeth Brito (University of Aveiro, ESTGA, Portugal); Dr. Sheryl Buckley (Unisa, South Africa); Dr. Dagmar Caganova (Slovak University of Technology Faculty of Materials Science and Tech‐ nology, Slovakia); Prof. Leonor Cardoso (University of Coimbra, Portugal); Prof. Sven Carlsson (School of Economics and Man‐ agement, Lund University, Sweden); Dr. Gabriel Cepeda Carrion (Universidad de Sevilla, Spain); Dr. Juan‐Gabriel Cegarra‐ Navarro (Universidad Politécnica de Cartagena, Spain); Daniele Chauvel (SKEMA Business School , France); Satyadhyan Chick‐ erur (B V Bhoomaraddi College of Engineering and Technology, Hubli,, India); Ana Maria Correia (Universidade Nova de Lis‐ boa, Portugal); Dr. Bruce Cronin (University of Greenwich Business School, UK); Anikó Csepregi (University of Pannonia, De‐ partment of Management, Hungary); Roberta Cuel (University Of Trento – Faculty Of Economics, Italy); Prof Marina Dabic (Nottingham Trent University, UK); Dr. Farhad Daneshgar (University of New South Wales, Australia); Dr. Ben Daniel (Univer‐ sity of Saskatchewan, Saskatoon, Canada); Prof. Monica De Carolis (University of Calabria, Italy); Prof. Annunziata De Felice (University of Bari, Italy); Dr. John Deary (Independent Consultant, UK, Italy & Dubai); Dr. Paulette DeGard (The Boeing Com‐ pany, Seattle, USA); Dr. Izabela Dembinska (University of Szczecin, Poland); Dr. Charles Despres (Conservatoire des Arts et Metiers, Paris, France); Dr. Mihaela Diaconu ("Gheorghe Asachi" Technical University, Romania); Zeta Dooly (Waterford Insti‐ tute of Technology , Ireland); Dr. Yan Qing Duan (Luton Business School, University of Luton, UK); Nasser Easa (University of Stirling, Scotland, UK); Sally Eaves (Sheffield Hallam University, UK); Prof. John Edwards (Aston Business School, UK); Dr. An‐ andasivakumar Ekambaram (SINTEF, Norway); Jamal El Den (Charles Darwin University, Australia); Dr. Steve Eldridge (Man‐ chester Business School, , UK); Isaac Enakimio (University of Greenwich/Kent and Medway Health Informatics, USA); Dr. Scott Erickson (Ithaca University, USA); Mercy Escalante (Sao Paulo University, Brazil); Dr. Mansour Esmaeil Zaei (Panjab University, India); Dr Iancu Eugenia (Stefan cel Mare University, Romania); Nima Fallah (University of Strasbourg, France); Dr. Doron Fa‐ ran (Ort Braude College, Israel); Dr. Péter Fehér (Corvinus University of Budapest, Hungary); Dr. Silvia Florea (Lucian Blaga University of Sibiu, Romania); Dr. Andras Gabor (Budapest University of Economic Sciences and Public Administration, Hun‐ gary); Brendan Galbraith (University of Ulster, UK); Ass Prof. Balan George (German‐Romanian University, Romania); Elli x
Georgiadou (Middlesex University, UK); Dr. Lilia Georgieva (Heriot‐Watt University, UK); Prof. Secundo Giustina (University of Salento, Italy); Prof. Secundo Giustina (University of Salento, Italy); Dr. Andrew Goh (International Management Journals, Singapore); Gerald Guan Gan Goh (Multimedia University, Melaka, Malaysia); Dr Golestan Hashemi Golestan (Iranian Re‐ search Center of Creanovatology , Innovation Science, Iran); Dr. Miguel Gonzalez‐Loureiro (University of Vigo, Spain); Dr. Lo‐ ganathan Narayansamy Govender (University of Kwazulu‐Natal, South Africa); Francesca Grippa (Scuola Superiore ISUFI, Uni‐ versity of Salento, Italy); Norbert Gronau (University of Potsdam, Germany); David Gurteen (Gurteen Associates, UK); Dr. Leila Halawi (Bethune Cookman University, USA); Linda Cathrine Hald (NTNU, Norway); Dr. Matthew Hall (Aston Business School, UK); Prof. Meliha Handzic (International Burch University , Bosnia and Herzegovina); Dr. Harold Harlow (Wingate Univeristy, USA); Deogratias Harorimana (Southampton Solent University, , UK); Dr. Mahmoud Hassanin (Pharos Univer‐ sity,Alexandria, Eygpt); Dr. Liliana Hawrysz (Opole Univarsity of Technology, Poland); Prof. Igor Hawryszkiewycz (University of Technology, Sydney, Australia); Dr. Ciara Heavin (University college cork, UK); Dr. Peter Heisig (Leeds University Business School, UK); Dr Nina Helander (University of Vaasa, Finland); Remko Helms (Universiteit Utrecht, The Netherlands); Dr. Ali Hessami (Vega Systems Ltd., UK); Dr. Eli Hustad (University of Agder, Norway); Fahmi Ibrahim (Glasgow Caledonian Univer‐ sity, UK); Dr. Thomas Jackson (Loughborough University, UK); Dr. Harri Jalonen (Turku University of Applied Sciences, Finland); Prof. Brigita Janiunaite (Kaunas University of Tehnology, Lithuania); Dr. Daniel Jimenez (Universidad de Murcia, Spain); Prof. Palimra Juceviciene (Kaunas University of Technology , Lithuania); Prof. Robertas Jucevicius (Kaunas University of Technology , Lithuania); Dr. Magdalena Jurczyk‐Bunkowska (Opole University of Technology, Poland); Selvi Kannan (Victoria University, Melbourne, Australia); Dr. Silva Karkoulian (Lebanese American University Beirut Campus, Lebanon); Dr. Sarinder Kaur Kashmir Singh (University Malaya, Malaysia); Dr. Marcela Katuščáková (University of Žilina, Slovakia); Prof. Dr. Turksel Kaya Bensghir (TODAIE‐Public Administration Institute for Turkey and the Middle East, Turkey); Dr. Radwan Kharabsheh (Hashemite University Jordan, Jordan); Dr. Prof. Aino Kianto (Lappeenranta University of Technology, Finland); Monika Kli‐ montowicz (University of Economics in Katowice, Poland); Ute Klotz (Lucerne University of Applied Sciences and Arts, Switzer‐ land); Dr. Andrew Kok (Western Cape Government, South Africa); Ass.Prof.Dr. Jaroslava Kubatova (Palacky University, Czech Republic); Dr. Bee Theng Lau (Swinburne University of Technology, Australia); Rongbin W.B Lee (The HongKong Polytechnic University, Hong Kong); Prof. Dr. Franz Lehner (University of Passau, Germany); Jeanette Lemmergaard (University of South‐ ern Denmark, Denmark); Prof. Ilidio Lopes (Polythenic Institute of Santarém, Portugal); Prof. Monique Lortie (Universit du Qu bec Montreal, Canada); Dr. Maria de Lourdes Machado‐Taylor (CIPES, Portugal); Dr. Agnes Maciocha (Institute of Art, Design, and Technology, Ireland); Avain Mannie (Dept of Finance, Port Elizabeth, South Africa); Prof. Virginia Maracine (Academy of Economic Studies, Bucharest, Romania); Dr. Farhi Marir (London Metropolitan University, UK); Prof. Dora Martins (ESEIG‐IPP (Superior School of Industrial and Management Studies, Polytechnic of Porto), Portugal); Prof Antonio Martins (Universidade Aberta, Portugal); Prof. Maurizio Massaro (Udine University, Italy); Fiona Masterson (National University of Ireland, Galway, Ireland); Florinda Matos (ISCTE‐IUL, Lisbon, Portugal , Portugal); Prof. Jane McKenzie (Henley Business School, UK); Dr. Dalila Mekhaldi (University of Wolverhampton, UK); Dr. Robert Mellor (Kingston University, UK); Prof. Dr. Kai Mertins (Fraunhofer‐ IPK, Germany); Dr. Anabela Mesquita (School of Accounting and Administration of Porto (ISCAP) / Politechnic Institute of Porto (IPP), Portugal); Kostas Metaxiotis (National Technical University Athens, Greece); Dr. Antonio Leal Millan (Universidad de Seville, Spain); Dr. Kristel Miller (Queens University, Northan Ireland); Ludmila Mladkov (University of Economics Prague, Czech Republic); Dr. Sandra Moffett (University of Ulster, Londonderry, UK); Prof. Samuel Monteiro (University of Beira Inte‐ rior, Portugal); Dr. Mahmoud Moradi (University of Guilan, Iran); Dr. Arturo Mora‐Soto (Carlos III University of Madrid, Ma‐ drid); Prof. Oliver Moravcik (Slovak University of Technology, Slovakia); Prof. Mieczysaw Morawski (Wroclaw University of Economics, Faculty of Economics, Management and Tourism, Poland); Aboubakr Moteleb (B2E Consulting, UK); Dr. Mary Mu‐ henda (Uganda Management Institute, Uganda); Aroop Mukherjee (King Saud University, Saudi Arabia); Dr. Birasnav Mut‐ huraj (New York Institute of Technology, Bahrain); Arash Najmaei (MGSM, Australia); Dr. Elena Irina Neaga (School of Man‐ agement (Plymouth Business School) Plymouth University, UK); Dr. Gaby Neumann (Technical University of Applied Sciences Wildau, Germany); Dr. Emanuela Alia Nica (Center for Ethics and Health Policy (CEPS) and University "Petre Andrei" Iasi, Ro‐ mania); Dr. Cristina Niculescu (Research Institute for Artificial Intelligence of the Romanian Academy, Romania); Klaus North (FH Wiesbaden, Austria); Dr Nora OBERMAYER‐KOVACS (UNIVERSITY OF PANNONIA/FACULTY OF ECONOMICS, Hungary); Dr. Jamie O'Brien (St. Norbert College, USA); David O'Donnell (Intellectual Capital Research Institute of Ireland, Ireland); Gary Oliver (University of Sydney, Australia); Dr. Ivona Orzea (Academy of Economic Studies, Romania); Dr. Kaushik Pandya (Shef‐ field Business School, City Campus, UK); Dr. Paul Parboteeah (Loughborough University, UK); Dr. Dan Paulin (Chalmers Uni‐ versity of Technology, Sweden); Jan Pawlowski (University of Jyväskylä, Austria); Dr. Corina Pelau (Academy of Economic Studies, Bucharest, Romania); Monika Petraite (New York Institute of Technology, Lithuania); Rajiv Phougat (IBM, USA); Prof. Paulo Pinheiro (Universidade da Beira Interior, Portugal); Prof. Mário Pinto (Polytechnic Institute of Porto, Portugal); Prof. Selwyn Piramuthu (University of Florida, Gainesville, USA); Dr. Gerald Polesky (IBM. 11425 N. Bancroft Dr, Phoenix, USA); Dr. John Politis (Charles Darwin University, Australia); Dr. Nataša Pomazalová (FRDIS MENDELU in Brno, Czech Republic); Dr. Stavros Ponis (National Technical University Athens, Greece); Prof. Asta Pundzienė (Kaunas University of Technology , Lithua‐ nia); Dr. Devendra Punia (University of Petroleum & Energy Studies, India); Dr. Gillian Ragsdell (Loughborough University, UK); Dr. Lila Rajabion (Penn State University, Mont Alto , USA); Prof. Thurasamy Ramayah (Universiti Sains Malaysia, Malay‐ sia); Dr. M S Rawat (DCAC, University of Delhi, India); Prof. Dr. Ulrich Reimer (University of Applied Science St. Gallen, Switzer‐ land); Dr. Marcin Relich (University of Zielona Gora, Poland); Gerold Riempp (EBS,Germany, Germany); Eduardo Rodriguez (IQ Analytics, Ottawa, Canada); Dr. Inès Saad (Amiens School of Management , France); Dr. Josune Sáenz (University of Deusto, San Sebastián, Spain); Prof. Lili Saghafi (Canadian International College, Egypt); Mustafa Sagsan (Near East University, Nicosia, Northern Cyprus, CYPRUS); Prof. Svetlana Sajeva (Kaunas University of Technology, Lithuania, Lithuania); Dr. Kalsom Salleh xi
(Faculty of Accountancy, University Technology MARA, Malaysia); Dr. María‐Isabel Sanchez‐Segura (Carlos III University of Madrid, Spain); Dr. Antonio Sandu (Mihail Kogalniceanu University, Romania); Prof. Helena Santos‐rodrigues (IPVC, portugal); Prof. Dan Savescu (Transilvania University of Brasov, Romania); Dr. Ousanee Sawagvudcharee (Centre for the Creation of Co‐ herent Change and Knowedge, Liverpool John Moores University, Thailand); Dr. Golestan Hashemi Sayed Mahdi (Iranian Re‐ search Center for Creanovatology , TRIZ & Innovation Science, Iran); Enrico Scarso (Università Degli Studi Di Padova, Italy); Dr. Thomas Schalow (University of Marketing and Distribution Sciences, Japan); Dr. Christian‐Andreas Schumann (University of Zwickau, Germany); Prof. Jurgita Sekliuckiene (Kaunas University of Technology , Lithuania); Dr. Maria Th. Semmelrock‐Picej (Alpen‐Adria Universität Klagenfurt, Austria); Amani Shajera (University of Bahrain, Bahrain); Dr. Mehdi Shami Zanjani (Uni‐ versity of Tehran, Iran); Peter Sharp (Regent’s College, London , UK); Dr. Michael Shoukat (UMUC, USA); Dr. Evangelia Siachou (Hellenic American University , USA); Dr. Kerstin Siakas (Alexander Technological Educational Institute of Thessaloniki, Greece); Prof. Umesh Kumar Singh (Vikram University, Ujjain, India); Dave Snowden (Cognitive Edge, Singapore); Dr. Siva Sockalingam (Glasgow School for Business and Society, UK, UK); Prof. Dr. Marta‐Christina Suciu (Academy of Economic Stud‐ ies Bucharest, Romania); Christine Nya‐Ling Tan (Multimedia University, Melaka, Malaysia); Dr. Llewellyn Tang (University of Nottingham Ningbo , China); Ass.Prof.Dr. Gintare Tautkeviciene (Kaunas University of Technology , Lithuania); Dr. Sara Ted‐ mori (Princess Sumaya University for Technology, UK); Dr. Eduardo Tomé (Universidade Europeia, Lisbon. , Lisbon); Dr. Zuzana Tuckova (Tomas Bata University in Zlín, Czech Republic); Prof. Alexandru Tugui (Alexandru Ioan Cuza University, Ro‐ mania); Geoff Turner (University of Nicosia, Cyprus); Dr. Anna Ujwary‐Gil (Wyzsza Szkola Biznesu‐National‐Louis University, Poland); Andras Vajkai (University of Pécs, Hungary); Dr. Changiz Valmohammadi (Islamic Azad University‐South Tehran Branch, Iran); Dr. Christine van Winkelen (Henley Business School, University of Reading, UK); Dr Murale Venugopalan (Am‐ rita School of Business,Amrita Vishwa Vidyapeetham University, India); Prof. Jose Maria Viedma (Polytechnic University of Catalonia, Spain); John Walton (Sheffield Hallam University, UK); Maria Weir (Independent Consultant, Italy); Christine Welch (University of Portsmouth, UK); Florian Welter (IMA/ZLW & IfU ‐ RWTH Aachen University, Germany); Anthony Wensley (Uni‐ versity of Toronto, Toronto, Canada, Canada); Dr. Sieglinde Weyringer (University of Salzburg, Austria); Roy Williams (Univer‐ sity of Portsmouth, UK); Dr. Lugkana Worasinchai (Bangkok University, Thailand, Thailand); Prof. Les Worrall (University of Coventry, UK); Dr. Mohammad Hossein Yarmohammadian (Health Management and economic research Center, Isfahan Uni‐ versity of Medical Sciences, Iran); Prof. Qinglong Zhan (Tianjin University of Technology and Education, China); Dr. Malgorzata Zieba (Gdansk University of Technology, Poland);
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Biographies Conference Co‐Chairs Dr Carla Vivas is an Assistant Professor at the School of Management and Technology (Polytechnic Institute of Santarém) where she teaches Management, Operations Management, Logistics and Stra‐ tegic M anagement. She has a PhD in Management. Her main research interest areas include: Stra‐ tegic Management, innovation and internationalization strategies in SMEs. Pedro Sequeira is Director of the Research Unit of the Polytechnic Institute of Santarém; General Secre‐ tary of European Network of Sport Science, Education & Employ ment (ENSEE); Professor at Sport Sci‐ ences School of Rio Maior – Polytechnic Institute of Santarém.
Programme Co‐Chairs Dr Susana Leal is Assistant Professor at the Polytechnic Institute of Santarém, Portugal. She PhD from University of Coimbra, Portugal, and has articles published in Journal of Business The International Journal of Hum an Resource Management, and Creativity Research Journal. search deals with Organizational Behavior and Corporate Social Responsibility
has a Ethics, His re‐
Maria Barbas is a teacher in Polytechnic Institute of Santarém and invited teacher in Universidade Aberta. Coordinates teams in elearning; examiner jury for the defense of monographs; UIIPS member, effective researcher at the Center for Research and Teaching Technology in Training of Trainers (Univer‐ sity of Aveiro) and contributing member of the Center for Advanced Studies in Management and Eco‐ nomics (CEFAGE‐University of Évora); guest member of editorial writing in International Symposiums and Journals; scholarship Postdoctoral, winner of National and International Awards; executor of copyright registration; participant in the program Lifelong Learning; reviewer in journals and national and interna‐ tional conferences. Guidance of Master, doctoral and post‐doctoral theses.
Keynote Speakers Nuno Guimarães graduated in Electrotechnical Engineering at the Technical University of Lisbon (IST/UTL), Portugal (1983), where he also completed his MsC (1987) and PhD (1992) in Electrotechnical and Computer Engineering. Nuno Guimarães is currently (2014) Full Professor (Professor Catedrático) at ISCTE‐IUL ‐Instituto Universitário de Lisboa, Portugal. From June 2012 to March 2014, he was Pro‐ Rector for International Issues of ISCTE‐IUL and since March 2014 he has been Pro‐Rector for Interna‐ tionalisation and E‐Learning of ISCTE‐IUL. Nuno has extensive evaluation experience with a number of programmes, including EU Telematics Programme, Education & Training, PRATIC/INETI – National Pro‐ gramme AdI, EU ESPRIT Programme, FCT Programmes, Key Area Multimedia Tools and Applications (KA3), EU IST Pro‐ gramme, POSI‐2.2 National Programme, AdI Networks of Excellence and EU FP7 Expert). Rui Lança is a Consultant and Trainer in Coaching, Leadership and Team Coaching for companies from a number of different industries as well as for the University sector. He holds a Postgraduate Diploma in Leadership and People Management from INA and he has an Executive Master degree from the Un. Catholic and EGE in Audit Management as well as a Master in Sports Management and a degree in Sports Science, both from FMH – UTL. Rui was a Trainer and Facilitator at the European Council 2002‐ 2008 and is author of several books including 'How to form teams of high performance‘ and ‘Coach to Coach’, both in Portuguese. His areas of expertise include Organizational and Team Coaching, Leader‐ ship, Facilitation and Team Dynamics, Communication Impact and Interpersonal Relations. xiii
Mini Track Chairs Dr Juan Gabriel Cegarra‐Navarro is associate professor of the Business Administration Department of the Universidad Politécnica de Cartagena (Spain). He has been a visitin g professor at the University of Manchester and at the University of Hull in the UK. Dr Peter Heisig is founder and coordinator of the Global Knowledge Research Network including 30+ p artners worldwide. He has been working in KM since 1989 and his research interest is around the crea‐ tion and use of knowledge in organisations and society. After leading the Fraunhofer KM Competence Centre for a decade, he worked with Cambridge University and is currently a Senior Research Fellow at Leeds University Business School. Dr. Radwan A. Kharabsheh is a lecturer in international business and the assistant dean, international affairs at the Hashemite University in Jor dan. His research interests include organizational learning, knowledge management and international joint ventures. He is member of ANZIBA and ANZMAC and the Sydney University Centre for Peace Studies and Conflict Resolution. Aino Kianto, D.Sc. (Econ. & Bus. Adm.) is a Professor at the School of Business at Lappeenranta Univer‐ sity of Technology, and the Academic Director of Master’s Program in Knowledge Man agement. Her main research interests are in the areas of knowledge management, intellectual capital and innovation. Florinda Matos PhD Social Sciences, Organizational Behavior Studies, Technical University of Lisbon. Masters Degree in Business Sciences, ISCTE‐IUL Business School; Engineering Degree in Agricultural Engineering & Licentiate Degree in Management of Agricultural Business, Po lytechnic Institute of Santarém. Lectures and is a business consultant. Researches Knowledge Management, Intellectual Capital, Business Strategy, Marketing, Organizational Behavior, Innovation and Entrepreneurship. Pres‐ ident of ICAA ( Intellectual Capital Accreditation Association) www.icaa.pt Dr Sandra Moffett Senior Lecturer of Computer Science with University of Ulster’s School of Computing and Intelligent Systems, Magee Campus. Core member of Business and Management Research Institute. Expertise on Knowledge Management contributes to her being one of UK leading aut hors in this field. Received a number of research awards and citations for her work. External funding has enabled Dr Moffett to undertake extensive quantitative/qualitative research to benchmark KM implementation within UK companies.
Biographies of Presenting Authors Rute Abreu is an Accounting and Finance Professor at the Instituto Politécnico da Guarda, Portugal. She received her PhD Degree in Accounting and Finance from the Universidad de Salamanca, Spain (2009). She researches on social responsibility, accounting and finance. She publishes several papers and participates, all over the world, frequently in conferences and meetings. Rigel Adiratna, graduated from Faculty of Humanities, Bina Nusantara University, Jakarta, majored in Psychology. In 2014, she attended 2 months Overseas Studies Program (English literature) at Oxford. Working experience: Intern at Indonesian Child Protection Commission, Talent Development officer (intern) at United Tractors, and Therapist at Yayasan Baik, Indone‐ sia. Ghosia Ahmed is a PhD student in the School of Business and Economics at Loughborough University. Her research draws attention to the largely unexplored area of ‘knowledge security’ to explore whether a conflict exists between knowledge sharing and information security practices, and, the subsequent implications of this on knowledge sharing.
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Kamla Ali Al‐Busaidi is an Associate Professor of Information Systems at Sultan Qaboos University in Oman. She received her Ph.D. in Management Information Systems from Claremont Graduate University in California. Her research interests include knowledge management systems and learning management systems. She has published articles in several international con‐ ference proceedings, book chapters, and journals. Asma Al‐Harthy is a student at the college of economics and Political Science at Sultan Qaboos University in Oman. She ma‐ jored in finance with a minor in information systems. Her research interests include the utilization of information technolo‐ gies to improve decision making in the finance field. Ghitha Al‐Kalbani is a student at the college of Economics and Political Sciences at Sultan Qaboos University in Oman. She majored in information systems. Her research interests include knowledge management, social learning and social intelli‐ gence. Xiaomi An, is a professor of records and knowledge management at School of Information Resources Management, Renmin University of China (RUC). She is leader of Knowledge Management Team at Key Laboratory of Data Engineering and Knowl‐ edge Engineering, Ministry of Education at RUC. She has chaired 30 projects, published 16 books and 195 academic papers. Roberta Antonelli is PhD student at University of Cassino and Southern Lazio. Ivett María Aportela Rodríguez Bachelor’s Degree in Library and Information Science and Master’s Degree in Communication from the Universidad de la Habana (Cuba). Now she is Assistant Professor and Doctoral candidate in the Library and Informa‐ tion Science Department at Universidad Carlos III de Madrid (Spain). She worked as an information specialist and manager at an Information Consultancy in Cuba. Nekane Aramburu is PhD in Economics and Business Administration and Director of the Strategy and Information Systems department in Deusto Business School (University of Deusto, Spain), where she is also the Academic Director of the Advanced Health Management Programme. Her research is focused on the fields of: Strategic Management, Knowledge Management, Organizational Learning, and Innovation. Pierre‐Emmanuel Arduin is a postdoctoral researcher funded by the Laboratory of Excellence Control of Technological Sys‐ tems of Systems (Labex MS2T), he is also lecturer at Paris‐Dauphine University, KM and IT consultant within several large companies. He studied Psychology, Computer Science and Management, and now focuses on Knowledge Management, link‐ ing knowledge with individual interpretation processes. Zenona Atkočiūnienė Academic degree ‐ Prof. Dr. (HP) (Communication and Information Science) Employment ‐ Commu‐ nication faculty of Vilnius University. Position ‐ Head of the Information and communication Institute Research interests – Knowledge management ; Creative industries ; Creativity and Innovation; Knowledge management practices from a cross‐ cultural perspective; Science communication. Urszula Bakowska‐Morawska, born: 26.09.1976; place: Kalisz Town, Poland; scientific discipline: management science; workplace: Wroclaw University of Economics;position: Associate Professor since 2006; number of publications: 40, in this book: 1; research in the field: strategic management in tourism sector, aspect cooperation in tourism, supply chain in tourism problems, non-work interests: travel, healthy life. Shahnaz Bashir is a Doctoral researcher in the School of Computing, University of the West of Scotland, UK. She obtain M.Ed in Teaching and Learned Higher education and Curriculum Development from AIOU Islamabad, B.Ed from university of Pe‐ shawar, MA Urdu from University of Peshawar, Diploma in Computer from Khan Academy and Certificate in teaching (CT) from AIOU Islamabad. Her research interests include Societal Culture, Knowledge Management, Knowledge Sharing and Vir‐ tual Communities. Her contributes to computing school conferences, seminars and publishes in school journals. Fabio Ferreira Batista, PhD is a Senior Researcher at Institute of Applied Economic Research (Ipea) and professor of Knowledge Management at Catholic University in Brasilia, Brazil. He is the author of the book Knowledge Management Framework for Brazilian Public Administration (2012) and has conducted research about KM in the public sector in Brazil since 2003. Denise Bedford is currently the Goodyear Professor of Knowledge Management at Kent State University and is adjunct fac‐ ulty at Georgetown University’s Communication Culture and Technology program. She teaches a range of course s in knowl‐ edge management and enterprise architecture. Her current research interests include communities of practice, use of se‐ mantic analysis methods and technologies, knowledge economy, knowledge cities, intellectual capital and communities of practice.
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Iskhar belkacem, has a General Education Diplomain electric engineering. Engineer in computer sciences, option: advanced information systems. Master’s degree in computer sciences, option: knowledge and information systems. PhD student at high school on computer sciences, Algiers, Algeria. Computer teacher at preparatory school on economic and commercial sciences and management sciences, Constantine, Algeria. “Learning processus design from enterprise’s business”, STIC 2011 conference Tébessa, Algeria. “The Capitalization of Enterprises' Business in an E‐learning Context,” ICELW 2011, New York. Nicole Bittel holds a master of arts from the University of Zurich in pedagogy with a thesis on storytelling. Currently she is a research associate at FFHS, where she is project leader in e‐Collaboration, focusing on applying storytelling to learning and knowledge management. Madeleine Block, PhD is a lecturer at the Faculty of Sociology at the Saint‐Petersburg State University in Russia. Her main field of interest is knowledge management; her current research is related to the issues of understanding, evaluating and optimising knowledge sharing within organisations. Pavel Bogolyubov is a Management and Business Development Fellow at Lancaster University Management School, UK. He gained his first degree in Physics at Herzen University in St. Petersburg, Russia, and an MBA from Bradford School of Man‐ agement, UK. Prior to returning to academia, he spent ten years working in various Continuous Improvement roles in FMCG multinationals across Europe. His research interests are centred around “softer” aspects of Web 2.0 and its role in KM. Ettore Bolisani is Associate Professor at the University of Padua. He was Research Associate at Manchester University, visit‐ ing scholar at Coventry University, visiting lecturer at Kaunas Technological University. He authored papers on communities of practice, knowledge protection, KIBS, knowledge measurement. He was Chair of ECKM 2009. He is first president of the International Association for Knowledge Management, and co‐editor (with Meliha Handzic) of the Book Series on “Knowl‐ edge Management and Organisational Learning” (Springer). Matteo Bonifacio is Assistant Professor in Organizational Sciences and Research and Innovation Policy at the University of Trento. He was a member of the group of Policy Advisers to the President of the European Commission (BEPA) on research, higher education and innovation where he co‐authored the EC report on Social Innovation Elisabeth Brito Doctorate in Psychology (area of expertise in Organizational Psychology). Professor at the Águeda Higher School of Technology and Management, University of Aveiro, also coordinating the degree of Quality Management. Knowledge management, quality management services and client satisfaction are her main research interests. Author of var‐ ious book chapters and scientific papers. Sheryl Buckley is an Associate Professor in the School of Computing at the University of South Africa. Her interests are In‐ formation Science, e‐learning, business intelligence and communities of practice. She is committee member of a number of international and local organizations and an active peer reviewer. I have presented and published papers locally and interna‐ tionally. Barry Byrne is a serving officer in the Irish Defence Forces. He is also an adjunct assistant professor in the Computer Science Department of Trinity College Dublin. Barry is leading an enterprise‐wide project developing policies, procedures and tech‐ nological solutions to improve Knowledge Management. Barry presented at ECKM 2013 and is delighted to be back this year. Maria Do Rosario Cabrita holds a PhD and is Assistant Professor and researcher at the Universidade Nova de Lisboa, Portu‐ gal, and teaches at the Portuguese Banking Management School in Lisbon. She has several years of experience in executive positions in international banks. Her current field of research is focused on intellectual capital, knowledge management and measuring intangibles. Jaime Campos is an Associate Professor at the department of Informatics, Linnaeus University, Sweden. His main research interest includes the application of Knowledge Management Systems, Information and Communication Technologies espe‐ cially Web technologies as the Semantic web and Web 2.0, Agent and Mobile technologies for the Industrial domain. Andrea Cappilli, graduated in 2012 from University of Salento (Italy) in Management Engineering. Since 2013 he is involved in a 2‐year industrial training program aimed to develop Entrepreneurial Innovators capable to design and orchestrate tech‐ nology entrepreneurship ecosystems within territories and companies. The program is led by the Apulian Technological Dis‐ trict DHITECH, in collaboration with universities and Industrial partners. Antonio José Carrasco‐Hernandez is a Professor of management at the University of Murcia (Spain). His current research focuses on the relationships among innovation, human resource management and family firms. He has recently published in Family Business Review, Management Research and The Electronic Journal of Knowledge Management.
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Cristina Castro is a PhD Student at University of Coimbra. Master in Work, Organizational and Personnel Psychology at Uni‐ versity of Coimbra and at University of Barcelona, granted with a WOP‐P Master Scholarship for 2007‐2009. Learning & Qual‐ ity Manager in a worldwide Financial Company, responsible for knowledge management, training and performance en‐ hancement in Service Areas. Knowledge management is her main research interest. Behiye Tüzel Çavuşoğlu In 2004 Çavuşoğlu started her professional career at Near East University Department of Economics as a lecturer. Since 2013 she has been continuing her career also with vice chairman.She has many published articles and conference proceedings.Çavuşoğlu also acting as a member of board at Knowledge Management Research Center. Hui Chen is a PhD candidate at School of Business and Economics, Loughborough University. She holds an MSc in Information Management from University of Sheffield and a BSc from Renmin University of China. Her main research interests are: Identi‐ fication and Classification of Shareable Tacit Knowledge Associated to Experience, Knowledge Sharing, Knowledge Manage‐ ment and Records Management. Koteshwar Chirumalla is postdoc researcher at the Division of Design and Visualisation at Mälardalen University, Sweden. He received his Ph.D. in the area of Product Innovation, with a focus on lessons learned practice. His research is focused on the development of new knowledge management methods and tools to support the early stages of product innovation projects. Dr Agnieszka Chlon‐Dominczak is an Assistant Professor at Warsaw School of Economics and Educational Research Institute. Previously a Deputy Minister in the Ministry of Labour and Social Policy. Co‐author of the pension reform in Poland intro‐ duced in 1999. Consultant of World Bank, ILO and the OECD. Researcher and author of publications in demography, pen‐ sions, labour markets and education. Rozina Chohan is a PhD student based at Lancashire Business School, UCLan, Preston, United Kingdom. She is also based at Department of Computer Science Shah Abdul Latif University, Khairpur, Pakistan. Her background is BSc. in Computer Sci‐ ence, MSc. in IT Service Management. Rozina Chohan is a corresponding author and can be contacted at: RCho‐
[email protected] Stephanie Conn graduated from the University of Ulster with a Bachelor of Science in Creative Computing and is currently undertaking a MSc in Professional Practice whilst in employment by the University of Ulster under a Knowledge Transfer Partnership project. The knowledge‐base company is Mervyn Stewart Ltd, Belfast, the two year project is focused on Knowl‐ edge Management in the Motor Retail Industry. Ricardo V. Costa is a lecturer at Maia University Institute – ISMAI, where he coordinates the Business Management Course (first cycle), and a researcher at UNICES. He graduated in Economics at Universidade do Porto, and received is Phd in Business Management from Universidade de Vigo, in Spain. He got an Executive MBA in Business Strategy from Escuela de Negocios Caixanova, in Vigo, and attended the “Program in International Management” at Georgetown University in Washington. His main research interests are intellectual capital, product innovation and corporate finance. Vitor Costa I hold a master degree in work and organizational psychology from University of Beira Interior, Covilhã, Portugal. Presently, I’m a work and organizational psychology Ph. D. candidate at University of Beira Interior. My research interests are knowledge management, absorptive capacity, strategic human resources management and innovation. Carla Curado is a tenured Assistant Professor of Organizational Behavior and Human Resources Management at ISEG, Eco‐ nomics and Business School at Universidade de Lisboa. She received her PhD in management from the Technical University of Lisbon. She currently teaches postgraduate, master and doctoral programs related to strategy and organizational behavior Brit‐Eli Danielsen. Training manager of N‐USOC (Norwegian User Support and Operations Centre), NTNU Social Research, CIRiS. Rune Kristiansen Valle. Master student in psychology, NTNU Boštjan Delak, Ph.D, CISA, CIS, is a senior consultant at ITAD, Technology Park, Ljubljana, Slovenia. From 2008 he conducted more than 60 IS audits and from 1998 he delivered more than 70 IS due diligences in 15 countries across Central and Eastern Europe. His research interest is IS due diligence. Souad Demigha is a Doctor in Computer Science from the University of Paris1 Sorbonne (Paris). She is a researcher at CRI (Centre de Recherche en Informatique) at the Sorbonne University and Lecturer at the University of Paris XI (Orsay). Her Re‐ search field deals with : information systems, medical imaging, elearning systems, artificial intelligence (case‐based reason‐ ing), knowledge‐ based systems, knowledge management and data warehousing systems. She is the author or co‐author of 21 international scientific papers.
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Sally Eaves is a committed ‘practitioner‐researcher’, spanning IT Service Management positions within the Communications Sector alongside academic roles, primarily with Sheffield Hallam University. Affording a particular interest in methodological innovation, knowledge management and entrepreneurial innovation, she is a reviewer for titles such as JMMR and active in professional bodies, notably The British Academy of Management. Anandasivakumar Ekambaram (Siva) works as a research scientist at SINTEF – Technology and Society, Industrial Manage‐ ment Department, Trondheim, Norway. He obtained his doctoral degree, which focuses on project management and knowledge transfer in organizations, from the Norwegian University of Science and Technology (NTNU). Besides his research work, he is involved in teaching activities at NTNU. Martina Ergan is a part‐time student in Master in Business Administration at Buskerud and Vestfold University College, Nor‐ way. She is also a fulltime employee and a student adviser at Hedmark University College, Norway. Her master thesis is about participation in Virtual Communities of Practice established in Norwegian organizations. Leif Estensen works as a senior advisor at SINTEF – Technology and Society, Industrial Management Department, Trondheim, Norway. He has a master's degree in Mechanical Engineering from Norwegian University of Science and Technology (NTNU). He has more than 20 years of experience as a researcher and a competence broker in regional development initiatives in Norway. Nina Evans is Associate Head of the School of IT and Mathematical Science (ITMS) at the University of South Australia. She holds tertiary qualifications in Chemical Engineering, Education and Computer Science, a Masters in IT, an MBA and a PhD. She teaches Knowledge Management and ICT Leadership on Masters’ and Doctorate level. Her research interests focuses on Knowledge Management, Business‐IT fusion, ICT Education and Information Asset Management. She has published in nu‐ merous international journals and conferences. Doron Faran (PhD) is a lecturer in ORT Braude College in Karmiel, Israel. His areas of interest include organizational learning, epistemology and methodology. Besides his academic duties he leads the College's strategic thinking and advises the presi‐ dent. Vitor Hugo Ferreira has received his PhD from Lisbon University (ISEG) in Innovation. He is associate professor at Polytechnic Institute of Leiria and a Business Consultant. He is author of scientific published works, chair at GBATA and reviewer in differ‐ ent journals. He is executive director at the D.Dinis Business School and was coordinator of the MSc in Management Control. Elisa Figueiredo is Professor at the Department of Management and Economics of the School of Technology and Manage‐ ment at Guarda Polytechnic Institute, Guarda, Portugal, PhD in Organizational Psychology. Consultant and trainer in human resource management and organizational behavior. Her research interests are focused on knowledge management and hu‐ man resource management. Charles Gagné is a Knowledge Transfer Advisor at IRSST’s Knowledge Transfer and Partner Relations Department. The KTPR mandate consists of ensuring the use of research results and their diffusion to partners and stakeholders involved in the pre‐ vention of occupational accidents. Ernesto Galvis‐Lista is an Associate Professor in Engineering Faculty at the Universidad del Magdalena in Santa Marta – Co‐ lombia since 2007. Also he is a PhD student at Universidad Nacional de Colombia in Bogotá. Galvis completed his undergrad‐ uate and master studies at Universidad Industrial de Santander. His research interests lie in the area of Software Engineering Processes and Knowledge Management. Johan Garcia is an Associate Professor of Computer Science at Karlstad University in Sweden. His research interest span com‐ puter aided reasoning support, computer networking and computer forensics, and he has published extensively within these topics. Dr Garcia has participated in several European Union and National projects as a project coordinator, work‐package co‐ leader and project participant. Sahar Ghrab is a PhD student in the MIS (Modelling, Information & System) laboratory (Amiens‐France) and in the MIRACL (Multimedia, InfoRmation Systems and Advanced Computing Laboratory) laboratory (Sfax Tunisia). Apostolos Giannakopoulos (Paul) is an Academic Support Coordinator at Unisa, South Africa, managing the tutoring system. He graduated in 2012 with a PhD in Mathematics Education. He taught for 10 years in Colleges and 22 years at the Universi‐ ties Mathematics and computers. Problem solving in general and graduation rates are his specialization. Raquel Gimenez is a PhD student in the Department of Management of Tecnun, Engineering School (University of Navarra) in San Sebastian, Spain. She obtained her Industrial Management Engineering Graduate class (2013) from Tecnun. She has par‐ xviii
ticipated in the ELITE European research project. Her research fields are emergency management, communities of practice and wiki technology. Ingrida Griniene is a PhD student and a lecturer of Information and Communication at the Faculty of Communication of Vil‐ nius University, Vilnius, Lithuania. Her research interests and publications are in information management, organizational learning, human resource management, knowledge management and innovation. Scientific experience: participation in the international and national projects. Maria Luminita Gogan received the M.Sc. in Accountancy and IT Management (2009), the B.Sc. in Accounting Management, Expertise and Audit (2011) and currently she is PhD student, also at the University "Politehnica" of Timisoara ‐ Romania. Her PhD thesis is concern with researches in the field of intellectual capital in order to identify key elements for increasing com‐ petitiveness. Some of her research results have been published in proceedings of international scientific conferences. Meliha Handzic is Professor of Management and Information Systems at the International Burch University, Sarajevo and Suleyman Sah University, Istanbul. Her PhD is from the University of New South Wales, Sydney. Meliha’s main research inter‐ ests lie in the areas of knowledge management and decision support. She has published extensively on these topics in leading journals. Dr. Harold Harlow’s research interests include developing measures of intellectual capital and tacit knowledge. Doctoral de‐ gree (DBA) in strategic management from Alliant International University (San Diego, California); MBA in Finance from Xavier University (Cincinnati, OH); undergraduate degree in mechanical engineering technology (BT.) from University of Dayton. Industry experience includes executive positions as vice president, director, CEO and senior manager at IBM and Novatel, QUALCOMM, Air Weigh and Rockwell Collins Aviation respectively. Dr Peter Heisig is founder and coordinator of the Global Knowledge Research Network including 30+ partners worldwide. He has been working in KM since 1989 and his research interest is around the creation and use of knowledge in organisations and society. After leading the Fraunhofer KM Competence Centre for a decade, he worked with Cambridge University and is currently a Senior Research Fellow at Leeds University Business School. Ilona Heldal is a Professor in Informatics (focus: Interactive Systems) and a Program Director for the Indistrial PhD Program in Applied Informatics, ApplyIT. Her main research interest is collaboration and interaction in virtual environments and how visualizations support collaboration. She also is interested in initiating collaboration and cooperation projects. Inge Hermanrud (PhD) is an Associate Professor at Hedmark University College, Norway. Inge teaches courses in human re‐ source management. His published work appears in journals like Informing Science, Journal of Cases in Information Technol‐ ogy and Nordic Journal of Social research. His research focuses on knowledge sharing across dispersed employees in public organizations. Eli Hustad is an Associate Professor at the University of Agder in Kristiansand, Norway. She holds a Ph.D. from the University of Oslo. Her research and teaching focus on enterprise‐wide information systems, knowledge networking, KM 2.0 and utiliza‐ tion of social media in businesses. Henri Inkinen, M.Sc. (Econ. & Bus. Adm.) is a Doctoral Student at the Technology Business Research Center (TBRC) at Lap‐ peenranta University of Technology. His research interests are in the areas of intellectual capital and knowledge manage‐ ment practices. He has been involved with these issues through his work experience within knowledge‐intensive industries. Mahsa Jahantab is a PhD student doing Knowledge Management research at the Faculty of Engineering and Computing of Coventry University, UK. She has completed an MSc in Engineering Project Management at Coventry University in 2010 and a BSc in Electrical Engineering at American University in Dubai in 2008. Dr Daniel Jiménez Jiménez Associate profession, Management and Finance Department, University of Murcia,Spain. Resear‐ ches innovation,knowledge management, absorptive capacity, human resources and organizational learning. Published in many journals and participated in various research projects related to organizational cultura, innovation and information technologies. Vice Deam of School of Labour and Employment Relations at the University of Murcia. Palmira Juceviciene – Ph. D., Habil. Dr., full professor at Kaunas University of Technology. Research interests – individual and organizational learning, knowledge creation and management, learning organizations and regions, human resource devel‐ opment, higher education. Dr. Juceviciene has published more than 200 scholarly articles and 10 books. Consultant in indi‐ vidual and organizational learning, learning organizations and regions, human resource development.
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Rita Juceviciene holds a PhD degree in Management and is Senior Lecturer at Kaunas University of Technology (Lithuania). Her research interests cover various aspects of inter‐organizational trust that she had been researching during her PhD stud‐ ies and research stays at the University of Geneva, University of Lausanne (Switzerland) and University of Cambridge (UK). Giedrius Jucevicius is a Professor at the Strategic Management Department, School of Economics and Business, Kaunas Uni‐ versity of Technology (Lithuania). He holds a PhD in Management, has been visiting scholar at HEC University of Lausanne (Switzerland), Lund university (Sweden), etc. His academic interests include comparative international management, business model innovation, inter‐organizational relations and trust, clusters and industrial systems. Robertas Jucevicius is a Professor and Director of the Business Strategy Institute at Kaunas University of Technology, Lithua‐ nia. He holds a PhD in Economics and Habilitated Doctor in Management. He is also a visiting fellow at the University of Cam‐ bridge (UK), as well as Fulbright (USA) and Wallenberg (Sweden) fellow and the member of the Council for National Progress of Lithuania. Nowshade Kabir is the CEO of Knolee Group, a Canadian investment and consulting company focused on technology invest‐ ment. He has M. Sc. in Computer Science, MBA and Ph. D. in Information Technology. His present interests are Big Data, In‐ novation, Knowledge Management, Semantic Technologies, Entrepreneurship and Strategic Management. He is presently pursuing a DBA in the joint program of Grenoble Graduate School of Business and Newcastle University Business School. Katerina Kashi I am currently studying second year of PhD study, department of Business Economics and Management. I spe‐ cialize on human resources issues, especially employees’ training and development and employees’ total reward linked to competency models. My working experiences include: office assistant and office manager in USA, where I lived for nearly a decade. Marcela Katuščáková Lecturer at the University of Žilina. Masters and PhD. graduate of the Comenius University in Brati‐ slava. She is working in research and education, specializing in information and knowledge management, scientific collabora‐ tion, storytelling and text mining. She has worked in the field of knowledge management implementation in research pro‐ jects such as the Memory of Slovakia and KNIHA SK. Yasmina Khadir‐Poggi is a Doctoral student in the School of Business Studies at Trinity College Dublin. Besides, she is a Senior Lecturer in International Business at American College Dublin. Her research interests include knowledge intensity in organisa‐ tion, knowledge workers management and the subsequent knowledge‐based development. Tomasz Kijek holds PhD in Economics and conducts teaching and research activities in the Department of Economics and Management at the University of Life Sciences in Lublin, Poland. His research interests focus on innovation, innovation capi‐ tal, intellectual capital, knowledge and a firm’s competitiveness. He is the author and co‐author of several scientific publica‐ tions, including chapters of monographs and articles. Florian Kragulj is a research and teaching assistant in the fields of knowledge‐based management and information systems at the Vienna University of Economics and Business, Vienna, Austria. He graduated in Business Administration as well as in Cognitive Science and had recently a research stay at the Eötvös Loránd University Budapest. Jaroslava Kubátová, Ph.D. Associate Professor at Palacky University Olomouc, Czech Republic. Head of the Department of Applied Economics Areas of Expertise: Human Capital Management and Knowledge Management with ICTs utilization http://www.linkedin.com/in/jaroslavakubatova, https://www.researchgate.net/profile/Jaroslava_Kubatova2 Carmem Leal has a Master (2004) and Phd (2011) degrees in Management by UTAD. She is Assistant Professor of Financial Accounting at University of Trás‐os‐Montes e Alto Douro. Her research on Management Control (Intellectual Capital) has been presented at numerous international conferences. At the moment she investigates Intellectual Capital within enterpris‐ es’ performance and Financial Management. Monique Lortie Ph.D., is a tenure professor at Université du Québec à Montréal. She graduated in Industrial Engineering from École Polytechnique de Montréal and completed her graduated studies in Ergonomics in France. Her main field of re‐ search is the occupational health and safety from which various issues on knowledge transfer and management are explored. Grzegorz Majewski MSc degree awarded by Warsaw School of Economics and another by University of the West of Scot‐ land. Worked for companies in telecommunication and finance industries. PhD in Computing awarded by University of the West of Scotland. Active in research field presenting his papers at international conferences and publishing in refereed jour‐ nals. His current research focuses on Knowledge Management, Business Process Simulation, Innovation Management, Social Networks, e‐Learning and Immersive Virtual Worlds.
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Carla Susana Marques has a PhD in Management. She is Assistant Professor in the University of Trás‐os‐Montes e Alto Douro (UTAD) and Coordinator of the ‘Innovation, Markets and Organization’ research group in UTAD’s Centre for Transdisciplinary Development Studies. Her research on innovation and entrepreneurship has been presented at numerous international con‐ ferences and published in international journals. Dra. Eva Martínez‐Caro is Associate Professor of Business Management at the School of Industrial Engineering, Universidad Politécnica de Cartagena. Her research areas of interest include knowledge management, technology‐based learning envi‐ ronments and technology management. Dora Martins did her PhD thesis on expatriates’ management on Portuguese companies and continues researching this topic. She has also attended several international conferences. She teaches in the degree and master course of Human Resources Management at Superior School of Industrial and Management Studies, Polytechnic of Porto, Portugal. Dr. Fuensanta Medina‐Dominguez is assistant professor at Carlos III University of Madrid. Her research interests include SE and software process improvement. Contact her at
[email protected]. Andreia Meireles, MSc, is a Doctoral researcher at Faculty of Psychology and Sciences of Education – University of Coimbra. Knowledge management is her main research interest. At the present, she is ending a research project that approaches inter‐ organizational knowledge sharing networks. Undergraduate and post‐graduate teaching experience in human resource man‐ agement, knowledge management, and work and organizational psychology. Patricia Mercado Salgado Investigadora de la Facultad de Contaduría y Administración de la Universidad Autónoma del Estado de México. Licenciatura y Maestría en Administración. Doctorado en Administración (Organizaciones) obtenido en la Universidad Nacional Autónoma de México. Miembro del Sistema Nacional de Investigadores (Conacyt). Coordinadora del Doctorado en Ciencias Económico‐Administrativas). Miembro del Cuerpo Académico Gestión del Capital Intelectual. Peter Mkhize completed his PhD in 2012. He is currently working for University of South Africa as a senior lecturer. He has published few journal and conference papers on e‐Learning and knowledge management. Among other research interests is human capital development, social networks, communities of practice. Ludmila Mládková works as an associate professor at the University of Economics Prague, Faculty of Business Administra‐ tion, Department of Management. She specializes in knowledge management, management of knowledge workers and man‐ agerial leadership. Her activities involve lecturing, writing and work with Ph.D. students. Lisete M. Mónico is Professor at the University of Coimbra, Ph.D. in Social Psychology, European Diploma of Advanced Stud‐ ies in Social Psychology. Member of the Institute of Cognitive Psychology, dedicates her professional activity to research in Social Psychology and Quantitative Data Analysis. Author of one book and several book chapters and peer reviewed articles. Samuel Monteiro Assistant Professor, University of Beira Interior – Portugal. PhD in Organizational Psychology (2011) ‐ Uni‐ versity of Coimbra. MSc in Organizational Psychology (2007) ‐ University of Porto. BSc degree in Psychology (2003) – (Work and Organizational Psychology) ‐ University of Coimbra. Researcher of the business and organizational management line of research at NECE – UBI ‐ Research Unit in Business Sciences. Mieczysław Morawski, born: 10.05.1962; place: Jelenia Góra Town, Poland; scientific discipline: management science; workplace: Wroclaw University of Economics;position: professor since 2008; number of publications: 130, in this book: 11; research in the field: personal aspect of knowledge management, national management style, human capital management non‐work interests: travel the world, forecasts the development of civilization. Mustafa Doruk Mutlu. Mustafa completed his undergraduate study in Gazi University, Turkey and master study in Warwick Business School, United Kingdom. He continues his PhD in Sheffield University. His current research focuses on knowledge worker team personality composition working in R&D context. Martin Nkosi Ndlela, is an associate professor at Hedmark University College in Norway. His research interests within knowledge management include knowledge sharing and communication, communities of practice and the role of infor‐ mation and communication technologies. Ndlela has a keen interest in knowledge sharing in the public sector focusing main‐ ly on emergency organizations. Irina Neaga is a Lecturer in Logistics dealing with supply chains and logistics systems, and researching of knowledge man‐ agement for collaborative logistics, decisions and operations. She worked for industry, research consortia, and higher educa‐ tion in Romania, United Kingdom, Finland, Canada, and The Netherlands. She contributed to European and Academia‐ industry collaborative research projects. xxi
Satoshi Nishimura is a third year PhD student at Department of Engineering in Osaka University. He received Master of Engi‐ neering at Osaka University on 2012. His research interest is knowledge representation of human action based on ontology engineering. Felipe Nodari is a doctoral student at Pontifical Catholic University of Rio Grande do Sul (PUCRS), School of Business, Brazil. His current research interests include Knowledge Management, Knowledge Sharing, Information Management and Manage‐ ment Information Technology. Ana Nunes is Bachelor of Economics by Faculdade of Economia of Porto and Master in Finance by INDEG/ISCTE – IUL. She worked as Risk Analyst at Ricoh Portugal, as Brand and Communication at BNP Paribas Corporate & Investment Banking and at Planning & Control Analyst at EDP Soluções Comerciais. Since April 2013 she is Financial Controller at EDP Soluções Comerciais. Dr. Nóra Obermayer‐Kovács is an Assistant Professor at the Department of Management, University of Pannonia. She ob‐ tained her Ph.D. (Conscious knowledge management in knowledge economy) in Economics and Management in 2008. She has published numerous articles and presented at national and international conferences. Her main fields of interest include knowledge management, knowledge sharing, organizational culture. Okeke Okeoma John‐Paul Currently a doctoral researcher at the University of East London with interests in knowledge man‐ agement. Current research is focused on evaluating knowledge management within the Nigerian Oil Petroleum Corporation focusing on the knowledge processes within the firm and how they are integrated in its operational and business processes. Mírian Oliveira obtained her doctoral degree in Business Administration from the Federal University of Rio Grande do Sul (UFRGS) in 1999. She is a professor and researcher at Pontifical Catholic University of Rio Grande do Sul (PUCRS), School of Business, Brazil. Her current research interests include Knowledge Management, Knowledge Sharing, Information Manage‐ ment and Research Method. Tereza Otčenášková, is Ph.D. candidate at the Faculty of Informatics and Management (University of Hradec Králové, Czech Republic), where she received Master Degree in Information Management. She received BA Diploma at the University of Hull, United Kingdom. She leads tutorials and cooperates within various projects. Her areas of interest include knowledge man‐ agement and decision‐support systems. Leonor Pais Professor at the University of Coimbra and Porto Business School of University of Porto. Pre‐graduate and post‐ graduate teaching activity in work and organizational psychology area. Portuguese Coordinator of the European WOP‐P Master supported by the European Commission. Knowledge management, human resources management and decent work are her main research interests. Author of various book chapters and scientific papers. Patcharaporn Paokanta has been a lecturer in the areas of Data Management, E‐Commerce, System Analysis and Design, and Information Technology at Chiang Mai University (CMU), Thailand. She is studying for a Ph.D. in Knowledge Management at CMU. She was awarded an ERASMUS MUNDUS scholarship (E‐Link Project) at the University of Sannio in Italy. She has pub‐ lished articles in international journal and conference proceedings, including ICIC Express Letter, IJCTE, IJIIP, ISABEL 2010 and BHI 2012. Margarida C. Piteira is assistant professor of human resources. Her research activity has been driven in the area of organiza‐ tional innovation and human resources management, with particular interest in the method of cases. At present she is mem‐ ber of the executive board Research Centre in Economic and Organizational Sociology Dr. Mohammad Habibur Rahman is Associate Professor at Mohammed Bin Rashid School of Government, Dubai. He received his PhD from the University of Wales and held visiting positions at Syracuse University in USA and York University in Canada. He published papers on governance, local government, and knowledge sharing. Vítor Raposo PhD in Business Management and Organization. Assistant professor at the Faculty of Economics, University of Coimbra. Researcher and vice‐director of the Center for Studies and Health Research of the University of Coimbra and col‐ laborator of the Portuguese Observatory of Health Systems. Main research interests related with health governance, knowl‐ edge management and information management in health. Elizabeth Real de Oliveira is Dean of Faculty of Business and Economics of Lusiada University. She holds a PhD in Manage‐ ment by the University of South Wales (former University of Glamorgan). Her research interests include corporate social re‐ sponsibility, HRM, employee engagement and employer branding. She has a wide experience as professor and consultant.
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Paavo Ritala, D.Sc. (Econ. & Bus. Adm.) is a Professor at the School of Business at Lappeenranta University of Technology, and an Academic Director of Master’s Programme in Strategy, Innovation and Sustainability. His main research interests are in the areas of inter‐organizational networks, business models, knowledge management and innovation. Hanno Roberts is a full professor in Management Accounting & Control at BI Norwegian School of Business. His research in‐ terests are in intellectual capital, local information systems, and management accounting and control for the knowledge in‐ tensive firm. He is on the Editorial Boards of multiple journals and teaches executive and MBA courses around the world. Paula Cristina Lopes Rodrigues graduated in Economics. Masters degree on Cultural Marketing, finishing PhD on Measure‐ ment of Brand Equity in Fashion Companies, both in Economics University of Porto. Teaches Marketing, Statistc and Econo‐ metrics at Universidade Lusíada Famalicão and Porto. Published papers/books on marketing/statistics Direction of Faculty of Economics and Business (2010), Lusíada University of Porto. Held conferences and published l articles in Marketing. José L. Roldán, PhD. Associate Professor of Management, Universidad de Sevilla (Spain). Current research interests include technology acceptance models, knowledge management, and partial least squares (PLS). Published in Journal of Business Research, British Journal of Management, International Business Review, European Journal of Information Systems, and In‐ dustrial Marketing Management, among others. He is currently on the editorial board of The Data Base for Advances in In‐ formation Systems. Svetlana Sajeva is currently Associated Professor at School of Economics and Business, Kaunas University of Technology, Kaunas, Lithuania. Her area of research interests covers knowledge management, knowledge‐intensive organization’s man‐ agement and development of human resources. Svetlana Sajeva can be contacted at:
[email protected]. João Samartinho Adjunct Professor of School of Management and Technology, Polytechnic . Institute of Santarém. Invited Professor of School of Education. Head of Department of Computer Science and Quantitative Methods. Researcher UIIPS Investigation Unit of Polytechnic Institute of Santarém. Chairman of the Cientific Board of School of Management and Tech‐ nology, November 2003 to April 2010 Noelia Sanchez‐Casado is a PhD Student at the Universidad Politécnica de Cartagena. Her research interests are in the area of knowledge management, social media and marketing. Maria‐Isabel Sanchez‐Segura has a PhD in Computer Science from Madrid Technical University. She is a faculty member of the Carlos III University of Madrid. Her research interests include software engineering with a focus on processes and intelli‐ gent organizations. She is a member of the IEEE Computer Society. Contact her at
[email protected] Thomas Schalow is a professor in the Department of Economics and Information Science at the University of Marketing and Distribution Sciences in Kobe, Japan, where he has taught for the past 15 years. He has also previously lectured at the Na‐ tional University of Singapore. His Ph.D. is from Princeton University. Camilo Augusto Sequeira . has a Master’s degree in Electronic Engineering from Catholic University, Rio de Janeiro, and has taught in both undergraduate and graduate programs. He has an MBA from Salford University, England. Sequeira has been top executive for multinational companies and international lecturer. He is currently a consultant and a researcher for the Institute of Energy of PUC‐Rio. Gulzada Serzhan, Lecturer at International Academy of Business, Almaty, Kazakhstan, IT Faculty Member Radim Šíp, Ph.D. (1975) is a teacher and researcher at Faculty of Education, Masaryk University, Brno, Czech Republic. He awarded Ph.D. in philosophy. He is the author of the first monograph on Richard Rorty on pragmatism in the Czech milieu. He is dealing with pragmatism, neuroscience, cognitive science, and philosophy and history of science. Inga Stankevice guest lecturer at the Department of Management and junior research assistant at the Department of Strate‐ gic Management, Kaunas University of Technology (Lithuania). Research stays at Bergen University (Norway), University of Geneva (Switzerland), Nottingham University Business School (UK). Holds 10 scientific awards, has nearly 30 publications, participated in 7 research projects. Erik Steinhöfel studied Industrial Engineering focusing on Innovation Management at University of Applied Sciences Berlin and University of Technology, Sydney. Became senior researcher at Fraunhofer IPK, Division Corporate Management. Expert in strategic and operational knowledge management, project manager for Intellectual Capital Statements. Comprehensive experience in innovation management and strategic planning. Trine Marie Stene Research Manager), NTNU Social Research, CIRiS (Centre for Interdisciplinary Research in Space). Senior research scientist at SINTEF. PhD in Education and Master in Psychology xxiii
Dr Ann Svensson holds a PhD in informatics and is an assistant professor at University West, Sweden. Her research interests are e‐learning and collaboration within e‐learning as well as knowledge management with a particular focus on complex and professional work within and across organizations. Erika Tauraitė‐Kavai 2nd year doctoral student, Doctoral studies in Social Sciences, Management and Administration, ISM University, Vilnius Lithuania.Erika has 14 years of international professional experience in market research, public policy ana‐ lytics and innovation management. In 2012 she started her PhD studies. Her research focuses on knowledge management practices in open innovation context. Giovanna Testa holds a PhD in Business Administration and Governance and is a researcher in economics and business man‐ agement at the University of Naples “Parthenope”. Her research focuses mainly on mechanisms of knowledge transfer and sharing. The most recent studies are focused on industrial districts, from their operation to their characteristic features, par‐ ticularly oil districts. Tkachenko Elena (1969) – the Doctor of Economics, the professor of the Department of the Enterprise Economics and Indus‐ trial Management ( St. Petersburg State University Of Economics). Author more than 120 scientific and methodical works, including 10 textbooks and 7 monographs. The sphere of scientific interests –innovations, investments, management of the intellectual capital, Industrial development Eduardo Tome PhD in Economics (2001), with a Thesis on the European Social Fund presented at the Technical University in Lisbon. Since then he published 24 papers in peer‐reviewed Journals and presented 48 papers in international conferences. He has also authored three book chapters. From September 2013 he is working at Universidade Europeia in Lisboa. Thierno Tounkara PhD in computer science at University Dauphine of Paris (2002) . Works at Business School “Telecom Ecole de Management” (TEM) as professor in Information Systems Department. Delivers courses in information system design, project management, Enterprise Resource Planning (ERP) and KM. Written scientific articles on KM and Engineering. Worked at ONERA, First Aerospace Research Player in France, as KM engineer, 3 years. In 2000, joined French Knowledge Manage‐ ment Club, association rallying a lot of French companies. Katarzyna Trawińska‐Konador graduated with a major in German and Dutch from the University of Warsaw. She studied at the University of Leuven in Belgium, the Freie Universität in Berlin and the University of Vienna. Ms. Trawińska‐Konador ac‐ quired extensive hands‐on professional experience in education working as director for studies at private continuing educa‐ tion institutions. Her main fields of professional interest include vocational education and training, continuing, non‐formal and informal education, and distance education. Dr. Anna Ujwary‐Gil PhD from Warsaw School of Economics, College of Management and Finance. Fellow of Foundation Scholarship and Training (Norwegian Funds). Currently Editor‐in‐Chief of Journal of Entrepreneurship, Management and In‐ novation. In 2010, book entitled "Intellectual Capital and Market Value of a Company" (Ch&Beck, Warsaw 2009) received a prestigious award granted by Polish Academy of Sciences. Jiro Usugami is a professor at Aoyama Gakuin University，Tokyo. His research topics include Knowledge Management in disaster risk reduction and Cross Cultural Management. Lina Užien Associate Professor, Department of Strategic Management, School of Economics and Business, Kaunas University of Technology. PhD in Management and Business Administration (2005) from Kaunas University of Technology. Scientific in‐ terests lie in intellectual capital measurement and management at corporate and regional levels. Professional activities in‐ clude university lecturing, corporate consulting and project work. José Vale lives in Porto, Portugal, and he is an invited lecturer at Aveiro University and at the Porto polytechnic in the areas of management, strategy and accounting. Presently is doing a PhD in Accounting and Management Control at the faculty of economics in Porto University, studying Intellectual Capital in a seaport context. Ana Cláudia Valente Researcher at DINÂMIA’CET‐IUL. Fields of research are human capital and innovation mainly skills and work organization studies and education and employment policies analysis. Is currently a national expert in the CEDEFOP network for skills forecasting and labour market developments. Ph.D. in Economics, specialization in Industrial Economics and Innovation, by ISCTE ‐ Lisbon University Institute. Mika Vanhala, D.Sc. (Econ & Bus. Adm.) is a post‐doctoral researcher in Knowledge Management at School of Business, Lap‐ peenranta University of Technology, Finland. His primary research interest is the relationship between HRM practices, organ‐ izational trust and organizational performance. Mika’s research has been published in Management Decision, Personnel Re‐ view and Management Research Review. xxiv
Stanislav Vojir graduated from applied informatics (Knowledge technologies, Information systems and technologies). Cur‐ rently, he is internal PhD student at Faculty of Informatics and Statistics, University of Economics in Prague. He deals with problem of business rules in conjunction with datamining of association rules. Tone Vold Assistant Professor is lecturing at Hedmark University College since 2000. Since her Master in Informatics in 2005, Vold’s areas of interests now include social sciences and she currently teaches within the areas of Organizational Studies and Knowledge Management. Volker Wagner is a teaching assistant at the chair for human resource management at the University of Hamburg. He is cur‐ rently working on his PhD in the fields of social cognition and shared cognitive structures in organisations. He studied Eco‐ nomics and Business Administration at the University of Hohenheim with majors in HRM and Organizational Psychology. Igor Zatsman has the PhD (Information‐Computer Science). Currently, he is the head of research department at the Institute of Informatics Problems of the Russian Academy of Sciences. He has the highest research diploma, obtained after the PhD. Research interests are in the fields of Cognitive Informatics, Modeling Emerging Meanings Processes and Their Tracing by Computer. Malgorzata Zieba PhD, Eng. is an assistant professor at the Faculty of Management & Economics of Gdansk University of Technology, Poland. She has taken part in several national and international projects. Her scientific interests oscillate around knowledge management and modern concepts of management in SMEs. She has a record of around 30 publications.
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Learned Helplessness of Prisoners: Psychology and Knowledge Management Perspective Juneman Abraham and Rigel Adiratna Bina Nusantara University, Jakarta, Indonesia
[email protected] [email protected] Abstract: The author posits that knowledge creation and management nowadays do not occur in prisons in Indonesia since the existence of learned helplessness phenomena among its prisoners. This study contributes by identifying predictor variables of prisoner’s learned helplessness. The design of this research is quantitative‐predictive correlational design. This research hypothesized that social rejection and three types of neurotic personality orientations (moving away from people, moving against people, and moving toward people) are able to predict learned helplessness of prisoners. As it is known in the literature of Knowledge Management, learned helplessness lessens one’s effort to understand complex issues. In addition, prospective approach to knowledge management suggests that learned helplessness should be transformed into learned optimism. The participants of this research were 163 inmates from Cipinang IA Penitentiary Institution and Pondok Bambu IIA Prison in DKI Jakarta, the capital of Indonesia. The measurement tools of this study were adapted and developed from Rejection Sensitivity Questionnaire, Karen Horney’s Three Orientations, and Learned Helplessness Scales. Multiple linear regression analyses showed that social rejection and the tendency of “moving toward” are not able to predict learned helplessness. The tendency of “moving away” and of “moving against” are able to predict learned helplessness in the negative ways. All results of this research will be discussed by employing relevant psychological theories and knowledge management perspective. The implication of result of this research toward efforts in facilitating learning as well as knowledge creation and management of prisoners in prison is proposed in the Discussion section of this article. The authors are of the position that if all these things are well facilitated, the prisoners will be a valuable social capital for Indonesia. Keywords: learned helplessness, knowledge management, psychology
1. Introduction Prisons in Indonesia are always fascinating to study, mostly because prisons are miniature representatives of social issues in Indonesia (Larasati n.d). In prisons, we find oppression of minorities, corruption, drugs and orgy, institutional reformation, conflict transformation, deradicalization of convicted terrorist, and others. Therefore, the author assumes that (1) solving the issues in Indonesian prisons will contribute enormously to settlement of social problems in Indonesia, (2) social and psychological capital—including knowledge—findings in Indonesian prisons are crucial for the settlement of social issues in Indonesia. It is a fact that crimes and modus operandi of criminals move faster and more sophisticated compared to law enforcement by its officers (Fajar Online 2011; Purnomo 2013). Based on this issue, the author argues that knowledge of inmates must be appreciated, meaning that their knowledge must be viewed as significant in the context of crime prevention and eradication. Unfortunately, convicts are usually positioned as a social entity that must firstly be intervened, treated, educated, transformed (as object), and not, before all else, to be understood and respected for their knowledge (as subject, both as an individual or a group). Prisoners have their own logic (Sarwono 2013) which may be different from the logic of non‐prisoners. Utilization of prisoner’s knowledge is not taboo. Sarwono (2012 p. 58) described his activities in studying terrorists: “We are successful in engaging the ikhwan (Islamic terminology for brother) in discussion regarding their believe and action, although at the beginning of the discussion they refuse ... (Discussion) is effective strategically and tactically (for example, with regard to killing people that do not attack Islam, killing women and children, or with regard to their decision on whether Java and Bali can be regarded as jihad area).” If we look back to the history of Indonesia, knowledge creation and exchange in prisons are a typical experience of the founding fathers of Indonesia—Soekarno, Hatta, and Syahrir—during the colonial era. Prisons bring about creative, productive, transformative experience, which facilitate those individuals to a deeper understanding of the “truth” that they have fought for (Laksana 2013). In prison, they read books and perform knowledge exchange through meaningful social relation.
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Juneman Abraham and Rigel Adiratna Maruna (2011) emphasized two basic issues regarding how psychology should relate to prisoners. He states that psychologists need to see transformation opportunities of personality, cognitive ability, and other issues with regard to prisoners. The strength of prisoners must also be given proper attention in addition to their weaknesses. If prisoners are viewed as a deviance or pathology, psychologists must be careful not to fall on the trap of individualization or attribute the cause of the deviance or pathology solely on the personality of the individual. Psychologists should consider that deviance has social loci, namely social contexts, power dynamics, and interpersonal situations. Those thoughts indicate that knowledge exchange can also be conditioned in social interactions. However, inmates are often only seen as objects. Prisoners are often considered as the enemy by society, as part of the out‐group‐low‐status opponents; hence they are treated offensively, or—in a more passive way— they get humiliation or exclusion (Fiske, Harris and Cuddy 2004). Even when they are out of the prison, ex‐ prisoners face many issues when reintegrated into society, such us unemployment, homelessness, and legal obstacles to accessing public services, which lead to recidivism (Wheeler and Patterson 2008). Wheeler and Patterson propose that in reducing recidivism, it is vital to perform coordinated community services for prisoners that have already been stigmatized by society. However, this service should be a continuum since prisoners are in prison. According to the author, the main purpose, among others, is to decrease learned helplessness experienced by prisoners even since they are in prison. Knowledge creation and management nowadays do not occur in prison in Indonesia since the existence of learned helplessness phenomenon among its prisoners. Learned helplessness reduces one’s effort to understand complex issues (Schwartz and Te’eni 2010). Learned helplessness is described as one’s personal belief that he/she is not able to do anything to increase his/her performance, and as the consequence, he/she does not desire to achieve any reward or to avoid punishment (Lieder, Goodman and Huys 2013; Reivich, Gilham, Chaplin and Seligman 2005). Schill and Marcus (1998) explain that learned helplessness is influenced by attribution style. The psychological process is as following: imprisonment creates one’s sense of losing personal control of him/herself and his/her actions. If individuals want to exert more control, for example by questioning orders and debating with prison officers, they will lose more of their rights and limited facilities. In such chronic situation, inmates will be conditioned to belief that the negative events that happened are caused by internal, stable, and global reasons. In other words, inmates adopt and developed helpless attribution style or pessimistic explanatory style. Lieder et al (2013) also show that learned helplessness can be generalized—because it is assumed as a learning process—or creates depression in other new situation. The knowledge management perspective suggests that learned helplessness should be transformed into learned optimism (Thatchenkery and Chowdhry 2007). The author assumes that differences in personality and social factors obtained throughout life (since childhood) influenced the degree of their learned helplessness for every (ex‐) prisoner. The author chooses Karen Horney’s Three Orientations (moving against people, moving away from people, and moving toward people) as well as social rejection as the predictors (Figure 1). Karen Horney’s Three Orientations variable is chosen because its psychoanalysis concept speaks about defence that people create to deal with their basic anxiety (Coolidge, Segal, Benight and Danielian, 2004; Walborn 2014) —a sense of hopelessness that is primitive in a hostile world. This “hostile world” is actually a projection of the child’s inner world. This inner world is the result of experience in facing the environment and parenting that is severely and chronically maladaptive. The child wanted to fight the parents, but he/she is also dependent on them; hence his/her sense of resistance is repressed. In psychoanalysis, this results in a reaction formation where the child becomes excessively affectionate towards the parents, but, on the other hand, sees the world as hostile. Furthermore, growing up, this individual developed an “idealized (not real) self” rooted in a neurotic necessity for affection and admiration—by performing what is assumed as expected by the parents—but never felt satisfied or contented. Walborn (2014) in his analysis added that the same anxiety does not result only from experience of interacting with the parents, but also through interacting with capitalistic world which solely appreciate people based on their material possession and physical appearance, not by who they are. In the struggle to achieve the idealized self, people use three defensive strategies, namely (1) moving towards people (compliant trend), (2) moving against people (aggressive trend), and (3) moving away from people (detached trend). Horney argues that neurotic adults experience fixation on one of those three orientations, however, healthy adults have the flexibility to move between those three.
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Juneman Abraham and Rigel Adiratna
Karen Horney’s Three Orientations
Learned Helplessness of Prisoners
Social Rejection
Figure 1: The hypothetical model Social rejection in this study is measured based on subjective sensitivity. The construct being measured is social rejection sensitivity. Rejection sensitivity is a disposition to defensively (anxiously or angrily) expect, readily perceive (even when events are ambiguous), and overreact (e.g., aggressing against or withdrawing from others) to rejection (Wang, McDonald, Rubin and Laursen 2012; Wang and Nesdale 2012). Sensitivity to rejection and continuous overreaction is a part of the natural learning process. High level of sensitivity is a result of initial rejection and prolonged experiences of caregivers and significant others (Kross et al 2007). Watson and Nesdale (2012) found that rejection sensitivity correlate negatively with (1) confidence in building and maintaining meaningful social relation, and (2) perceived efficacy in controlling social situation. In addition, they also speculate that individuals with high rejection sensitivity will assume that their failure in social relation is due mostly by the immutable negative characteristics of their personalities. This further strengthens the feeling of the individuals regarding their social incapability and fruitlessness. However, Watson and Nesdale states that the speculation requires further investigation. The author observed that the latter symptom is compatible with helpless attribution style described previously above, which is experienced by prisoners or ex‐prisoners. This study will first test the predictive hypotheses as described above, and will further provide discussion regarding the implication of the empirical findings on knowledge sharing in prisons.
2. Methods This study used the design of quantitative, predictive correlational research, with data analysis technique in the form of multiple linear regression analyses. The predictor variables are Karen Horney’s Three Orientations and social rejection sensitivity, and the criterion variable is learned helplessness. Participants of this study were inmates of Cipinang IA Correctional Facility and Pondok Bambu Class IIA Prison, in Jakarta, Indonesia, both new inmates (inmates serving their first prison sentence) and recidivist inmates (inmates with two or more prison sentence). The number of participants is 163 consisting of 64 men, 99 women (Mean of age = 33.14 years old; Standard deviation of age = 8.48 years old). Participants were taken using convenience sampling technique, and they were asked to fill the questionnaire in Indonesian. The instrument for measuring learned helplessness is adapted and developed from Learned Helplessness Scale (LHS) constructed by Quinless and Nelson (1988). This instrument initially has 20 items categorized into five dimensions. The first dimension is Internality‐Externality, with sample scale items: (1) When I do not succeed at a task, I find myself blaming my own stupidity for my failure, (2) If I complete a task successfully; it is probably because I became lucky. The second dimension is Globality‐Specific, with sample scale items: (1) I am unsuccessful at most tasks I try, (2) I do not have the ability to solve most of life's problems. The third dimension is Stability‐Instability, with sample scale items: (1) When I do not succeed at a task, I do not attempt any similar tasks because I feel that I will fail them also, (2) I do not try a new task if I have failed similar tasks in the past. The fourth dimension is Ability‐Inability to Control, with item: (1) No matter how much energy I put into a task, I feel I have no control over the outcome, (2) I feel that I have little control over the outcomes of my work. The fifth dimension is Individual's Choice of Situation, with items: (1) I do not accept a task that I do not think I will succeed in, (2) I do not place myself in situations in which I cannot. LHS has response options from Strongly Disagree (score of 1) to Strongly Agree (score of 6). The higher the total score of the participants in this scale shows a higher learned helplessness. The results of reliability and validity test on 90 participants (for instrument tryout) indicate that LHS is reliable with an internal consistency index (Cronbach’s Alpha) of 0.833 with corrected item‐total correlations ranged from 0.377 to 0.701 after dismissing 10 items.
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Juneman Abraham and Rigel Adiratna The instrument for measuring Karen Horney’s Three Orientations is adapted and developed from Karen Horney’s Social Movement assessment instrument constructed by Wheeler (1991). This instrument consists of 108 items categorized into three dimensions. The first dimension is Aggression (moving against people), with sample scale items: (1) When people talk about me and say things I do not like, I have a tendency to become angry and say things back about them, (2) If I see someone I dislike approaching me from a distance, I have a tendency to meet him or her ready to argue or show my dislike. The second dimension is Avoidance‐ Passiveness (moving away from people), with sample scale items: (1) When a discussion turns into an argument, I have a tendency to withdraw from the conversation, and (2) When my roommate repeatedly eats food of mine that I had been saving especially for myself, I have a tendency to avoid the person and the situation. The third dimension is Compliance (moving toward people), with sample scale items: (1) When someone embarrasses me by spilling something on me, I have a tendency to tell them it is OK and accept and apology, (2) When people tell me things about me that I do not want to hear, I have a tendency to listen to what they are saying and see how I can change what they do not like about me. This scale has response options from Never (score of 1) to Always (score of 6). The higher the total score of the participants in each of the three sub‐scales (aggression, avoidance‐passiveness, compliance) shows an increasing level of neurotic trend by the participants on the related scale. The reliability and validity test results show that this instrument is reliable with an internal consistency index for aggression, avoidance, and compliance, respectively of 0.912, 0.917, and 0.908. The corrected item‐total correlations ranged from 0.250 to 0.732 for aggression (after dismissing 2 items), 0.320 to 0.616 for avoidance (after dismissing 2 items), and 0.254 to 0.682 for compliance (after dismissing 7 items). The instrument for measuring social rejection is adapted and developed from Rejection Sensitivity Questionnaire (RSQ) constructed by Downey and Feldman (1996). There are 18 situations to which that participants must respond. The sample of situations are as follow: (1) You approach a close friend to talk after doing or saying something that seriously upset him/her, (2) You call your boyfriend/girlfriend after a bitter argument and tell him/her you want to see him/her, (3) You ask a friend if you can borrow something of his/hers, (4) You ask a friend to do you a big favor, (5) You ask your spouse if he/she truly loves you. The RSQ instruction is as following: "Each of the items describes things one sometimes asks of other people. Please imagine that you are in each situation. You will be asked to answer the following questions: (a) How concerned or anxious would you be about how the other person would respond? (b) How do you think the other person would be likely to respond?" The response options for (a) are from Very Unconcerned (score of 1) to Very Concerned (score of 6). The response options for (b) are from Very Unlikely (score of 1) to Very Likely (score of 6). Scoring on participants’ responses follows the Downey and Feldman’s manual (1996). The reliability and validity test results indicate that LHS is reliable with an internal consistency index of 0.834 with a corrected item‐total correlations ranged from 0.259 to 0.654 without any item being dismissed.
3. Result and discussion Multiple linear regression analysis indicates coefficients of determination (R2) value and beta coefficients (β) as shown in Table 1. Table 1: Coefficients of determination and beta coefficients in the predictive model with Learned Helplessness as the criterion variable (n = 163) Model 1
Predictors Social Rejection Sensitivity & Orientation of Moving Away from People
F F(2, 162) = 6.652; p = 0.002**
2
Social Rejection Sensitivity & Orientation of Moving Against People
F(2, 162) = 6.344; p = 0.002**
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Social Rejection Sensitivity & Orientation of Moving Toward People
F(2, 162) = 0.560; p = 0.572
Note: * p 0.05) is allegedly due to the nature of the consequences of having attributes of SRS by individuals, namely negative and positive; thus the correlated scores might diminish each other. On one hand, SRS has negative consequences as proved in the previous studies. This is because SRS is associated with actual rejection (self‐fulfilling prophecy phenomenon), depression, loneliness, social withdrawal, jealous in partnerships, low self‐efficacy, relationship dissatisfaction and breakdown, and doubt or unwillingness to take social risks (Addis 2012; Wang et al, 2012; Watson and Nesdale 2012; Zimmer‐Gembeck and Nesdale 2012). Individuals’ social cognitions, feelings, and interpersonal behaviors such as these indeed lead to helplessness. However, there are evidence that positive consequences of social rejection. Kim, Vincent, and Goncalo (2012) states that experience of social rejection can stimulate creativity. Creativity is a psychological resource which is precisely the opposite of learned helplessness. However, creativity in this context only emerged on individuals with independent self‐concept. The psychological mechanism is as following: Social rejection interacts with independent self‐concept and this interaction strengthens individuals’ desire to further differentiate themselves from others through moderating variables need for uniqueness. This cognition will in turn lead to more creative effects. Subsequent researchers are advised to measure independent vs. interdependent self‐concept in order to obtain a complete picture regarding the relationship between SRS and Learned Helplessness. Negative correlation between Orientation of Moving against People with Learned Helplessness (β = ‐0.260; p [10 Dec, 2011]. Cong, X.; Pandya, K. V. (2003) Issues of knowledge management in the public sector. Electronic Journal of Knowledge Management. V. 1, No 2, (pp. 25‐33). Dalkir, K. (2013). Knowledge management in theory and practice, The MIT Press, Cambridge, MA Denning, S.. (2011) The Leader´s Guide to Storytelling. Mastering the Art and Discipline of Business Narrative. Jossey‐Bass, San Francisco. Gespública (2007). Instrumento para a Avaliação da Gestão Pública. Ciclo 2007. Ministério do Planejamento, Orçamento e Gestão, [Online], Available: www.prefeitura.sp.gov.br/arquivos/secretarias/subprefeituras/pqgp/materiais_consulta/0001/Instrumento_Avaliaca o_GESPUBLICA.pdf [4 May 2014]. Eiriz, V.; Simões, J. e Gonçalves, M.(2007). Obstáculos à gestão do conhecimento nas escolas de gestão e economia do ensino superior público em Portugal. Comportamento Organizacional e Gestão, vol.13, n.2 pp. 153‐167. [Online], Available:
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Effect of ICT on Information Sharing in Enterprises: The Case of Ministry of Development Özlem Gökkurt Bayram1 and Hakan Demirtel2 1 Department of Information and Records Management, Faculty of Languages History and Geography, Ankara University, Ankara, Turkey 2 Department of Information Society, Ministry of Development, Ankara, Turkey
[email protected] [email protected] Abstract: Information sharing at enterprise level is getting more important because of growing value and volume of knowledge exponentially. Information and communication technologies (ICT) are adding value to knowledge management efforts and trying to make these efforts more efficient. It is another fact that the growing use of ICT has changed significantly the knowledge creation and knowledge usage processes. Besides, it has become a necessity to use ICT tools to access and analyse the information because of huge amount of knowledge stored electronically. In this paper the effect of information systems developed and used by government is investigated by means of information sharing at enterprise level. For this purpose, the systems owned by Ministry of Development (MoD) of Republic of Turkey such as electronic records management system, document management system, intranet web site, official web site and MoD‐Search system are come up for review and effects of them on information sharing are examined. Knowledge sharing motivation factors defined in the literature such as sense of achievement, sense of responsibility, recognition of job done, operational autonomy, promotional opportunities, challenge of work (Herzberg 1968, Herzberg 1987, De Sitter 1994, Hendriks 1999) are set for examination criteria. So that, a questionnaire are applied to knowledge workers at the MoD to measure these factors and results are analysed. Keywords: knowledge sharing, information and communication technologies (ICT), knowledge sharing motivations
1. Introduction Today, information and communication technologies (ICT) have diffused into almost every area of life leading to progress in many fields. Now, organizations can carry out numerous tasks and transactions using ICT. Conversion of transactions to electronic environment increases data creation rapidly. Besides, as advanced web‐based and other communication technologies have enabled interaction with customers using such systems, all sorts of feedback received from users are recorded on these systems. As a result of this rapid data flow, the amount of data created enhances and conventional methods remain insufficient to process recorded data. Organizations that process data with the help of ICT facilities facilitate creation of personal knowledge on the one hand, and head towards values supporting creation of new knowledge on the other. Organizational culture is important in knowledge creation. Organizational public knowledge must be utilized in processes of knowledge creation besides private knowledge created within the organization. Otherwise, it is stated that organizational competitive power can be affected adversely (Matusik & Hill 1998, Matusik 2002). Organizations need credible systems where knowledge is recorded according to defined rules and rapid access is provided to such knowledge. Therefore, it is important to record all private and public knowledge used in organizational processes and to share this knowledge to increase recognition. In this respect, use of ICT must play a facilitative role. ICT tools develop embedded search functions facilitating access to content in electronic databases on Internet and organizational webpages and also improve technics in full‐text search, keyword and descriptors. However, it is of utmost importance to evaluate, on an organizational basis, to what extent users have internalized the use of technics and technologies.
2. Rationale and problem (literature review) In the literature, creation of organizational knowledge is addressed on the basis of SECI approach developed by Nanoka (1994). SECI model includes basic dynamics regarding knowledge creation. In this model, two forms of knowledge, namely tacit and explicit knowledge, regenerates constantly by shifting from tacit knowledge to explicit and then to tacit knowledge again within a cycle consisting of processes of socialization, externalization, combination and internalization in creation process (Nanoka 1994). Waterfall Model (Sun 2004), Hierarchical Spiral Model (Sun ve Hao 2006), Integrated Life‐cycle Model (Cruywagen et al. 2005) can be considered among other models of knowledge management. It is seen that
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Özlem Gökkurt Bayram and Hakan Demirtel sharing of all sorts of knowledge, tacit or explicit, is important in models of knowledge management. In these processes, ICT can contribute significantly to prompt creation of knowledge, facilitate sharing and flow of knowledge. Secure access to knowledge and sharing of accurate knowledge creates considerable competitive advantage in organizational activities. Knowledge is shared through organisational learning in systems of knowledge where ICT facilities are used efficiently on organizational level. However, it has been stated that the group that most use knowledge in an organization is the one that create and share knowledge most actively at the same time (Hopfgartner et al. 2008). Besides, developing organizational culture in this direction is inevitable for creating awareness on and dissemination activity in sharing of knowledge. Motivational factors must be utilized properly among staff of organization in order to activate dissemination of information. It has been stated that motivation of knowledge sharing depends on factors of reputation, reciprocity, autonomy, community, and alturism (Hopfgartner et al. 2008, Hung, Lai & Chang 2011). In addition, some theories such as social exchange, social capital, social cognition, expectancy theories and the theories of reasoned action and planned behaviour explain attitudes of staff, who work knowledge‐intensive in an organization (Tsai & Cheng 2012). Studies on the role of ICT in knowledge sharing at organizational level enlist primary technologies of SECI model as blogs, e‐mail systems, e‐collaborative systems, e‐forums, e‐learning/online learning, information TM repository, instant messaging, NetMeeting , audio conferencing, people finder, podcast, video conferencing, and wiki. In these studies, the weight of these tools in steps defined by SECI model is also investigated (Lee & Kelkar 2013). More efficient and precise access is targeted through use of tags, ranking and recommendations tools in sharing of the content forms stated above (Chennamaneni, Teng & Raja 2011). In this study conducted by Chennamaneni and colleagues, elements influencing behaviours of knowledge sharing are examined and the impact of knowledge systems on behaviour is assessed in the context of technological priorities. It is stated that ICT usage contributes to knowledge sharing through abolition of barriers among employees, easier access to knowledge, process improvement (McGrath and Hollingshead 1994) and sharing of meta‐knowledge (Hendriks 1999). Hendriks, taking this approach as starting point, reviewed the impact of ICT upon knowledge sharing on the basis of SECI model by utilizing motivational factors generally accepted in the literature. Nevertheless, this study focused on the impact of ICT on general motivation for knowledge sharing rather than direct knowledge sharing peculiar to ICT systems. The study focused specifically on knowledge system used by an organization and assessed the influence of genuine ICT systems used by that organization for access to and sharing of knowledge upon access and sharing. In this context, this study has been conducted taking into consideration the benefits, as a case study, of a research on the impact of ICT‐based systems used by organizations upon knowledge sharing.
3. Methodology The research primarily specifies the ICT systems of the Ministry of Development (MoD) towards knowledge access and sharing and gives preliminary information about such systems. Then a questionnaire is designed with a view to identify the usage of these systems in terms of knowledge management. The target of the questionnaire is to assess the contribution of ICT systems to knowledge access and sharing. Conventional methods of knowledge sharing have been included in answer choices of questionnaire to set out rates of usage of ICT systems. Additionally, the motivational factors in usage of the above‐mentioned ICT systems and other methods in knowledge sharing have been investigated. For this purpose, the criteria that are defined in literature as motivations for usage, sense of success, sense of responsibility, recognition of job done, operational autonomy, promotional opportunities and challenge of work (Herzberg 1968, Herzberg 1987, De Sitter 1994, Hendriks 1999), are incorporated into research to identify which of these criteria are prominent in knowledge sharing via ICT systems.
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Özlem Gökkurt Bayram and Hakan Demirtel The questionnaire was sent to 777 employees of the Ministry of Justice as online application. The data of questionnaire answers given online were evaluated using Excel programme. Totally 253 persons participated in the questionnaire and replied all questions.
4. Analysis for the ministry of development There are several methods, either ICT‐based or conventional, in access to or sharing of organizational knowledge. Within this framework, not only ICT systems, but also conventional methods were included in the questionnaire to analyse the present situation in the Ministry and to understand the contribution of ICT.
4.1 ICT systems towards knowledge access and knowledge sharing Within the framework of the study, all knowledge systems were scrutinized and ICT systems facilitating direct knowledge access and knowledge sharing were included in the scope of analysis. KB‐eb Electronic Records Management System (MoD‐ERMS): This system is used by whole Ministry. All formal correspondence within the Ministry has been carried out over this system where all managers and employees use e‐signature. MoD Intranet Site (MoD‐IntraNet) : It contains all organizational announcement and prepared forms, shortcuts for access to other ICT systems, discussion forms and collaboration tools. Archives and Document Management System (ADMS): The electronic system that stores and provides access, within defined authorization framework, to working papers created by the ministerial staff as well as other source documents used for knowledge creation. MoD official web site: The website that includes all official knowledge and outputs as well as news and announcements about the Ministry. MoD‐Search Knowledge System (MoD‐Search): There is metadata set for resource discovery within the Ministry. All systems of knowledge sharing have been adapted to this set, and this searching system allows for resource discovery from a single point. Official e‐mail system: It is the institutional e‐mail system with @kalkinma.gov.tr extension. All employees have an official e‐mail account. This system has functions of meeting organization and calendar management.
4.2 Conventional methods for knowledge access and knowledge sharing The conventional methods directly related to the subject are classified in four main groups, intra‐ organizational dialogue and collaboration, intra‐organizational meetings/trainings, communication within project groups and printed organizational records/documents/publications. Besides, documents in personal computers, despite their ICT basis, are considered as conventional methods because of their private characteristics.
4.3 Information about participation in questionnaire The questionnaire was sent to 777 employees with different titles and answered completely by 253 employees. The number and share of employees, who replied the questionnaire (respondents), according to their titles are given below (See Table 1). Accordingly, the highest rate of participation is reached at 54% by those having the title of “assistant expert.” Total participation rate is 33% which is considered as a sufficient proportion. Table 1: Number and ratio of employees receiving and/or replying the questionnaire according to title Title
Total Replied Ratio
Director General and upper positions
14
6
43%
Head of department
51
17
33%
Expert
286
92
32%
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Özlem Gökkurt Bayram and Hakan Demirtel Title
Total Replied Ratio
Assistant Expert
139
75
54%
Director
11
2
18%
Administrative personnel
145
35
24%
Technical personnel
41
10
24%
IT personnel
90
16
18%
Total
777
253
33%
Most respondents stated that they used ICT applications mentioned in the study every day (83%). The rate of respondents who use ICT applications more than once a week including those using every day attains 96% totally (See Table 2). Table 2: Usage frequency of ICT systems by participants Usage of ICT systems
Number of users Ratio
Every day
210
83%
More than once a week
34
13%
Once a week
5
2%
Once a mount
2
1%
Never
2
1%
Total
253
100%
All the ratios for everyday usage of ICT systems are high enough for all groups except technical personnel group. The lower ratio in comparison to the others for this group might be the subject for further analysis (See Figure 1).
Figure 1: Everyday usage ratio by titles
4.4 Evaluations about the questionnaire 4.4.1 Access to knowledge The primary three tools of knowledge access most preferred by the staff of the Ministry of Development are MoD‐Net intranet site (226), official e‐mail system (216), and MoD‐ERMS system (215) consecutively (See Table 3). As seen in the levels of usage, the Ministry staff prefers for ICT applications for knowledge access rather than conventional methods. The usage frequency of MoD‐Net intranet site at 89 % is noteworthy. The choice of intra‐organizational dialogue and collaboration, which is the most commonly used conventional method for knowledge access (174) could only rank 5th. In this field, the first four methods consist of ICT applications. Table 3: ICT systems and conventional methods to access knowledge ICT systems/conventional methods MoD‐ERMS MoD‐Net
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Number of usage Ratio 215
85%
226
89%
Özlem Gökkurt Bayram and Hakan Demirtel ICT systems/conventional methods ADMS
Number of usage Ratio 100
40%
MoD official web site
185
73%
MoD‐Search
36
14%
Official e‐mail system
216
85%
Intra‐organizational dialogue and collaboration
174
69%
Intra‐organizational meetings/trainings
156
62%
Communication within project groups
62
25%
Printed organizational records, documents, publications
130
51%
Documents in personal computers
163
64%
MoD‐Net intranet site is the most preferred system to access knowledge. It is seen that it has quite equal usage ratios for all user groups. It can be defined as a successful information system and satisfies all the needs of user groups successfully (See Figure 2).
Figure 2: Use of MoD‐NET to access knowledge by titles 4.4.2 Knowledge sharing For the staff of the Ministry of Development, the three most preferred tools of knowledge sharing have been identified as official e‐mail system (238), MoD‐ERMS system (176) and intra‐organizational dialogue and collaboration (166) consecutively (See Table 4). In terms of rates of usage, the Ministry staff gives preference to ICT applications for knowledge sharing. It is remarkable that the rate of e‐mail usage peaks at 94% regarding knowledge sharing. Table 4: ICT systems and conventional methods to share knowledge ICT systems/conventional methods
Number of usage Ratio
MoD‐ERMS
176
70%
MoD‐Net
106
42%
ADMS
77
30%
MoD official web site
61
24%
Official e‐mail system
238
94%
Intra‐organizational dialogue and collaboration
166
66%
Intra‐organizational meetings/trainings
141
56%
Communication within project groups
63
25%
Printed organizational records, documents, publications
76
30%
Documents in personal computers
88
35%
Official e‐mail system is the most preferred system for knowledge sharing. The system is very popular for all user groups. Only technical personnel group, whose usage is far behind of the average value. The needs of this group should be determined in future investigations to increase the usage rates (See Figure 3).
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Özlem Gökkurt Bayram and Hakan Demirtel
Figure 3: Use of official e‐mail system to share knowledge by titles 4.4.3 Effective tools of knowledge access and knowledge sharing The participants of questionnaire were asked about the most effective tools of knowledge access and knowledge sharing. The most effective tools for participants are specified as official e‐mail system (177), MoD‐ ERMS (153), and MoD‐Net (148), with rates of preference for these three systems as 70%, 60%, 58% consecutively, all above 50%. The rate of marking for conventional methods could not exceed 30%. This situation is interpreted as participants believe in the benefits of ICT tools in knowledge access and knowledge sharing (See Table 5). Table 5: Efficient ICT systems/conventional methods to access and share knowledge ICT systems/conventional methods
Number of users Ratio
MoD‐ERMS
153
60%
MoD‐Net
148
58%
ADMS
48
19%
MoD official web site
59
23%
MoD‐Search
1
0.4%
Official e‐mail system
177
70%
Intra‐organizational dialogue and collaboration
75
30%
Intra‐organizational meetings/trainings
29
11%
Communication within project groups
3
1%
Printed organizational records, documents, publications
27
11%
Documents in personal computers
12
5%
4.4.4 Motivations for knowledge sharing The prominent motivational factors taking into consideration all tools of knowledge sharing are challenge of work (46%), sense of success (35%) and sense of responsibility (35%) (See Figure 4 and Table 6). It is seen that motivational factors in knowledge sharing rather focus on ICT systems as in all other findings. Whereas official e‐mail system ranks first for motivations of sense of success (61%), sense of responsibility (54%) and recognition of job done (62%), MoD‐ERMS is prominent for motivations of operational autonomy (70%) and challenge of work (83%). Among conventional methods, intra‐organizational meetings/trainings is the only conventional method in the first place as regards promotional opportunities motivation. Choice of the motivation of challenge of work as high as 83% for MoD‐ERMS (209 choices) demonstrates the importance and indispensability of ICT tools for knowledge sharing (See Table 6). It has been observed that when only ICT systems are taken into consideration in knowledge sharing, motivational factors change slightly enlisted as challenge of work, recognition of job done and sense of responsibility. However, it is observed that there are ICT systems, which are under the average of knowledge sharing motivations. The most conspicuous system among others, is MoD‐Search with 9%. On the other hand, ADMS
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Özlem Gökkurt Bayram and Hakan Demirtel (22%) and MoD official web site (29%) with knowledge sharing ratios are appeared as the first priorities to be renewed.
Figure 4: Motivation factors Table 6: Motivations for knowledge sharing in terms of ICT systems and conventional methods ICT systems/conventional methods MoD‐ERMS
sense operatio promotion sense of recogniti challen of nal al Averag responsibil on of job ge of succes autonom opportuni e ity done work s y ties 27% 46% 58% 70% 14% 83% 50%
MoD‐Net
39%
32%
30%
26%
30%
42%
33%
ADMS
25%
24%
24%
15%
14%
30%
22%
MoD official web site
28%
26%
22%
25%
30%
40%
29%
MoD‐Search
6%
8%
6%
9%
10%
14%
9%
Official e‐mail system Intra‐organizational dialogue and collaboration Intra‐organizational meetings/trainings
61%
54%
62%
30%
37%
63%
51%
50%
49%
36%
29%
45%
54%
44%
48%
42%
33%
27%
47%
53%
42%
Communication within project groups Printed organizational records, documents, publications Documents in personal computers
33%
33%
27%
20%
32%
38%
31%
39%
32%
31%
32%
42%
44%
37%
32%
40%
23%
23%
46%
45%
35%
Average
35%
35%
32%
28%
32%
46%
35%
5. Conclusion ICT applications make important contributions to formation of organizational memory through recording of all organizational knowledge assets, either structural or non‐structural, in a scrutinized manner and to creation of new knowledge through sharing of among employees. According to the results, ICT applications have much more preferable than conventional methods in processes of knowledge access and knowledge sharing. For ICT to assume an efficient role of in knowledge management, not only infrastructural elements, system architecture and functionality of application, but also compatibility with individual and organizational learning culture contribute to dissemination of knowledge. According to Hendriks “The key to success in knowledge sharing is that the personal ambition should match the group ambition. Therefore, also the touchstone for successful ICT applications for knowledge sharing is the question how they relate to these ambitions, and to the motivation of knowledge workers to match them.” (Hendriks 1999). In this study, the findings of research conducted in MoD as an organizational case study have revealed that there is a correlation between the individuals’ desire to get information about their jobs and attitudes towards using organizational knowledge sources and that ICT applications influence access to and sharing of organizational knowledge widely. Knowledge sharing motivation factors described in literature have been presented through ICT systems in MoD where those factors are supported by more than 50% usage rate of e‐mail and ERM systems. Frequent usage of ICT systems by the organization employees is crucial to develop future sustainability criteria for these systems. Renewing information systems in terms of content and technical aspects should be considered
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Özlem Gökkurt Bayram and Hakan Demirtel according to the user needs to keep continuation in raising motivation levels of sharing knowledge. In addition, the survey revealed some ICT systems that have low motivation impact. In this sense, what factors might be related to the low motivation levels of sharing knowledge for MoD_Search, ADMS, and MoD official web site should be examined for the future, with a view of finding the organizational cultural approach to value ICT systems. Another finding of the research is that ICT applications are more efficient than conventional methods in terms of motivations of knowledge sharing at organizational level. The survey results showed that digital culture has had a widespread positive impact on sharing knowledge across the Organization. Only, the reasons of low usage by technical personnel group among all user groups need to be investigated in depth. Efficient and widespread knowledge sharing at organizational level has great importance in increasing organizational competitiveness and providing sustainability. In order to carry out this function, it is necessary to establish knowledge systems that keep records of all organizational knowledge assets and thereby to disseminate knowledge sharing. Proper use of motivational factors influences active and ubiquitous sharing of knowledge in a positive direction.
References Chennamaneni A.,Teng J., Raja M.K. (2012), “A unified model of knowledge sharing behaviours: theoretical development and empirical test”, Behaviour & Information Technology, Vol 31, No.11, pp 1097‐1115. Cruywagen, M., Fourie, L.C.H., Gevers, W.R. 2005. “Understanding the role of enterprise portals in knowledge management”, 7th Annual Conference on World Wide Web Applications, 29‐31 August, Cape Town. De sitter, L.U. (1994), “Synergetisch proceduren: Human resources Mobilisation in de produktie; een inleiding in strutuurbouw (Synergetic production: Human resources mobilisation in production; an introduction to structuration), Assen, Van Gorcum. Hendriks P. (1999), “Why Share Knowledge? The Influence of ICT on the Motivation for Knowledge Sharing”, Knowledge & Process Management, Vol 6, No. 2, pp 91‐100. Herzberg, F. (1968), Work and the nature of man, London, Granada Publishing. Herzberg, F. (1987), “One more time ‐ How do you motivate employees?”, Harvard Business Review, Vol 65, No. 5, pp 109‐ 120. Hopfgartner, F. et al (2008), “Search trails using user feedback to improve video seach”, In: Proceedings of the 16th ACM international conference on multimedia, Vancouver, Canada. New York: ACM, pp 339‐348. Hung S.,Lai H. and Chang W. (2011), “Knowledge‐sharing motivations affecting R&D employees' acceptance of electronic knowledge repository”, Behaviour & Information Technology, Vol. 30 Issue 2, pp 213‐230. Lee, S.C. and Kelkar R.S. (2013), “ICT and knowledge management: perspectives from SECI model”, The Electronic Library, Vol 31, No. 2, pp 226‐243. Matusik, S.F. and Hill, C.W.L (1998), “The utilization of contingent work, knowledge creation, and competitive advantage”, Academy of Management Review, Vol 23, No. 4, pp 680‐697. Matusik, S.F. (2002), “An empirical investigation of firm public and private knowledge”, Strategic Management Journal, Vol 23, No. 5, pp 457‐467. McGrath, J.E. and Hollinshead, A.B. (1994), Groups with technology. Ideas, evidence, issues, and agenda, Thousand Oaks, CA, Sage. Nanoka, I. (1994), “Dynamic theory of organizational knowledge creation”, Organization Science, Vol 5, No. 1, pp 14‐37. Sun, Z. 2004. “A waterfall model for knowledge management and experience management”, Proc of 4th Iinternational Conference on Hybrid Intelligent Systems, Japan, IEEE Press, pp 472‐475. Sun, Z., Hao, G. 2006. “HSM: A hierarchical spiral model for knowledge management”, Faculty of Commerce‐Papers, p 36. Tsai M. and Cheng N. (2012), “Understanding Knowledge Sharing between IT Professionals ‐ An Integration of Social Cognitive and Social Exchange Theory”, Behaviour & Information Technology, Vol 31, No. 11, pp 1069‐1080.
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Blueprinting a Knowledge Sciences Center to Support a Regional Economy Denise A. D. Bedford1, John Lewis2 and Brian Moon3 1 Goodyear Professor of Knowledge Management, Kent State University Kent Ohio 2 Founder, Explanation Age LLC; Adjunct Faculty, Kent State University, Kent Ohio 3 Chief Technology Officer, Perigean Technologies; Adjunct Faculty, Kent State University, Kent Ohio
[email protected]
Abstract. As cities and regions transform from an industrial to a knowledge economy, there is a need to build new working relationships among academic, business communities, labor and workforce, civil society, and the technology sector – to create Knowledge Cities. A Knowledge City values all kinds of knowledge, is grounded in an economy that runs on st knowledge and intellectual capital, and encourages knowledge markets and transactions. The 21 century knowledge economy is dependent upon knowledge cities and regions, representing a major shift from the industrial economy. Transforming an industrial city to a Knowledge City is not a trivial task. It requires that all members of the society make the transition together. Currently, there are no institutions that can facilitate this role. This paper considers how a Knowledge Sciences Center might fulfill that role, and reports on the thoughts of over 200 participants of the Knowledge Sciences Symposium held in Canton, Ohio, and Washington DC in 2013. Keywords: Knowledge sciences center, knowledge cities, knowledge economy, economic transformation, Knowledge Sciences Symposium
1. Knowledge Sciences Symposium There is a need to redefine many of our institutional relationships and the way that our institutions work as we st transition to a knowledge economy and a knowledge society in the 21 century. No aspect of society remains unchanged in a knowledge economy – every sector, every individual, every organization and business changes. What we value shifts – intellectual capital is as important as is financial or physical capital (Andriessen 2004) (Bontis 2001) (Bontis 2002) (Bounfour and Edvinsson 2005) (Kratke 2011). In an industrial economy, academia was a haven for cutting-edge knowledge. It was where you went to learn. Solutions to industrial economy challenges are structured and managed because industrial economy challenges are linear, predictable and manageable. In the knowledge economy, there is as much or more knowledge being created outside of academia as there is within (Peters 2007). Knowledge economy challenges are chaotic, dynamic and “wicked”. The knowledge economy is not as segmented or hierarchically structured as was an industrial economy – the transformation requires that all sectors and all stakeholders move together rather than move individually. Businesses understand the challenges of competing in a knowledge-based economy. Academia needs to learn from and deliver outcomes that can be used by business. Technology needs to move away from an industrial way of working or designing products for structured work to designing for a knowledge economy. The labor force needs to continuously learn – and learn not just from business or from union provided training – but to engage with academia. Learning today goes beyond formal degree programs. MOOCs, workshops, online webinars, in house training, and continuous lifelong learning are the norm. Academia needs to provide learning opportunities not just for those who can pay for formal credentials but to those who need to learn (Vardi 2012) (Rodriguez 2012). Knowledge Cities are emerging all around the globe from the remnants of industrial cities (Baqir and Kathawalla 2004) (Brenner and Kell 2003) (Carillo 2004) (Carollo 2006) (Castells and Hall 1994) (Dvir and Pasher 2004) (Edvinsson 2006) (Ergazakis et al 2009) (Garcia 2007) (Goldberg Pasher and Sagi 2006) (Matthiessen Schwarz and Find 2006) (Metaxiotis and Ergazakis 2008) (Ovalle Barquez and Salomon 2004) (Papalambros 2011) (van Winden et al 2012). The transition, though, does not always include all members or organizations of the industrial city.
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Denise A. D. Bedford, John Lewis and Brian Moon In September 2013, an emergent community of 200 people from across the country gathered in Canton, Ohio, and in Washington DC, to hold a Knowledge Sciences Symposium (www.kent.edu/slis/programs/iakm/symposium/index.cfm). The purpose of the Symposium was to bring together knowledge management thought leaders from businesses and organizations, technology sector, academia, civil society organizations and the broader workforce to design a blueprint for a Knowledge Sciences Center in order to support the transformation of st local industrial economies into the 21 century knowledge economy. The Symposium discussions were preceeded by five webinars in July 2013. The Symposium participants (“Participants”) designed a blueprint for st a 21 century Knowledge Sciences Center that focused on learning and career development, research and development, advocacy, advising and outreach and partnerships. The goal of this paper is to share that blueprint with the knowledge management community in order to elicit feedback and to find other people interested in moving the vision forward.
1.1 Rationale for a Knowledge Sciences Center Participants envisioned a Knowledge Sciences Center as a source that would help a local economy and society st make an effective transition to the 21 century knowledge economy. It was important to capture within the name of this Center the idea that the activities would go beyond what has typically been described as Knowledge Management. As a science, the range of activities would need to span the theoretical and academic foundations as well as the commercial and practical applications. The Knowledge Sciences Center we envisioned required a new blueprint if it was to serve this purpose.
1.2 Existing Models There are many examples of research institutes,, science centers and think tanks, but none that aligned with the community and economy focus of the Knowledge Sciences Center. Research institutes and science centers are designed to leverage expert knowledge, often focused on theoretical research or the R&D needs of specific funding organizations (Anttiroika 2004) (Appold 2003) (Chen and Choi 2004) (O’Mara 2005). The intended stakeholders are other highly credentialed or deeply resourced organizations, and the engagement models are heavily dependent upon public or endowment funding sources. Another example of a science center is a Think Tank where experts focus on investigating current topics for the purpose of advocacy or public policy development (Mendizabal 2010) (Goodman 2005). While these models certainly serve a purpose, Participants agreed that they do not meet the needs of a city or region making the transition to a knowledge economy. There was a clear consensus that a new model was needed.
2. Design Issues The Participants envisioned a new kind of Center that would act as a bridge between the worlds of academia, business, labor and technology, and could find no existing models to use as a blueprint. The design and vision emerged as we explored five issues (Figure 1). We needed to know who would participate in the center (Issue 1). We needed to know what kinds of activities the center would support to achieve its goals (Issue 2). We needed to know how stakeholders would engage (Issue 3). We needed to know how we would fund the Center (Issue 4). Finally, we needed to know what it would look like – physically and virtually (Issue 5). How do we engage? What do we do?
Issue 3
Issue 2
Who are the stakeholders? Issue 1
How do we fund? Issue 4
Knowledge Sciences Center
Figure 1. Knowledge Center Vision and Design – Five Key Issues
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What does it look like? Issue 5
Denise A. D. Bedford, John Lewis and Brian Moon Issue 1: Who are Participants in a Knowledge Sciences Center? We began the discussion of stakeholders with an assumption that there were five primary interest groups, including academic, business, labor, civil society and technology developers. It quickly became obvious that these groups were neither comprehensive nor inclusive of possible stakeholders. We realized we needed to look at potential stakeholders from multiple perspectives. In the end, the Participants concluded that any member of the community that was being served by the Knowledge Sciences Center was a potential stakeholder, including but not limited to: academic, religious, and educational institutions, libraries, localized ownership, NGOs, governmental organizations – federal, state, local, county , academics, congressional staff, service organizations (boy scouts, girls scouts, youth groups, 501(3)c organizations, charitable organizations, military support organizations, professional societies, chambers of commerce, city visitors’ bureaus, unions, local government agencies such as fire, police, emergency management, innovators in search of partners, elected government officials, and voluntary sector organizations. The list of participants clearly requires a different kind of organization than traditional institutes, science centers or think tanks. Understanding stakeholders along a single dimension such as their economic role presented a risk, but understanding stakeholder interests and needs will be necessary for brainstorming the types of activities, products and services the Center should provide. As a first step, Participants suggested a Knowledge Sciences Center should prepare persona. Persona templates would help to understand stakeholders’ goals, their different roles and responsibilities, their technology environment and skill levels, social media behaviors, and pain points. All of these dimensions are critical to planning activities, to designing access and supporting collaborative environments, to financing activities and to designing engagement models. Issue 2: What Do We Do? A core question for the blueprint is, “What does the Center do for these stakeholders?” We were fortunate to have more than 200 seasoned knowledge management professionals share their ideas on activities. We were also fortunate that this group had an implicit understanding of what we meant by knowledge sciences – its goals, its scope – and by what it means to practice knowledge management - its methods and tools. The participants proposed five areas of focus drawing upon their profound knowledge of the field and the challenges inherent to the transformation (Figure 2).
Figure 2. Business Capabilities of a Knowledge Sciences Center The five broad areas were: (1) Learning and Career Development; (2) Research and Development; (3) Advocacy; (4) Advising; and (5) Networking and Partnerships. A significant portion of the in-person meetings in Ohio and Washington DC were devoted to brainstorming activities for these five areas. As shown in Tables 15, there was no shortage of ideas.
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Denise A. D. Bedford, John Lewis and Brian Moon Table 1. Learning and Development Activities Activity Name Center of Excellence Reference materials
Knowledge Sciences Learning Programs
(KS)
KS Book and Journal Clubs KS TV Knowledge Sciences Learning Center Knowledge Visitor Center KS FAQs Student Internships Practicum
and
Brief Description Business Growth Maps, Case Studies, Lessons Learned/Smart Lessons, Information Repositories – Wikimedia Repositories for Other Hubs/Chapters, KM Body of Knowledge, KM Standards, Knowledge Visualizations, Open Repository or Wiki, Real Work Scenarios, Roadmaps, ROI Methods, Scalable Solutions, Standards Organizations, , KM Principles MOOCS, ADDIE Model Training and Collaborative Workshops, Webinars, in House Training Programs for Organizations, Retraining Programs With Economic Development Units. Open Discussions of Recent Works to Help Promote Research Uptake KM Tedtalks, Open Webinars, KM Internet Travel Channel, Community of Practice Study Tours (Virtual and Physical) Certificate Programs, Competitions for Knowledge Games, Learning Games – Simulations, Pointers to Courses, Pointers to Programs, Transformation Learning Support Orientation to rhe Knowledge Society and Knowledge Economy, KM Tourism, KM Concierge Basic Q&A for KM Novices, FAQs for Individual Topics, KM Study Guides Project and Internship Opportunities, Student Resumes and CVs, Matchup Projects and Industry Needs
Table 2. Research and Development Activities Activity Name KS Experimental Test Lab and Incubator
Knowledge Collaborative Development
Sciences Research &
Knowledge Sciences Information Access Improvement Knowledge Challenge Workshops and Projects Knowledge Elicitation Lab General Research & Development Knowledge Economy Future State Visions Knowledge Sciences Research for Economic Sectors and Industries
Brief Description Access to Smart Knowledge Systems, Technology Transfer Facilitation and Adoption, Novel Approaches to Licensing Or Purchasing Tools for Groups Or Communities, Guidebooks for Scalable and Right-Sized Solutions, Technology Transfer Opportunities, Identification of Reasonably Priced Platforms for Small and Medium Sized Organizations, Evaluate Products for Vendors, Focus Group Testing for Vendors, Open Source Software Development for Knowledge Sciences Community – in Collaboration With Other Disciplines Collect Research Needs Ideas , Creation of Use Cases and Case Studies, Enterprise Scalable Solutions, Interoperable Solutions, New Approaches to Translation and Interpretation of Regulations, Policies and Standards, Provide Real World Problems for The Center to Work On, Research Agenda, Research Needs Statements, Standards and Guidelines for Findability Knowledge Sciences Languages, Knowledge Sciences Organization Systems (e.g., Classification Schemes, Thesauri, Authoritative Lists) Global Expert Teams, Special Topics, Wicked Problem Teams Knowledge Elicitation Training, Knowledge Loss Prevention and Capture Strategies Assess Research Capabilities, Benchmarking Opportunities, Knowledge Cities Index, Knowledge Economy Models, Knowledge Society Behavior Codes and Ethics, Project Assessments, KM Rsearch Agendas, Innovation Research Economic Sector Scans, Industry Scans Knowledge Society Futures. Knowledge Futures for Specific Organizations
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Denise A. D. Bedford, John Lewis and Brian Moon Table 3. Advocacy Activities Activity Name Active Engagement with Knowledge Economy Transformation Executive marketing and communication about KM KM Competencies
Activity Examples Adaptive Society Change Information Technologies, Innovation to Gain Market Share, Libraries Coached to Communicate Knowledge Management in Real-World Terms Knowledge Sharing Workshops, Lessons Learned Engaging With Corporate Executives Cost Reducing Solutions, Early Maturity Needs, Efficient and Effective Solutions , Facilitation Services, Larger Strategic Perspective , Problem Solving Approaches That Leverage KM, Standards Graphs Showing ROI Marketing Center for All Things KM, Ability to Integrate with Other Domains, Providing Opportunities for Professionals to Socialize and Exchange Ideas
Sponsorship and Representation at Major Conferences and Social Activities Development of KM Legal and Ethical Codes KM Standards Development and Promotion
Advocacy With Professional Societies, Collaboration With Human Capital and Human Resource Management Establish Committees to Define Standards for KM Professionals, Develop Standards for KM Professionals, Assess the Validity for Standards for KM Professionals, Disseminate Standards for KM Professions Criteria for Teaching and Selection, Subversive Missions - Influencing Education and R&D, Gaming and Simulation, Education Technology, Cognitive Sciences, Lifelong Learning, Communications Receiving and Broadcasting Knowledge Management Projects Throughout the KSC Network, Promoting Stakeholder Capabilities Working with Publishers to Develop Pricing Models That Support Broad Access to Knowledge Management Research and Development, Case Studies and Thought Papers, Develop Online Open Access Journals and Trade Publications to Promote Stakeholder Knowledge and Learning. KM Awards and Recognition of Leading Organizations and Individuals
Promotion of KM at all levels of education Promotion of KM Project Opportunities Promotion of Open Access KM Journals Knowledge Awards
Management
Industry
Table 4. Outreach and Partnership Activity Name Annual KM Surveys Consulting and Advising Development and Collection of Metrics and Stories Funding proposals and opportunities Knowledge Management Mentorships Open Virtual Laboratory
Brief Description Understand Stakeholder Needs, Local and Networked Resources Establish Requirements, Create “People Finder” (e.g., through LinkedIn), Differentiate Types of Consulting the Center Does / Pilots, Develop a Methodology for Matching Stakeholders with Expertise for Consulting Purposes / Services, Identify Tools Repository Performance Plan Examples, Price Points, Provide Strategic Maps and Assistance to Cities and Towns Crowdsourced Solutions, Crowdsourced Funding for KM Research Needs, Short Term Services Mentoring Across Organizations, Mentoring Across Ages Learning Management System, Sandbox Tool – Simulators, Prototypes, “Authoritative” Tools, Customer Relation System, Profile, Access Rights, Track & Trend Analysis, Library of Access to Authoritative KM Content, Ontologies, Analysis, Blogs, Social Media Presence, Tool “Reviews”/ Recommendations
Table 5. Advising Activities Activity Name Broadcasting KS Activities Networking and Public Outreach
Open Meetings Spaces Outreach to Other Disciplines and Economic Sectors Social Media Support for Dynamic Conversations
Activity Examples “News” Source for Innovative KM Practices, KM Blogs, Investigative Reporting, Electronic Calendar of Global KM Events Community Networking, Linking Consultants and Clients, Affinity Grouping within and across Sectors, Networking across City Organizations, Links From Citizens to Thought Leaders, Knowledge Connectors – Linking Those with Problems and Those with Solutions, Knowledge Practitioners Directory Experiments, Brainstorming Sessions, Knowledge Jams, Partnership Outreach and Extension Service Links to Twitter Feeds Related to Knowledge Sciences
The list serves as a catalog of opportunities for any group that wishes to take up the challenge of building a Knowledge Sciences Center. It serves as a tool for prioritizing and implementing activities as relationships with stakeholders develop. Clearly, there are variations in cost, value, duration and sustainability, and lead times.
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Denise A. D. Bedford, John Lewis and Brian Moon The significant number of activities recommended reinforces both the need for and the lack of existing support provided by current players. It is clear that no one organization or institution can fulfill all of these needs. Only through working in a consortium or cooperative environment can a Knowledge Sciences Center meet these needs. Different activities and stakeholders also mean different engagement models. Issue 3: How Do We Engage? The Center’s engagement strategy is complex. Multiple engagement models would be required because different kinds of activities require different ways of working. Multiple models are needed because stakeholders’ interests, environments and resources vary. Participants discussed five possible engagement models, including: (1) Traditional academic R&D model; (2) Agricultural extension service model; (3) Knowledge services corps model similar to that of the Peace Corps; (4) Consortium model; and (5) Business franchise model. The first envisioned model would support applied research that is needed by the community or for which there is no other logical source. This engagement model looks like a traditional academic science center where knowledge resides in the center and is channeled out to the community. Such a model assumes there would be formal contracts in place with funding agencies or organizations, and that all research standards, records and protocols would need to be maintained. In order to support research, access to library resources is also required. The Center would have to work with the university or college to contract for access. The second envisioned model resembles that of an agricultural extension service. This model would support the development of solutions needed by the community, the non-formal learning needs of the community, and technology transfer issues. In this model the Center uses visits to stakeholders as a way of staying in touch with the needs of the local community, gather input to policy formulation, and provide targeted client advice. This engagement model would be a good fit for Learning and Career Development, and Advising activities. The third envisioned model resembles a Knowledge Services Corps – similar to a missionary model or Peace Corps structures where knowledge evangelists engage directly with the community to foster conversations and knowledge transactions while leveraging the Center’s infrastructure and resources. This engagement model might leverage graduate students, students fulfilling practicum or internship requirements, who were supported by community scholarships, or volunteers earning community service or continuing education credits. This model would align well with Outreach and Partnership activities. Tje fourth envisioned model resembles that of a consortium where the Center acts as a cooperative partner with other universities, institutions, and agencies to support activities. This model supports activities that require or benefit from a collaborative environment. This engagement model would be a good fit for Advocacy activities, where the Center would partner with other organizations to move initiatives and standards forward on behalf of the larger community. And a fifth envisioned model – business franchise – was suggested. This was a particularly interesting model because it would allow the Center to reach out into the community through a hub-spoke model, and because it would provide conceptual buy-in and ownership relationships. “Franchise owners” at local libraries or universities or agencies would provide space or connectivity through which stakeholders could engage with the Center. Issue 4: How Do We Fund the Center? As a Knowledge Sciences Center our goal would be to mobilize and promote ideas. As with any such venture, funding will be necessary for sustained effect. Participants were asked to consider what kind of an innovative funding model would support Learning and Career Development, Research and Development, Advocacy, Advising and Networking. The answer to this question was similar to other answers – multi-faceted, dynamic and flexible. Funding models – as engagement models – must be relevant to the activity and to the stakeholders. Learning and Career Development activities may leverage a variety of funding models ranging from entirely open source contributed courses accessible on MOOCs, to no-fee open webinars, to fee-based workshops and on-site training courses, to formal certification or testing services. Advocacy activities would leverage in kind resources, community grants, crowd-funding, or direct sponsorship.
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Denise A. D. Bedford, John Lewis and Brian Moon Research and Development may be funded through grants, research funding awards, and joint sponsored funding. Research may also be supported by in-kind contributions of the members of global expert teams. The model will depend on the nature and intensity of the research. R&D projects that support technology development or evaluation may be sponsored by technology vendors or venture capitalists. Research that has a direct community application may be funded through crowd-sourced or in-kind contributions. The nature of the funding must also take into consideration the intellectual property rights of the products and services. In some cases, established intellectual property provisions will apply. In other cases, creative commons and open source models might be more appropriate. Another funding model would be pay-for-service. This may be appropriate for Advising activities. Again, there would need to be a progressive pricing strategy to ensure that all members of the community can afford to participate in these activities. The lowest pricing option should be an in-kind contribution or a barter system. In-kind contributions strengthen the Center by increasing its stock of knowledge. Where the Center might support in-kind contributions or contributed services, it would be necessary for stakeholders to have access, and the Center to support the idea of a “knowledge bank”. The idea would be that as stakeholders contribute to the Center, they earn intellectual credit that can be applied to future requests. Also proposed was a fee-based membership model.. The challenge with membership models,though, is that they lock and organization into providing predictable and pre-defined services to members. This typically leads to the need to define generic products and services rather than on-demand or stakeholder-focused activities. We have observed that institutions based on memberships over time can become bogged down in the administrative tasks of supporting members. The membership model might also price many community members out of most engagements. The Participants thought that a membership model should be considered only after all other options had been explored. In addition, to having a stock set of funding models, the Center would need to have a robust list of funding sources and opportunities. On-going fundraising relevant to current or planned engagements would be one of the Center’s major operations. Issue 5: What Does the Center Look Like? The Participants were of one mind in recommending both a virtual and a physical preference. The sentiment was that the physical presence should be minimalist and networked to increase visibility. The physical space should ideally be located on a university or college campus to ensure there is easy access to faculty and students, as well as to research protocol support. However, participants suggested that a remote or satellite campus might be more appropriate to ensure that the Center can establish its own innovationoriented, dynamic and community-focused organizational culture. The nature of the space should be open, heavily technology-enabled, with spaces for stakeholders to meet and work. The physical space should feel like an open knowledge sharing environment. As the Center grows, there may be a need for spaces for visiting scholars or short-term team work spaces. Depending on the nature of the stakeholders, their competencies and environments, the physical Center may need to provide access to the Center’s virtual space. We would also expect “Center franchisees” to provide community-based access to the Center. The Center’s virtual structure includes online collaboration environments, access to social media and cloud-based repositories. The Center is also virtually linked to other similar-Centers. The Center’s virtual presence might leverage cutting edge technologies under development or testing by technology developers or vendors. The heavy reliance on virtual access would present both challenges and opportunities. In terms of challenges we would expect that many stakeholders would not have affordable high-bandwidth access. We also expect that digital literacy rates might be low for some stakeholders. This presents opportunities, though, for coaching and mentorships particularly where students and community members contribute training time in exchange for other services.
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3. The Blueprint The participants generated a wealth of ideas and options. While a number of support activities might be consistently supported through stable funding sources, it is clear that many will be ‘designer-oriented’. In other words, a stakeholder engagement and funding design model might need to be put in place for each activity. This is not the way that most organizations work. Thus, the participants agreed that an engagement design model would need to be developed for the Center. The model favored by the participants was an emergent engagement design (Figure 3). The design process would begin with a proposed activity. To ensure that the Center stays true to its goal of facilitating the community or local area’s transition to a knowledge economy, deployment needs to be carefully managed and aligned with demand. The Center would put in place the virtual infrastructure, and engage stakeholders in activities that required low investments but could demonstrate high value. As value is recognized and promoted, stakeholder engagements would expand and build the Center’s reputation.
Stakeholder Competencies Ownership Issues
Stakeholder Environment Engagement Design
Activity Engagement Model
Outputs and Outcomes Funding Options Figure 3. Knowledge Center Activities
4. Observations and Next Steps The purpose of sharing these ideas is to encourage communities around the world to consider starting a Knowledge Sciences Center. We hope that this paper and its presentation at the ECKM-2014 Conference will encourage others to take up the challenge of creating a knowledge sciences center. We hope that others will share their experiences and ideas on the design issues we have raised and the blueprint that emerged from the Symposium discussions. A second Knowledge Sciences Symposium is being planned for 2014 to carry these ideas forward.
References Andriessen, D. (2004). Making sense of intellectual capital: designing a method for the valuation of intangibles. Routledge. Anttiroiko, A. V. (2004). “Science cities: their characteristics and future challenges”, International Journal of Technology Management, 28(3), 395-418. Appold, S.(2003). “Research parks and the location of industrial research laboratories: An analysis of the effectiveness of a policy intervention”, Research Policy 33, 225 – 243. Baqir, M. N., & Kathawala, Y. (2004). “Ba for knowledge cities: a futuristic technology model”, Journal of Knowledge Management, 8(5), 83-95. Bontis, N. (2001). “Assessing knowledge assets: A review of the models used to measure intellectual capital”. International Journal of Management Reviews, 3(1), 41-60. Bontis, N. (2002). National Intellectual Capital Index: Intellectual Capital Development in the Arab Region. United Nations, NY. Bounfour, A. and Edvinsson, L. (2005). Intellectual Capital for Communities: Nations, Regions and Cities, ButterworthHeinemman, Boston. Carrillo, F. J. (2004). “Capital Cities: A Taxonomy of Capital Accounts for Knowledge Cities”, Journal of Knowledge Management, Special Issue on Knowledge-based Development II, Knowledge Cities, 8(5), 28-46. Carrillo, F. J. (2006). Knowledge Cities – Approaches, Experiences, Perspective. Butterworth-Heinemann, 2006.
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Denise A. D. Bedford, John Lewis and Brian Moon Castells, M. (2000), The rise of network society, Blackwell Publishers Castells, M. and Hall, P. (1994). Technopoles of the World: The Making of Twenty-first Century Industrial Complexes. London: Routledge. Chen, S and Choi, C.J. (2004). “Creating a Knowledge-based City: The example of Hsinchu Science Park”, Journal of Knowledge Management, Vol. 8, No. 5, 73 – 82 Dvir, R., & Pasher, E. (2004). “Innovation engines for knowledge cities: an innovation ecology perspective”, Journal of Knowledge Management, 8(5), 16-27. Edvinsson, L. (2006). “Aspects on the city as a knowledge tool”, Journal of Knowledge Management 10(5), 6-13. Ergazakis, E., Ergazakis, K., Metaxiotis, K. and Charalabidis, Y. (2009) “Rethinking the development of successful knowledge cities: an advanced framework”, Journal of Knowledge Management 13(5), 214-227. Ergazakis, K., Metaxiotis, K., Psarras, J. and Askounis, D. (2006). “A unified methodological approach for the development of knowledge cities”, Journal of Knowledge Management 10(5), 65-78 Garcia, B. C. (2006). “Learning conversations: knowledge, meanings and learning networks in Greater Manchester”. Journal of Knowledge Management 10(5), 99-109, Garcia, B.C. (2007). “Working and learning in a knowledge city: a multilevel development framework for knowledge workers”, Journal of Knowledge Management 11(5), 18-30, Goldberg, M., Pasher, E., and Sagi, M. L. (2006). “Citizen participation in decision-making processes: knowledge sharing in knowledge cities” . Journal of Knowledge Management 10(5), 92-98, Goodman, J. C. (2005). What is a Think Tank? National Center for Policy Analysis. Haughton, G. and Hunter, C. (2003), Sustainable Cities, Routledge. Kratke, S. (2011). The Creative Capital of Cities: Interactive Knowledge Creation and the Urbanization Economies of Innovation. Blackwell, 2011 Matthiessen, C. W., Schwarz, A. W. and Find, S. (2006). “World cities of knowledge: research strength, networks and nodality”, Journal of Knowledge Management 10(5), 14-25, Mendizabal, E. (2010). on the business model and how this affects what think tanks do, http://onthinktanks.org/2010/10/03/on-the-business-model/ Retrieved 2011-11-02. Metaxiotis, K. and Ergazakis, K. (2008). “Exploring stakeholder knowledge partnerships in a knowledge city: a conceptual model”. Journal of Knowledge Management 12(5), 137-150, O’Mara, M. P. (2005). Cities of Knowledge: Cold War Science and the Search for the Next Silicon Valley. Princeton University Press, 2005. Ovalle, M., Barquez, J. A. A., and Salomon, S. D. M. (2004). “A compilation of resources on knowledge cities and knowledge-based development”. Journal of Knowledge Management. 8(6), 107-127. Papalambros, Panos Y. (2011). "A New Knowledge Ecosystem." Journal of Mechanical Design 133.perspective’’, Journal of Knowledge Management, 8(5), 16-27. Peters, M. A. (2007). Knowledge economy, development and the future of higher education. Rotterdam: Sense Publishers. Rodriguez, C. O. (2012). “MOOCs and the AI-Stanford Like Courses: Two Successful and Distinct Course Formats for Massive Open Online Courses”. European Journal of Open, Distance and E-Learning. van Winden, W., de Carvalho, L., van Tuijl, E. and van Haaren, J. (2012). Creating Knowledge Locations in Cities: Innovation and Integration Challenges. Routledge. Vardi, M. Y. (2012). “Will MOOCs destroy academia?” Communications of the ACM, 55(11), 5.
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Blueprinting a Knowledge Sciences Center to Support a Regional Economy Denise A. D. Bedford1, John Lewis2 and Brian Moon3 1 Goodyear Professor of Knowledge Management, Kent State University Kent Ohio 2 Founder, Explanation Age LLC; Adjunct Faculty, Kent State University, Kent Ohio 3 Chief Technology Officer, Perigean Technologies; Adjunct Faculty, Kent State University, Kent Ohio
[email protected]
Abstract. As cities and regions transform from an industrial to a knowledge economy, there is a need to build new working relationships among academic, business communities, labor and workforce, civil society, and the technology sector – to create Knowledge Cities. A Knowledge City values all kinds of knowledge, is grounded in an economy that runs on st knowledge and intellectual capital, and encourages knowledge markets and transactions. The 21 century knowledge economy is dependent upon knowledge cities and regions, representing a major shift from the industrial economy. Transforming an industrial city to a Knowledge City is not a trivial task. It requires that all members of the society make the transition together. Currently, there are no institutions that can facilitate this role. This paper considers how a Knowledge Sciences Center might fulfill that role, and reports on the thoughts of over 200 participants of the Knowledge Sciences Symposium held in Canton, Ohio, and Washington DC in 2013. Keywords: Knowledge sciences center, knowledge cities, knowledge economy, economic transformation, Knowledge Sciences Symposium
1. Knowledge Sciences Symposium There is a need to redefine many of our institutional relationships and the way that our institutions work as we st transition to a knowledge economy and a knowledge society in the 21 century. No aspect of society remains unchanged in a knowledge economy – every sector, every individual, every organization and business changes. What we value shifts – intellectual capital is as important as is financial or physical capital (Andriessen 2004) (Bontis 2001) (Bontis 2002) (Bounfour and Edvinsson 2005) (Kratke 2011). In an industrial economy, academia was a haven for cutting-edge knowledge. It was where you went to learn. Solutions to industrial economy challenges are structured and managed because industrial economy challenges are linear, predictable and manageable. In the knowledge economy, there is as much or more knowledge being created outside of academia as there is within (Peters 2007). Knowledge economy challenges are chaotic, dynamic and “wicked”. The knowledge economy is not as segmented or hierarchically structured as was an industrial economy – the transformation requires that all sectors and all stakeholders move together rather than move individually. Businesses understand the challenges of competing in a knowledge-based economy. Academia needs to learn from and deliver outcomes that can be used by business. Technology needs to move away from an industrial way of working or designing products for structured work to designing for a knowledge economy. The labor force needs to continuously learn – and learn not just from business or from union provided training – but to engage with academia. Learning today goes beyond formal degree programs. MOOCs, workshops, online webinars, in house training, and continuous lifelong learning are the norm. Academia needs to provide learning opportunities not just for those who can pay for formal credentials but to those who need to learn (Vardi 2012) (Rodriguez 2012). Knowledge Cities are emerging all around the globe from the remnants of industrial cities (Baqir and Kathawalla 2004) (Brenner and Kell 2003) (Carillo 2004) (Carollo 2006) (Castells and Hall 1994) (Dvir and Pasher 2004) (Edvinsson 2006) (Ergazakis et al 2009) (Garcia 2007) (Goldberg Pasher and Sagi 2006) (Matthiessen Schwarz and Find 2006) (Metaxiotis and Ergazakis 2008) (Ovalle Barquez and Salomon 2004) (Papalambros 2011) (van Winden et al 2012). The transition, though, does not always include all members or organizations of the industrial city.
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Denise A. D. Bedford, John Lewis and Brian Moon In September 2013, an emergent community of 200 people from across the country gathered in Canton, Ohio, and in Washington DC, to hold a Knowledge Sciences Symposium (www.kent.edu/slis/programs/iakm/symposium/index.cfm). The purpose of the Symposium was to bring together knowledge management thought leaders from businesses and organizations, technology sector, academia, civil society organizations and the broader workforce to design a blueprint for a Knowledge Sciences Center in order to support the transformation of st local industrial economies into the 21 century knowledge economy. The Symposium discussions were preceeded by five webinars in July 2013. The Symposium participants (“Participants”) designed a blueprint for st a 21 century Knowledge Sciences Center that focused on learning and career development, research and development, advocacy, advising and outreach and partnerships. The goal of this paper is to share that blueprint with the knowledge management community in order to elicit feedback and to find other people interested in moving the vision forward.
1.1 Rationale for a Knowledge Sciences Center Participants envisioned a Knowledge Sciences Center as a source that would help a local economy and society st make an effective transition to the 21 century knowledge economy. It was important to capture within the name of this Center the idea that the activities would go beyond what has typically been described as Knowledge Management. As a science, the range of activities would need to span the theoretical and academic foundations as well as the commercial and practical applications. The Knowledge Sciences Center we envisioned required a new blueprint if it was to serve this purpose.
1.2 Existing Models There are many examples of research institutes,, science centers and think tanks, but none that aligned with the community and economy focus of the Knowledge Sciences Center. Research institutes and science centers are designed to leverage expert knowledge, often focused on theoretical research or the R&D needs of specific funding organizations (Anttiroika 2004) (Appold 2003) (Chen and Choi 2004) (O’Mara 2005). The intended stakeholders are other highly credentialed or deeply resourced organizations, and the engagement models are heavily dependent upon public or endowment funding sources. Another example of a science center is a Think Tank where experts focus on investigating current topics for the purpose of advocacy or public policy development (Mendizabal 2010) (Goodman 2005). While these models certainly serve a purpose, Participants agreed that they do not meet the needs of a city or region making the transition to a knowledge economy. There was a clear consensus that a new model was needed.
2. Design Issues The Participants envisioned a new kind of Center that would act as a bridge between the worlds of academia, business, labor and technology, and could find no existing models to use as a blueprint. The design and vision emerged as we explored five issues (Figure 1). We needed to know who would participate in the center (Issue 1). We needed to know what kinds of activities the center would support to achieve its goals (Issue 2). We needed to know how stakeholders would engage (Issue 3). We needed to know how we would fund the Center (Issue 4). Finally, we needed to know what it would look like – physically and virtually (Issue 5). How do we engage? What do we do?
Issue 3
Issue 2
Who are the stakeholders? Issue 1
How do we fund? Issue 4
Knowledge Sciences Center
Figure 1. Knowledge Center Vision and Design – Five Key Issues
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What does it look like? Issue 5
Denise A. D. Bedford, John Lewis and Brian Moon Issue 1: Who are Participants in a Knowledge Sciences Center? We began the discussion of stakeholders with an assumption that there were five primary interest groups, including academic, business, labor, civil society and technology developers. It quickly became obvious that these groups were neither comprehensive nor inclusive of possible stakeholders. We realized we needed to look at potential stakeholders from multiple perspectives. In the end, the Participants concluded that any member of the community that was being served by the Knowledge Sciences Center was a potential stakeholder, including but not limited to: academic, religious, and educational institutions, libraries, localized ownership, NGOs, governmental organizations – federal, state, local, county , academics, congressional staff, service organizations (boy scouts, girls scouts, youth groups, 501(3)c organizations, charitable organizations, military support organizations, professional societies, chambers of commerce, city visitors’ bureaus, unions, local government agencies such as fire, police, emergency management, innovators in search of partners, elected government officials, and voluntary sector organizations. The list of participants clearly requires a different kind of organization than traditional institutes, science centers or think tanks. Understanding stakeholders along a single dimension such as their economic role presented a risk, but understanding stakeholder interests and needs will be necessary for brainstorming the types of activities, products and services the Center should provide. As a first step, Participants suggested a Knowledge Sciences Center should prepare persona. Persona templates would help to understand stakeholders’ goals, their different roles and responsibilities, their technology environment and skill levels, social media behaviors, and pain points. All of these dimensions are critical to planning activities, to designing access and supporting collaborative environments, to financing activities and to designing engagement models. Issue 2: What Do We Do? A core question for the blueprint is, “What does the Center do for these stakeholders?” We were fortunate to have more than 200 seasoned knowledge management professionals share their ideas on activities. We were also fortunate that this group had an implicit understanding of what we meant by knowledge sciences – its goals, its scope – and by what it means to practice knowledge management - its methods and tools. The participants proposed five areas of focus drawing upon their profound knowledge of the field and the challenges inherent to the transformation (Figure 2).
Figure 2. Business Capabilities of a Knowledge Sciences Center The five broad areas were: (1) Learning and Career Development; (2) Research and Development; (3) Advocacy; (4) Advising; and (5) Networking and Partnerships. A significant portion of the in-person meetings in Ohio and Washington DC were devoted to brainstorming activities for these five areas. As shown in Tables 15, there was no shortage of ideas.
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Denise A. D. Bedford, John Lewis and Brian Moon Table 1. Learning and Development Activities Activity Name Center of Excellence Reference materials
Knowledge Sciences (KS) Learning Programs KS Book and Journal Clubs KS TV Knowledge Sciences Learning Center Knowledge Visitor Center KS FAQs Student Internships and Practicum
Brief Description Business Growth Maps, Case Studies, Lessons Learned/Smart Lessons, Information Repositories – Wikimedia Repositories for Other Hubs/Chapters, KM Body of Knowledge, KM Standards, Knowledge Visualizations, Open Repository or Wiki, Real Work Scenarios, Roadmaps, ROI Methods, Scalable Solutions, Standards Organizations, , KM Principles MOOCS, ADDIE Model Training and Collaborative Workshops, Webinars, in House Training Programs for Organizations, Retraining Programs With Economic Development Units. Open Discussions of Recent Works to Help Promote Research Uptake KM Tedtalks, Open Webinars, KM Internet Travel Channel, Community of Practice Study Tours (Virtual and Physical) Certificate Programs, Competitions for Knowledge Games, Learning Games – Simulations, Pointers to Courses, Pointers to Programs, Transformation Learning Support Orientation to rhe Knowledge Society and Knowledge Economy, KM Tourism, KM Concierge Basic Q&A for KM Novices, FAQs for Individual Topics, KM Study Guides Project and Internship Opportunities, Student Resumes and CVs, Matchup Projects and Industry Needs
Table 2. Research and Development Activities Activity Name KS Experimental Test Lab and Incubator
Knowledge Sciences Collaborative Research & Development Knowledge Sciences Information Access Improvement Knowledge Challenge Workshops and Projects Knowledge Elicitation Lab General Research & Development Knowledge Economy Future State Visions Knowledge Sciences Research for Economic Sectors and Industries
Brief Description Access to Smart Knowledge Systems, Technology Transfer Facilitation and Adoption, Novel Approaches to Licensing Or Purchasing Tools for Groups Or Communities, Guidebooks for Scalable and Right-Sized Solutions, Technology Transfer Opportunities, Identification of Reasonably Priced Platforms for Small and Medium Sized Organizations, Evaluate Products for Vendors, Focus Group Testing for Vendors, Open Source Software Development for Knowledge Sciences Community – in Collaboration With Other Disciplines Collect Research Needs Ideas , Creation of Use Cases and Case Studies, Enterprise Scalable Solutions, Interoperable Solutions, New Approaches to Translation and Interpretation of Regulations, Policies and Standards, Provide Real World Problems for The Center to Work On, Research Agenda, Research Needs Statements, Standards and Guidelines for Findability Knowledge Sciences Languages, Knowledge Sciences Organization Systems (e.g., Classification Schemes, Thesauri, Authoritative Lists) Global Expert Teams, Special Topics, Wicked Problem Teams Knowledge Elicitation Training, Knowledge Loss Prevention and Capture Strategies Assess Research Capabilities, Benchmarking Opportunities, Knowledge Cities Index, Knowledge Economy Models, Knowledge Society Behavior Codes and Ethics, Project Assessments, KM Rsearch Agendas, Innovation Research Economic Sector Scans, Industry Scans Knowledge Society Futures. Knowledge Futures for Specific Organizations
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Denise A. D. Bedford, John Lewis and Brian Moon Table 3. Advocacy Activities Activity Name Active Engagement with Knowledge Economy Transformation Executive marketing and communication about KM KM Competencies
Activity Examples Adaptive Society Change Information Technologies, Innovation to Gain Market Share, Libraries Coached to Communicate Knowledge Management in Real-World Terms Knowledge Sharing Workshops, Lessons Learned Engaging With Corporate Executives Cost Reducing Solutions, Early Maturity Needs, Efficient and Effective Solutions , Facilitation Services, Larger Strategic Perspective , Problem Solving Approaches That Leverage KM, Standards Graphs Showing ROI Marketing Center for All Things KM, Ability to Integrate with Other Domains, Providing Opportunities for Professionals to Socialize and Exchange Ideas
Sponsorship and Representation at Major Conferences and Social Activities Development of KM Legal and Ethical Codes KM Standards Development and Promotion
Advocacy With Professional Societies, Collaboration With Human Capital and Human Resource Management Establish Committees to Define Standards for KM Professionals, Develop Standards for KM Professionals, Assess the Validity for Standards for KM Professionals, Disseminate Standards for KM Professions Criteria for Teaching and Selection, Subversive Missions - Influencing Education and R&D, Gaming and Simulation, Education Technology, Cognitive Sciences, Lifelong Learning, Communications Receiving and Broadcasting Knowledge Management Projects Throughout the KSC Network, Promoting Stakeholder Capabilities Working with Publishers to Develop Pricing Models That Support Broad Access to Knowledge Management Research and Development, Case Studies and Thought Papers, Develop Online Open Access Journals and Trade Publications to Promote Stakeholder Knowledge and Learning. KM Awards and Recognition of Leading Organizations and Individuals
Promotion of KM at all levels of education Promotion of KM Project Opportunities Promotion of Open Access KM Journals Knowledge Management Industry Awards
Table 4. Outreach and Partnership Activity Name Annual KM Surveys Consulting and Advising Development and Collection of Metrics and Stories Funding proposals and opportunities Knowledge Management Mentorships Open Virtual Laboratory
Brief Description Understand Stakeholder Needs, Local and Networked Resources Establish Requirements, Create “People Finder” (e.g., through LinkedIn), Differentiate Types of Consulting the Center Does / Pilots, Develop a Methodology for Matching Stakeholders with Expertise for Consulting Purposes / Services, Identify Tools Repository Performance Plan Examples, Price Points, Provide Strategic Maps and Assistance to Cities and Towns Crowdsourced Solutions, Crowdsourced Funding for KM Research Needs, Short Term Services Mentoring Across Organizations, Mentoring Across Ages Learning Management System, Sandbox Tool – Simulators, Prototypes, “Authoritative” Tools, Customer Relation System, Profile, Access Rights, Track & Trend Analysis, Library of Access to Authoritative KM Content, Ontologies, Analysis, Blogs, Social Media Presence, Tool “Reviews”/ Recommendations
Table 5. Advising Activities Activity Name Broadcasting KS Activities Networking and Public Outreach
Open Meetings Spaces Outreach to Other Disciplines and Economic Sectors Social Media Support for Dynamic Conversations
Activity Examples “News” Source for Innovative KM Practices, KM Blogs, Investigative Reporting, Electronic Calendar of Global KM Events Community Networking, Linking Consultants and Clients, Affinity Grouping within and across Sectors, Networking across City Organizations, Links From Citizens to Thought Leaders, Knowledge Connectors – Linking Those with Problems and Those with Solutions, Knowledge Practitioners Directory Experiments, Brainstorming Sessions, Knowledge Jams, Partnership Outreach and Extension Service Links to Twitter Feeds Related to Knowledge Sciences
The list serves as a catalog of opportunities for any group that wishes to take up the challenge of building a Knowledge Sciences Center. It serves as a tool for prioritizing and implementing activities as relationships with stakeholders develop. Clearly, there are variations in cost, value, duration and sustainability, and lead times.
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Denise A. D. Bedford, John Lewis and Brian Moon The significant number of activities recommended reinforces both the need for and the lack of existing support provided by current players. It is clear that no one organization or institution can fulfill all of these needs. Only through working in a consortium or cooperative environment can a Knowledge Sciences Center meet these needs. Different activities and stakeholders also mean different engagement models. Issue 3: How Do We Engage? The Center’s engagement strategy is complex. Multiple engagement models would be required because different kinds of activities require different ways of working. Multiple models are needed because stakeholders’ interests, environments and resources vary. Participants discussed five possible engagement models, including: (1) Traditional academic R&D model; (2) Agricultural extension service model; (3) Knowledge services corps model similar to that of the Peace Corps; (4) Consortium model; and (5) Business franchise model. The first envisioned model would support applied research that is needed by the community or for which there is no other logical source. This engagement model looks like a traditional academic science center where knowledge resides in the center and is channeled out to the community. Such a model assumes there would be formal contracts in place with funding agencies or organizations, and that all research standards, records and protocols would need to be maintained. In order to support research, access to library resources is also required. The Center would have to work with the university or college to contract for access. The second envisioned model resembles that of an agricultural extension service. This model would support the development of solutions needed by the community, the non-formal learning needs of the community, and technology transfer issues. In this model the Center uses visits to stakeholders as a way of staying in touch with the needs of the local community, gather input to policy formulation, and provide targeted client advice. This engagement model would be a good fit for Learning and Career Development, and Advising activities. The third envisioned model resembles a Knowledge Services Corps – similar to a missionary model or Peace Corps structures where knowledge evangelists engage directly with the community to foster conversations and knowledge transactions while leveraging the Center’s infrastructure and resources. This engagement model might leverage graduate students, students fulfilling practicum or internship requirements, who were supported by community scholarships, or volunteers earning community service or continuing education credits. This model would align well with Outreach and Partnership activities. Tje fourth envisioned model resembles that of a consortium where the Center acts as a cooperative partner with other universities, institutions, and agencies to support activities. This model supports activities that require or benefit from a collaborative environment. This engagement model would be a good fit for Advocacy activities, where the Center would partner with other organizations to move initiatives and standards forward on behalf of the larger community. And a fifth envisioned model – business franchise – was suggested. This was a particularly interesting model because it would allow the Center to reach out into the community through a hub-spoke model, and because it would provide conceptual buy-in and ownership relationships. “Franchise owners” at local libraries or universities or agencies would provide space or connectivity through which stakeholders could engage with the Center. Issue 4: How Do We Fund the Center? As a Knowledge Sciences Center our goal would be to mobilize and promote ideas. As with any such venture, funding will be necessary for sustained effect. Participants were asked to consider what kind of an innovative funding model would support Learning and Career Development, Research and Development, Advocacy, Advising and Networking. The answer to this question was similar to other answers – multi-faceted, dynamic and flexible. Funding models – as engagement models – must be relevant to the activity and to the stakeholders. Learning and Career Development activities may leverage a variety of funding models ranging from entirely open source contributed courses accessible on MOOCs, to no-fee open webinars, to fee-based workshops and on-site training courses, to formal certification or testing services. Advocacy activities would leverage in kind resources, community grants, crowd-funding, or direct sponsorship.
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Denise A. D. Bedford, John Lewis and Brian Moon Research and Development may be funded through grants, research funding awards, and joint sponsored funding. Research may also be supported by in-kind contributions of the members of global expert teams. The model will depend on the nature and intensity of the research. R&D projects that support technology development or evaluation may be sponsored by technology vendors or venture capitalists. Research that has a direct community application may be funded through crowd-sourced or in-kind contributions. The nature of the funding must also take into consideration the intellectual property rights of the products and services. In some cases, established intellectual property provisions will apply. In other cases, creative commons and open source models might be more appropriate. Another funding model would be pay-for-service. This may be appropriate for Advising activities. Again, there would need to be a progressive pricing strategy to ensure that all members of the community can afford to participate in these activities. The lowest pricing option should be an in-kind contribution or a barter system. In-kind contributions strengthen the Center by increasing its stock of knowledge. Where the Center might support in-kind contributions or contributed services, it would be necessary for stakeholders to have access, and the Center to support the idea of a “knowledge bank”. The idea would be that as stakeholders contribute to the Center, they earn intellectual credit that can be applied to future requests. Also proposed was a fee-based membership model.. The challenge with membership models,though, is that they lock and organization into providing predictable and pre-defined services to members. This typically leads to the need to define generic products and services rather than on-demand or stakeholder-focused activities. We have observed that institutions based on memberships over time can become bogged down in the administrative tasks of supporting members. The membership model might also price many community members out of most engagements. The Participants thought that a membership model should be considered only after all other options had been explored. In addition, to having a stock set of funding models, the Center would need to have a robust list of funding sources and opportunities. On-going fundraising relevant to current or planned engagements would be one of the Center’s major operations. Issue 5: What Does the Center Look Like? The Participants were of one mind in recommending both a virtual and a physical preference. The sentiment was that the physical presence should be minimalist and networked to increase visibility. The physical space should ideally be located on a university or college campus to ensure there is easy access to faculty and students, as well as to research protocol support. However, participants suggested that a remote or satellite campus might be more appropriate to ensure that the Center can establish its own innovationoriented, dynamic and community-focused organizational culture. The nature of the space should be open, heavily technology-enabled, with spaces for stakeholders to meet and work. The physical space should feel like an open knowledge sharing environment. As the Center grows, there may be a need for spaces for visiting scholars or short-term team work spaces. Depending on the nature of the stakeholders, their competencies and environments, the physical Center may need to provide access to the Center’s virtual space. We would also expect “Center franchisees” to provide community-based access to the Center. The Center’s virtual structure includes online collaboration environments, access to social media and cloud-based repositories. The Center is also virtually linked to other similar-Centers. The Center’s virtual presence might leverage cutting edge technologies under development or testing by technology developers or vendors. The heavy reliance on virtual access would present both challenges and opportunities. In terms of challenges we would expect that many stakeholders would not have affordable high-bandwidth access. We also expect that digital literacy rates might be low for some stakeholders. This presents opportunities, though, for coaching and mentorships particularly where students and community members contribute training time in exchange for other services.
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3. The Blueprint The participants generated a wealth of ideas and options. While a number of support activities might be consistently supported through stable funding sources, it is clear that many will be ‘designer-oriented’. In other words, a stakeholder engagement and funding design model might need to be put in place for each activity. This is not the way that most organizations work. Thus, the participants agreed that an engagement design model would need to be developed for the Center. The model favored by the participants was an emergent engagement design (Figure 3). The design process would begin with a proposed activity. To ensure that the Center stays true to its goal of facilitating the community or local area’s transition to a knowledge economy, deployment needs to be carefully managed and aligned with demand. The Center would put in place the virtual infrastructure, and engage stakeholders in activities that required low investments but could demonstrate high value. As value is recognized and promoted, stakeholder engagements would expand and build the Center’s reputation.
Stakeholder Competencies Ownership Issues
Stakeholder Environment Engagement Design
Activity Engagement Model
Outputs and Outcomes Funding Options Figure 3. Knowledge Center Activities
4. Observations and Next Steps The purpose of sharing these ideas is to encourage communities around the world to consider starting a Knowledge Sciences Center. We hope that this paper and its presentation at the ECKM-2014 Conference will encourage others to take up the challenge of creating a knowledge sciences center. We hope that others will share their experiences and ideas on the design issues we have raised and the blueprint that emerged from the Symposium discussions. A second Knowledge Sciences Symposium is being planned for 2014 to carry these ideas forward.
References Andriessen, D. (2004). Making sense of intellectual capital: designing a method for the valuation of intangibles. Routledge. Anttiroiko, A. V. (2004). “Science cities: their characteristics and future challenges”, International Journal of Technology Management, 28(3), 395-418. Appold, S.(2003). “Research parks and the location of industrial research laboratories: An analysis of the effectiveness of a policy intervention”, Research Policy 33, 225 – 243. Baqir, M. N., & Kathawala, Y. (2004). “Ba for knowledge cities: a futuristic technology model”, Journal of Knowledge Management, 8(5), 83-95. Bontis, N. (2001). “Assessing knowledge assets: A review of the models used to measure intellectual capital”. International Journal of Management Reviews, 3(1), 41-60. Bontis, N. (2002). National Intellectual Capital Index: Intellectual Capital Development in the Arab Region. United Nations, NY. Bounfour, A. and Edvinsson, L. (2005). Intellectual Capital for Communities: Nations, Regions and Cities, ButterworthHeinemman, Boston. Carrillo, F. J. (2004). “Capital Cities: A Taxonomy of Capital Accounts for Knowledge Cities”, Journal of Knowledge Management, Special Issue on Knowledge-based Development II, Knowledge Cities, 8(5), 28-46. Carrillo, F. J. (2006). Knowledge Cities – Approaches, Experiences, Perspective. Butterworth-Heinemann, 2006.
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Denise A. D. Bedford, John Lewis and Brian Moon Castells, M. (2000), The rise of network society, Blackwell Publishers Castells, M. and Hall, P. (1994). Technopoles of the World: The Making of Twenty-first Century Industrial Complexes. London: Routledge. Chen, S and Choi, C.J. (2004). “Creating a Knowledge-based City: The example of Hsinchu Science Park”, Journal of Knowledge Management, Vol. 8, No. 5, 73 – 82 Dvir, R., & Pasher, E. (2004). “Innovation engines for knowledge cities: an innovation ecology perspective”, Journal of Knowledge Management, 8(5), 16-27. Edvinsson, L. (2006). “Aspects on the city as a knowledge tool”, Journal of Knowledge Management 10(5), 6-13. Ergazakis, E., Ergazakis, K., Metaxiotis, K. and Charalabidis, Y. (2009) “Rethinking the development of successful knowledge cities: an advanced framework”, Journal of Knowledge Management 13(5), 214-227. Ergazakis, K., Metaxiotis, K., Psarras, J. and Askounis, D. (2006). “A unified methodological approach for the development of knowledge cities”, Journal of Knowledge Management 10(5), 65-78 Garcia, B. C. (2006). “Learning conversations: knowledge, meanings and learning networks in Greater Manchester”. Journal of Knowledge Management 10(5), 99-109, Garcia, B.C. (2007). “Working and learning in a knowledge city: a multilevel development framework for knowledge workers”, Journal of Knowledge Management 11(5), 18-30, Goldberg, M., Pasher, E., and Sagi, M. L. (2006). “Citizen participation in decision-making processes: knowledge sharing in knowledge cities” . Journal of Knowledge Management 10(5), 92-98, Goodman, J. C. (2005). What is a Think Tank? National Center for Policy Analysis. Haughton, G. and Hunter, C. (2003), Sustainable Cities, Routledge. Kratke, S. (2011). The Creative Capital of Cities: Interactive Knowledge Creation and the Urbanization Economies of Innovation. Blackwell, 2011 Matthiessen, C. W., Schwarz, A. W. and Find, S. (2006). “World cities of knowledge: research strength, networks and nodality”, Journal of Knowledge Management 10(5), 14-25, Mendizabal, E. (2010). on the business model and how this affects what think tanks do, http://onthinktanks.org/2010/10/03/on-the-business-model/ Retrieved 2011-11-02. Metaxiotis, K. and Ergazakis, K. (2008). “Exploring stakeholder knowledge partnerships in a knowledge city: a conceptual model”. Journal of Knowledge Management 12(5), 137-150, O’Mara, M. P. (2005). Cities of Knowledge: Cold War Science and the Search for the Next Silicon Valley. Princeton University Press, 2005. Ovalle, M., Barquez, J. A. A., and Salomon, S. D. M. (2004). “A compilation of resources on knowledge cities and knowledge-based development”. Journal of Knowledge Management. 8(6), 107-127. Papalambros, Panos Y. (2011). "A New Knowledge Ecosystem." Journal of Mechanical Design 133.perspective’’, Journal of Knowledge Management, 8(5), 16-27. Peters, M. A. (2007). Knowledge economy, development and the future of higher education. Rotterdam: Sense Publishers. Rodriguez, C. O. (2012). “MOOCs and the AI-Stanford Like Courses: Two Successful and Distinct Course Formats for Massive Open Online Courses”. European Journal of Open, Distance and E-Learning. van Winden, W., de Carvalho, L., van Tuijl, E. and van Haaren, J. (2012). Creating Knowledge Locations in Cities: Innovation and Integration Challenges. Routledge. Vardi, M. Y. (2012). “Will MOOCs destroy academia?” Communications of the ACM, 55(11), 5.
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Developing an Interactive View on Intra‐Organisational Knowledge Sharing Madeleine Block1 and Tatiana Khvatova² 1 Saint‐Petersburg State University, Saint‐Petersburg, Russia ²Saint‐Petersburg State Polytechnic University, Russia
[email protected] tatiana‐
[email protected] Abstract: Management of knowledge within organisations is supposed to foster innovative solutions and enhance competitive advantage. Knowledge is held by, and found within individuals, groups and their interrelations. A key part of knowledge management is having an understanding of the knowledge and information flow among people, groups and the organisation as a whole. Such insight enables intervention and fostering of effective knowledge sharing processes. However, in order to understand the knowledge flow and interrelations among organisational actors, we must first identify which patterns exist, and what the real paths are within organisations. In this article, the social network approach is applied to organisational settings and used as research methodology for gaining insight into the intra‐organisational knowledge sharing process. The overall aim of this research is to investigate how potential actors within a specific network can be identified and interlinked in order to support effective knowledge sharing and collaboration. In this research, the extent of relationships between organisational actors is central. As such, we view the concept of social capital with the central proposition that networks of social relationships constitute a valuable resource for the conduct of social interaction. From these findings, this research taes a step back, and seeks to identify and analyse information and knowledge flow among organisational actors. Here, social network analysis enters on stage, in order to map and analyse the actual state of the knowledge sharing network within organisations. In the next step, we refer to the contingency theory of organisations in arguing that the certainty degree of a task has a great impact on the organisational structure. Accordingly, in organisations where a higher task certainty is given, employees have little need and choice of creating work‐related interactions beyond the static structure which is displayed in the formal organisational chart. Today´s fast, internationally connected environment inevitably increases the complexity of tasks within organisations which cannot be pre‐described. In this way, employees may build up informal networks in order to accomplish their tasks, and the organisational structures become more organic and self‐organised. In this research, we discuss this circumstance and perform a comparative view of the informal networks and the formal organisational chart. As such, the research provides a case study, exploring intra‐organisational knowledge sharing among financial departments of an international industry company. The study is based on a questionnaire which evaluates the extent of interrelation between financial departments according to employees’ self‐reported opinions. Empirical data was collected through an email survey distributed to the financial departments, involving ten leaders and 97 specialists. For analysis of the collected data, statistical quantitative analysis and for visualisation of the knowledge network, social network analysis software were used as research techniques. Keywords: knowledge sharing; organisation; social network approach; empirical research
1. The concept of social capital as a theoretical umbrella The interactive approach chosen in this article refers to the most common notion in social sciences, which is that individuals cannot act separately from each other, but instead they are interrelated and interactively connected. This is why knowledge sharing does not occur automatically, but takes place within social interactions perceived as beneficial by the participants. At this stage, the concept of social capital helps to gain a better understanding of knowledge sharing within cooperative relationships, such as among individuals and departments within organisations. The term `social capital´ has been made well‐known by such writers as Pierre Bourdieu (1986), James Samuel Coleman (1990), and Robert David Putnam (1993), among others. Nowadays, scholars generally agree that the core notion of social capital theory is that `networks of relationships constitute a valuable resource for the conduct of social affairs´ (Nahapiet and Ghoshal 1998, p. 243). In other words, social capital is an investment in social relationships with expected outcomes in the short or long term (Block 2013, p. 99, 133). Regarding intra‐organisational knowledge sharing, we refer to Nahapiet and Ghoshal (1998), who applied social capital theory to the intra‐organisational context, while the first empirical study was conducted by Tsai and Ghoshal (1998). Based on Bourdieu and Putnam´s elements of social capital, Nahapiet and Ghoshal (1998, p. 243‐244) propose three social capital dimensions: a structural dimension, cognitive dimension and relational
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Madeleine Block and Tatiana Khvatova dimension (Block 2013, pp. 111, 133). In this article the focus is on the structural dimension. While the relational dimension of social capital represents the affective side of relationships and the cognitive dimension relates to a shared context and understanding among participants, the structural dimension refers to social relations and structures that are considered as an important source of social capital. Social structures reflect a normative integration mechanism, enacted by the organisation, and which acts as a kind of `social control´. On the other hand, structural dimension refers to the patterns of connections among involved actors which are closely interlinked with the social network theory. In this study, social structures within organisations constitute the channels for knowledge sharing, providing actors with opportunities to access the resources of others, such as knowledge, and to share their own knowledge (Block 2013, p. 113; Tsai and Ghoshal 1998, p. 252).
2. Understanding the actual state of intra‐organisational knowledge sharing interactions In the social sciences arena, the structural dimension of social capital, which is founded on research into social interactions, has particularly been the focus of social network researchers. They seek to identify various kinds of patterns, and to visualise these, their theory being that the pattering of social relations inevitably has consequences for the participants (Freemann 2004, p.2). Referring to the social network theory, this study aims to explain and visualise the knowledge sharing relationships among actors within an organisation. Since the 1930s, modern social network theory has been present and employed in social sciences. However, as a recognised perspective it finally appeared only in the late 1970s, represented by such scientists as Russell Bernard, Lawrence Kincaid, and Nan Lin. In general, social network researchers explain individual behaviour not as a function of characteristics of the same individual, but rather by aspects of the individual´s social environment (Borgatti et al. 2009, p. 894). The focal point of the Social Network Analysis (SNA) is the relationships between actors, based on an assumption of the importance of the way actors are related to each other within the network (Richards, Seary and Fraser 2008, pp. 1‐3). In SNA terminology a network is a set of relations between actors, while actors represent nodes in the network and are defined as the smallest units in the network, or rather known as actors which or who contain and pass information. The tie is defined as a connection between two nodes, meaning that there is some passing of information between them (Giuffre 2013, pp. 12‐13; Hanneman and Riddle 2005, 1st Chapter). SNA has been applied in various research fields. For example, in management studies there have been attempts to apply the SNA in the field of knowledge management to help organisations improve sharing and make use of the knowledge held by individuals, groups and the organisation as a whole. Yet this is far from being complete. In this context, this study interlinks and aims to explore knowledge sharing paths within organisations with the help of the SNA. For this purpose, we refer to a case study conducted among ten financial departments of an international industry company. These financial departments are classified into four main units. Table 1 shows the distribution of units and departments, the number of employees within participating financial departments and the total number of respondents to the survey. Table 1: Distribution of financial departments and classification of survey respondents Unit and department Employees Respondents Percentage Unit 1: Accounts Receivable (AR) Accounts Receivable Northern Europe (AR NE) 12 7 58,33% Accounts Receivable Western Europe (AR WE) 5 4 80,00% Accounts Receivable Central Europe (AR CE) 10 8 80,00% Accounts Receivable UK and North America (AR UK/NA) 2 2 100,00% 15 9 60,00% Unit 2: Accounts Payable (AP) 14 8 57,14% Unit 3: Cash Management (CM) Unit 4: Purchase Invoice Handling (PI) Purchase Invoice Handling Northern Europe (PI NE) 23 8 34,78% Purchase Invoice Handling Western Europe (PI WE) 10 6 60,00% Purchase Invoice Handling Central Europe (PI CE) 14 6 42,86% Purchase Invoice Handling UK and North America (PI UK/NA) 2 1 50,00% Total 107 59 55,14%
The data for the SNA of the knowledge sharing interaction ties were collected from two questions of the survey. The following questions were asked:
`Could you please identify the department where you work?`;
`Could you please identify the department(s) you contact for task‐related issues?`.
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Madeleine Block and Tatiana Khvatova Answers to both questions were submitted by the 59 employees of the ten departments. During analysis of the network, two matrices were composed: a) person‐by‐department network and b) department‐by‐ department network. Absence of ties between individuals and departments were coded as zero, and presence of ties with one. Network analysis was done using UCINET (Borgatti et al. 2002) and NetDraw programmes (Borgatti 2002). In order to map the actual state of the knowledge sharing network of the financial departments, we refer to attributes such as centrality and network size. The latter feature provides important insights about the network structure of relations, i.e. as larger the network is, the more complex is the network. The proportion of all possible relationships in the network that are actually present equates to the measure of network density informing us about the speed at which knowledge is spread among the actors. A relatively high density network enables the development of a form of collective identity, and is more likely to be more effective for collective action such as knowledge sharing. In this paper, we argue that (task‐related) knowledge sharing is more likely to happen in a network where the density of ties among the individuals is relatively high, yet not too strong. Centrality can be defined as the extent to which an actor has a central, favourable or less favourable position in the whole network. In this study, we look at two measures of centrality (Kilduff and Tsai 2005, p. 132): degree centrality and closeness centrality. The measure of degree centrality expresses the number of direct relations a node has in the network. Usually it is assumed that the more ties a node has, the more power s/he will get through more opportunities and less dependencies. The degree centrality is assessed with the help of the number of ties sent (out‐degree) indicating influence on others; and the number of ties received (in‐ degree) showing the node´s popularity within the network. While centrality degree does not consider indirect ties to a third node, closeness centrality refers to indirect relations and the ability of an actor to reach many others, i.e. how close, on average, an actor is to every other actor within the network. It is assumed that the closer a node to all other in the network is, the more favourable is his/her position. The shortest path between any two network participants is called `geodesic´ and reflects often the most efficient relation between nodes. A small geodesic length, on average, indicates a relatively close position to others within the network, while a large average geodesic length reflects relatively distant relations to the rest of the network. Person‐by‐department network Figure 1 shows the person‐by‐department sociogram, wherein nodes and ties of the network among the 59 employees allocated to the ten financial departments are presented. The strength of the knowledge sharing process is represented for individuals by the number of ties, and for departments by the size of the symbol – the bigger the size, the larger its central position. The arrow states the direction: from a person to a department.
Figure 1: Person‐by‐department network
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Madeleine Block and Tatiana Khvatova The network shown in Figure 1 consists of 207 actual existing relations, which equates to a network density rate of 4.4%. The small network density confirms that a network in larger size becomes more complex in which connecting to everyone else becomes increasingly difficult. Further results of the analysis indicate that the number of departments contacted by each employee ranges from 0 to 7 out of 9 possible departments. For example, node numbers 1 and 30 are in contact with 7 departments along with their own, and node number 25 with 3 other departments. Only two nodes out of 59 have no ties to any department, i.e. they do not contact other departments for task‐related issues. So, this map of relationships shows that almost every person is somehow involved in the knowledge sharing process. Regarding the departments, the results show a strong central position of two departments called `AP´ and `CM´. These are the most involved and requested of all. On the other hand, the `AR UK/NA´ and `PI UK/NA´ departments take only a marginal central position in this network. Department‐by‐department network The department‐by‐department sociogram of the ten departments is displayed in Figure 2. It can be observed that every department is part of the knowledge sharing process by being connected through a tie. The calculated network density with 65.60% is clearly higher than for the larger person‐department network. It means that sharing of information and knowledge is more likely to happen among the ten departments. Similarly to Figure 1, the layout of the sociogram is aligned with the attribute of centrality, and shows the central position of both `AP´ and `CM´ departments.
Figure 2: Department‐by‐department network Due to the symmetric data of the department‐by‐department network, it is possible to calculate the degree centrality for each node. The results in Figure 3 show the in‐degree and out‐degree of each node whereas the first two columns represent the actual number, and the third and fourth column the standardised value. For example, the `CM´ department is most actively in contacts with other departments – all nine possible. On the other hand, `AP´ is the department most requested by all the other departments. It means that both departments keep a central position in this network. At the other extreme, the `PI UK/NA´ department contacts other departments the least often (2 out of 9 possible), while the `AR UK/NA´ department is least contacted by others (contacted by only 3).
Figure 3: Centrality degree for department‐by‐department network
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Madeleine Block and Tatiana Khvatova The square symmetric matrix of the department‐by‐department network further allows for investigation into the interactions between each pair of departments and thus, for measuring the closeness centrality. Figure 4 represents a matrix of geodesic distances between two departments (row‐column crossing).
Figure 4: Matrix of geodesic distances for department‐by‐department network The geodesic distance between two departments is the path with the shortest length. For example, looking at the interaction between the row `PI NE´ and column 3 (AR CE), we see a `2´. This means that `PI NE´ and `AR CE´ are indirectly related by just one intermediator, which produces two edges. The table shows that the `PI UK/NA´ department has, on average, the longest paths with other departments, while department CM is directly interconnected with everyone. The average geodesic among reachable pairs is 1.356. In general, the relatively small geodesic length indicates a relatively close relation from one department to the rest of the network.
3. Studying congruence between knowledge flow and knowledge sharing performance In the above‐described part of the research, the question was how to map the actual state of knowledge sharing relations. Hereafter, the actual level of knowledge flow is centred and is compared with the existing organisational chart in order to predict the knowledge sharing performance. It is presumed that if the task is certain, it will fit to more rigid organisational structure, because employees will not need to actively search for knowledge sharing partners; it is sufficient to follow what is prescribed by organisational instructions. However, reality shows that this framework works until such time as some turbulence occurs in the environment and task certainty disappears, increasing a misfit between actual employee behaviour and organisational structure. This means that organisational structure should be modified in order to come closer to fit, i.e. to adapt to environmental contingencies. In this context, we refer to the contingency theory of organisational structure with the underlying assumption that there is no one best way to organise, and that the selected way to organise cannot be effective under all conditions as conditions constantly change (Galbraith 1973, p.2). In other words, organisational design is arguably most effective when the structure of an organisation fits the contingencies. The contingency theory sees organisations as adapting to their changing (internal) environmental contingencies in order to regain higher performance. As shown in Figure 5, higher performance leads to increasing contingency variables such as a surplus of resources and to a growth in size or diversification causing misfit with the existing organisational structure. In turn, a misfit engenders lower performance and encourages the organisation towards another structural change, so a move from misfit to another fit, and so on (Donaldson 2001, p. 20).
Figure 5: Cycle of structural misfit‐fit‐relationship
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Madeleine Block and Tatiana Khvatova Particular for the intra‐organisational contingency perspective, to which we refer in this paper, is that managers can control the organisational structure and its changes. Therefore, they will only change structures to another fit if it generates higher performance than the old fit (Donaldson 2001, p. 26). With regard to knowledge sharing performance, the following questions are addressed: does the formal organisational structure reflect the real task‐related knowledge flow? What kind of model could describe the knowledge sharing performance? Does the knowledge sharing performance depend on the organisational structure? Furthermore, the identification of fits and misfits offers guidance to managers about what the organisational design may adapt to. The literature review of organisational research on the relationship between tasks and organisational structure provides several studies. For example, in the research by Van de Ven and Delbecq (1974, p. 183) it is stated that appropriate organisational structure depends on both task difficulty and task variability. In the article by Becerra‐Fernandez and Sabherwal (2001, p. 29‐30), it is argued that two task dimensions (task orientation and task domain) require different types of organisational knowledge which implies that different knowledge management processes are required. Lawrence and Lorsch (1967, p. 7) suggested that if a group is created to perform more certain tasks, it will usually have a more formal structure than a group performing more uncertain tasks. Therefore, they believed that the design of an organisation and its effectiveness are contingent upon environmental variables. By applying the contingency theory to intra‐organisational knowledge sharing, we take up the relationship between fit or rather misfit of the formal organisational structure and the actual knowledge sharing behaviour predicting knowledge sharing performance. We argue that knowledge sharing performance depends on the contingencies under which it takes place, i.e. it is affected by the context, for example, by uncertainty versus certainty of tasks. Mathematically it is more convenient to validate the contingency theory through the misfit‐ performance‐relationship. Fit occurs where the level of formal structure matches the level of actual structure. Accordingly, misfit (M) is where the formal structure (X) differs from the contingency variable of actual . Conventionally, the misfit‐performance‐relationship is done by knowledge sharing behaviour (Y): using the difference score method which determines the performance (Z) as a result of the difference scores (X‐Y) representing congruence between the two states of organisational variables – formal and actual . This demonstrates that the bigger misfit is, the lower the knowledge sharing behaviour: performance will be. Edwards and Parry (1993) suggested expanding the equation and viewing the equation as polynomial regression for assessing the influence of misfit on performance. They propose to use the squared terms of the differences and its expansion which results in the following equation (Edwards and Parry 1993, p. 1579): ,
where X is the structural variable, Y the contingency variable, and Z the performance. The use of the polynomial regression equation has two methodological advantages: at first, squared term means avoiding problems with negative values of misfits occurring through difference scores; secondly the polynomial regression overcomes the collinearity problem of the X and Y variables (Edwards and Parry 1993, pp. 1578‐1579). Finally, polynomial models describe not only the influence of factors, but also their interactions including the polynomial higher order terms to show that some effects indeed arise due to them (Eliseeva 2005, p. 116). However, coefficients from quadratic equations are more difficult to interpret. Therefore, similar to Edwards and Parry (1993) we use the response surface methodology in order to describe and verify the important features of surfaces corresponding to the polynomial regression equation. Regarding the present case study, the performance of knowledge sharing – abbreviated by Z – is predicted by the relationship between the contingency variable (Y) and the structural variable (X). For the latter variable X – the formal knowledge sharing behaviour represented by the organisational chart was quantified according to from whom employees are supposed to obtain knowledge. In Figure 6 the organisational chart representing the financial departments shows not only the managerial hierarchy but rather a process‐oriented structure and their task‐related connectivity.
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Figure 6: Formal organisational chart The organisational chart suggests the strict rule about communication for each department. For example, it is prescribed that to do the job, the ARNE employee should contact at first her/his colleagues from ARNE, the neighbouring department, then the other two departments from their own group, plus outside the AP and CM department, while the communication to the PI departments are the last in the chain. According to the prescribed formal task‐related communication paths points were given with a maximum of five and summarised for each department. For the contingency variable (Y) we take the actual knowledge flow which is characterised by the desire of employees to address colleagues from other departments for advice. Based on the data resulting from the addressed question: `Could you please identify the department(s) you contact for task‐related issues?`, ten scenarios for different groups were reconstructed and quantified. The desire to communicate was measured by looking at the organisational chart – the farther an employee goes and the more unconventional the path they choose to acquire knowledge, the more points s/he gets (maximum five). The chi‐square test was conducted to test the misfit between the formal knowledge flow (X) and the actual knowledge flow (Y), i.e. . The misfit exists ( ²=153.91, degrees of freedom=51, significant at the 0.05 level) and it is essential. The underlying questions for analysis of the knowledge sharing performance (Z) among financial departments (see Table 1 and Figure 6) are:
`Could you please indicate the frequency with which other departments provide you with information and knowledge required for you to do your work?`;
`Could you please indicate the value of the information and knowledge which other departments provide you with in order for you to do your work?`;
The questions were graded on five‐point Likert‐type scales and the consistency of the questions for the variables was tested using Cronbach alphas, which were 0.95 and 0.83 respectively for every corresponding part of the questionnaire, which shows perfect consistency of the constructs. ) is measured as a weighted sum of the
The level of knowledge sharing performance for every person (
number of times (question a) knowledge is provided by another department ( of knowledge value (question b) that the exchange brought (
) multiplied by the indicator
):
,
where is the number of departments a person i addressed. Afterwards, the average mean of knowledge sharing performance (Z) was calculated for every department. There were some missing items in responses. Following listwise deletion, 52 out of 59 respondents were used in the analysis, a 55.14% response level. The
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Madeleine Block and Tatiana Khvatova response rates differed across groups (see Table 1); however, overall differences were not significant at 0.05 level. As a result, the performance of knowledge sharing among the financial departments equates to the . The following regression model: coefficients of the polynomial regression equation are represented in Table 2 and the hypothetical surface is shown in Figure 7. Table 2: Coefficients for the polynomial regression equation Equation
N was 52;
…
16.092*
‐0.461
0.238*
0.008*
‐0.022
0.013
R²
F‐test
0.155*
1.686*
are unstandardised regression coefficients.
* means significance at p
