In: International Journal of Production Research, Volume 51, Issue 7, 2013, pp 1953-1957.
“Knowledge Management and Supporting Tools for Collaborative Networks” A. K. Choudhary, J. A. Harding, L. M. Camarinha-Matos, S. C. L. Koh and M. K. Tiwari Recent organizational trends show an increase in the formation of collaborative networks (CNs) to improve competitive advantage, and provide world class excellence and flexibility to address dynamic and turbulent market conditions. Collaboration of various forms can increase profits by improving chances to capture valuable business opportunities, address market demands and share resources and competences in very competitive and rapidly changing environments. CNs can take a variety of forms varying from highly integrated and dynamic supply chains, extended and virtual enterprises, virtual organizations, collaborative virtual laboratories, professional virtual communities, virtual organizations breeding environments and collaboration pools. A major reason for collaboration is to exploit the core competencies of all the enterprises concerned, to form strategic alliances and enhance competitiveness by integrating value added activities, information, resources and knowledge between enterprises. These benefits are enabled by the advances in ICT based infrastructure and services. For more than a decade, the European Commission has been funding several projects in the area of ICT tools, techniques, methods and infrastructures for CNs. Currently, enterprises are adopting advanced ICT solutions for gathering, storing, organising, and accessing enterprise knowledge easily. In the era of the knowledge economy and knowledge-based competition, an efficient and adaptive CN must be able to secure various types of knowledge assets and maximize their strategic values. Effective knowledge management within a CN is core to its success. To enhance the activities of a networked enterprise in successful, timely creation of, and participation in, a CN, tools, techniques and processes are needed to capture, share, reuse and apply various types of knowledge relevant to the various stages of the collaboration lifecycle. Several authors have highlighted the need for developing knowledge management systems to integrate the information which must be exchanged or shared between the network partners and external knowledge they require on a common platform. Effective knowledge management is essential to improve the productivity and the quality of decisions taken by the member organisations. A critical aspect of effective knowledge management within CNs is the identification and capture of the most appropriate knowledge for reuse or exploitation in a particular context combined with the most efficient tools and mechanisms for its identification, sharing or transfer. With these capabilities, an enterprise can improve its decision making ability and capacity to withstand systemic discontinuities and can adapt to new risk environments. The enterprise can also effectively align its strategy, operations, management systems and decision support capability so that it can uncover and adjust to continually changing risks, endure disruptions to primary earning drivers and create advantage over less adaptive competitors. In addition, particularly because of the high importance of SMEs within such collaborative networks, this knowledge must be readily available through services, tools and technologies which are user-centric, interoperable, reliable and affordable. Therefore, knowledge based tools, methods, infrastructures and services are needed to achieve effective collaboration in a CN. Bearing in mind all these challenges and aspirations, this special issue mainly focused on gathering the state-of-the-art in research and technology for knowledge management and supporting tools, methods and services for Collaborative Networks. In addition, this special issue also identified and reported several future research directions, interesting topics and challenges. This special issue received a very strong interest from researchers working in the area of knowledge management and supporting tools, methods and services for Collaborative Networks. We have received 60 papers from researchers and practitioners located in different part of the world. After several rounds of peer review by 2-3 reviewers, 17 papers are selected for publication in this special issue. These 17 papers address and exemplify a variety of related aspects in developing knowledge management based methods, tools, techniques and systems to support various kinds of collaborative networks. Various
aspects of knowledge management issues have been discussed in a range of areas including integration in collaborative supply chains, decision models for SMEs CNs, buyer suppler collaboration, patent in design collaboration, collaborative commerce adoption, reference framework for CN, Collaborative tools for SMEs, new product development, supply chain control logic, decarbonizing product supply chains, customized production in SMEs, collaborative decision making, competence modelling for VOs, flexible supply networks, high value manufacturing and a collaborative approach for supply chain operational risk mitigation. A short description of each article is discussed as follows: The first article of this issue “A holistic view of knowledge integration in collaborative supply chains” by Jayaram and Pathak (2013), discusses a knowledge integration mechanism in collaborative supply chains. They propose two different types of mechanisms within a collaborative supply chain; shortterm knowledge sharing and iterative knowledge enrichment. They use data from a large and diverse set of 432 NPD projects, and investigate the effects of knowledge sharing and enrichment between firms and their collaborative network partners, on product concept effectiveness and process performance. Their findings suggest that knowledge sharing and enrichment are significant mechanisms for enterprise-wide knowledge integration in collaborative networks. In addition, upstream knowledge sharing and enrichment has a significant influence on both product concept effectiveness and manufacturing process performance, over and above the effects of downstream knowledge sharing and enrichment. The second article by Renna (2013), “Decision model to support the SMEs’ decision to participate or leave a collaborative network” proposes a decision model to support enterprises in their decisions to participate in or exit from a network of enterprises. The model is based on the definition of a set of rules that operate with local information to take the decisions and integrates the collaboration methodology and the decision model. This environment is related to independent plants that cooperate with reduced information sharing. A simulation environment is developed to test the proposed approach and the simulation results showed that the proposed approach is a very promising tool to support the enterprise's participation decisions in a collaborative network. The article “Harnessing value in knowledge management for performance in buyer–supplier collaboration” by Yang (2013), investigates how different knowledge-management processes (i.e. knowledge acquisition and dissemination) affect the manufacturers’ performance in collaborative economic exchanges with their suppliers. Drawing upon the knowledge based view and transaction cost economics, this article proposes that knowledge-management processes are positively related to the performance of the manufacturers in a collaborative buyer–supplier relationship. It also proposes that this link is stronger when the levels of supply-chain integration and relational stability are higher rather than lower. The next article “Ontology-based neural network for patent knowledge management in design collaboration” by Trappey et al. (2013), discusses and proposes a novel knowledge management approach using an ontology-based artificial neural network (ANN) algorithm to automatically classify and search knowledge documents stored in huge online patent corpuses. They focus on developing a smart and semantic oriented classification and search from the sources of the most critical and wellstructured knowledge publications namely patents, to gain valuable and practical references for the collaborative networks of technology-centric product and production development teams. This research provides an advanced semantic-oriented search algorithm to accurately identify related patent documents in the patent knowledge base. The results are compared with the previous automatic classification methods and outperformed earlier methods. The article “Do interorganisational relationships and knowledge-management practices enhance collaborative commerce adoption?” by Chong et al. (2013) aims to investigate the contributions of interorganisational relationships and knowledge-management practices as predictors of collaborative commerce (c-commerce) adoption. A survey was undertaken in 136 firms for this research and a noncompensatory adoption decision process was modeled using a neural network approach to examine the
predictors of c-commerce adoption. The results show that both interorganisational relationships and knowledge-management processes played an important role in predicting the adoption of c-commerce. The findings lead to an understanding of what attributes of interorganisational relationships and knowledge-management processes can contribute to the improved adoption of c-commerce in the supply chain. The next article “The application of a knowledge-based reference framework to support the provision of requisite variety and customisation across collaborative networks” by Lyons et al. (2013) concerns the discussion and application of a knowledge-based reference framework to demonstrate how product variety and customization can be supported across different forms of collaborative customer–supplier networks. In addition, explanations are provided on how collaborative networks can be classified, on how their adaptive capabilities can be established, and on the characteristics and attributes that particular types of network require in order to handle their commitment to the provision of variety and customization. The article “Collaboration networks and collaboration tools: a match for SMEs?” by Michaelides et al. (2013) discusses the role of the Internet as an enabling technology for virtual collaboration networks of SMEs for problem-solving and innovative idea-exchange. This research seeks to examine how informal interactions are facilitated in SMEs through Web 2.0 tools. They examine how Web 2.0 affects the collaborative effort in two SME CNs; this study demonstrated that the collaboration effort is amplified when Web 2.0 tools are available. Other parameters such as trust in other members’ ability; perception of usefulness; and enhancement of collective knowledge are seen as supporting the mutual relationship of CNs. In addition, it brings together the three diverse research areas of collaborative networks, internet collaborative tools and psychological barriers and enablers. The next article “A collaborative framework to minimise knowledge loss in new product development” by Shankar et al. (2013) highlights that in rapidly changing dynamic and multi-layered environments, recognizing, managing and preventing knowledge loss can be a key determinant of success of an organization. This research argues for a collaborative network structure within the organization to prevent knowledge loss in new product development. They developed an in-depth case study of six Indian auto-component manufacturing companies to identify the sources of K-loss. Based on their observation and case study, this article recommends ways to create collaboration pools that increase flow of information and communication and help mitigate knowledge loss throughout the value chain. This article also summarizes the researchers’ findings as usable rules-of-thumb for helping senior and middle-level managers develop and leverage collaborative networks for effectively managing knowledge loss for their organizations. The next article “Knowledge sharing in collaborative supply chains: twin effects of trust and power” by Cai et al. (2013) discusses the mechanisms underpinning knowledge sharing in supply chains specifically knowledge sharing in a dyadic buyer–supplier relationship. This research highlights that trust and power are two important antecedents of two types of knowledge sharing between a buyer and supplier, namely technical exchange and technology transfer. This research uses a large-scale survey conducted from a contact list of 800 companies provided by the Singapore Logistics Association for case design. The structural equation modelling was used to derive results which suggest that trust has significant effects on technical exchange and technology transfer. Further, power also affects technical exchange and technology transfer significantly, though the impacts appear to be weaker than trust. The next article “Web-services-based supply-chain-control logic: an automotive case study” by Makris and Chryssolouris (2013), discusses the design and implementation of a decision-support software system based on web services, capable of modelling the supply chain and querying the supply-chain partners to provide information, regarding the availability of parts, required for the production of a highly customizable product. They also demonstrated the feasibility of implementing this approach in a typical automotive case study.
The article “Decarbonising product supply chains: design and development of an integrated evidencebased decision support system – the supply chain environmental analysis tool (SCEnAT)” by Koh et al. (2013) proposes a state-of-the-art decision support system (DSS) for carbon emissions accounting and management, mainly across the product supply chains by identifying methodological shortcomings in existing tools, and establishes a supply chain (SC) framework which provides businesses with a holistic understanding of their supply chains and ensures that partners within supply chain collaborative networks have a shared understanding of their emissions. It describes the design and development of a DSS now known as supply chain environmental analysis tool (SCEnAT) in detail. The methodological framework used to design and develop SCEnAT integrates different individual techniques/methods of supply chain (SC) mapping, SC carbon accounting, SC interventions and SC interventions evaluation on a range of key performance indicators (KPIs). Finally, it also demonstrates the application of SCEnAT, especially the advantage of using a robust carbon accounting methodology, to a SC case study. Fornasiero and Zangiacomi (2013), in the next article “A structured approach for customised production in SME collaborative networks” aim to provide a reference model depicting its structure and the related tools for collaborative networks model for SMEs to address needs and expectations of specific target groups – such as elderly, obese, disabled, or diabetic people – to customise functional and fashionable clothes and footwear of high quality, affordable price and eco-compatible. They aim to develop a new framework for the textile, clothing and footwear industry (TCFI) based on methods and tools for (co) design, development, configuration, production, and distribution of small order quantities in collaborative networks. In the next article “A decision-focused knowledge management framework to support collaborative decision making for lean supply chain management”, Liu et al. (2013) identify efficient knowledge management as one of the key requirements to achieve integrated support for lean supply chain decisions. This research proposes a decision-focused knowledge framework including a multi-layer knowledge model (to capture the know-why and know-with together with the know-what and knowhow), a knowledge matrix for knowledge elicitation, and a decision tree for the design of the knowledge base. A knowledge system for lean supply chain management (KSLSCM) has been developed using artificial intelligence system shells VisiRule and Flex. The knowledge framework and the KSLSCM have been evaluated through an industrial decision case. It has been demonstrated through the KSLSCM that the decision-focused knowledge framework can provide efficient and effective support for collaborative decision making in supply chain waste elimination. Cheikhrouhou et al. (2013) in the next article “Modelling competence-based virtual organisations using the unified enterprise competence modelling language” introduce the principles for modelling competence-based virtual organisations by using a unified enterprise competence modelling language (UECML). Their proposed modelling approach and associated language provides a neutral interface to virtual organisation modelling based on competences, taking into account the several roles and entities participating in a virtual organisation. Therefore, providing constructs covering processes, resources, competences, and virtual organisation (VO) entities. A case study of the Swiss virtual organizations breeding environment Virtuelle Fabrik with regards to the project Abfallhai is presented and discussed, showing how the developed modelling language is adapted to model virtual organisations. Smirnov et al.(2013) in the next article “Dynamic configuration of flexible supply networks(FSNs) based on semantic service composition" propose a novel approach to dynamic network members’ discovery and selection based on competence profiles included in provided service descriptions. The approach is based on the idea of characterising all FSN members by their functions or services and describing them via profiles thus defining their roles. The profiles described by the application ontology are associated with agent-based services that negotiate to take into account explicit and tacit preferences of the enterprises, in order to dynamically configure a collaborative network on demand.
In the next article “A dynamic knowledge management framework for the high value manufacturing industry”, Piorkowski et al. (2013) describe a dynamic KM framework in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company's (BAE Systems) project stakeholders. The framework has been designed to support organizational learning and to reward employees at the start of the product lifecycle in order to improve the position of the company in the market place. Finally, the last article “Supply chain operational risk mitigation: a collaborative approach” by Chen et al. (2013) examines three types of risks, namely supply risk, demand risk and process risk in relation to three types of collaboration, namely supplier collaboration, customer collaboration and internal collaboration, as a mechanism to mitigate those risks. The proposed relationship model is tested with data collected from 203 manufacturing companies in Australia. The results show that each area of collaboration effectively reduces its respective supply chain risk, but only the mitigation of process risk and demand risk has a direct effect on supply chain performance. In addition, both supply risk and demand risk increase process risk. In summary, this special issue has collected research contributions from across the world from researchers and practitioners working in the area of knowledge management and supporting methods for collaborative networks. We are thankful to all the authors and the referees for their contribution to enhance the quality of the articles in this special issue. Special thanks go to the past Editor in Chief, J. E. Middle and to the current Editor-In-Chief, Prof. A. Dolgui for this opportunity and contribution in managing this special issue. Guest Editors of Special Issue: •
Dr. Alok K Choudhary, Logistics and Supply Chain Management Research Centre, Management School, The University of Sheffield, United Kingdom Email:
[email protected]
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Prof. Jenny Harding, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, United Kingdon, Email:
[email protected]
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Prof. Luis M. Camarinha-Matos, Faculty of Sciences and Technology, New University of Lisbon, Lisbon, Portugal, Email:
[email protected]
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Prof. S. C. Lenny Koh, Logistics and Supply Chain Management Research Centre, Management School, The University of Sheffield, United Kingdom Email:
[email protected]
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Prof. Manoj K Tiwari, Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur, West Bengal, India, Email:
[email protected]
References:
Cai, S., and Goh, M., De Souza, R., and Li, G. "Knowledge sharing in collaborative supply chains: twin effects of trust and power" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Cheikhrouhou, N., and Tawil, A. H. and Choudhary, A., "Modelling competence-based virtual organisations using the unified enterprise competence modelling language", International Journal of Production Research, volume xx, number yy, 2013, pages aa. Chen, J., Sohal, A. S., and Prajogo, D., "Supply chain operational risk mitigation: a collaborative approach", International Journal of Production Research, volume xx, number yy, 2013, pages aa.
Chong, A. Yee-Loong, Chan, F.T.S., Goh, M., and Tiwari, M.K., "Do interorganisational relationships and knowledge-management practices enhance collaborative commerce adoption?" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Fornasiero, R., and Zangiacomi, A., "A structured approach for customised production in SME collaborative networks" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Jayaram, J., and Pathak, S., "A holistic view of knowledge integration in collaborative supply chains", International Journal of Production Research, volume xx, number yy, 2013, pages aa. Koh, S.C. L., Genovese, A., Acquaye, A., Barratt, P., Rana, N., Kuylenstierna, J., and Gibbs, D., "Decarbonising product supply chains: design and development of an integrated evidence-based decision support system – the supply chain environmental analysis tool (SCEnAT)", International Journal of Production Research, volume xx, number yy, 2013, pages aa. Liu, S., Leat, M., Moizer, J., Megicks, P., and Kasturiratne, D., "A decision-focused knowledge management framework to support collaborative decision making for lean supply chain management" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Lyons, A.C., Everington, L., Hernandez, J., Li, D., Michaelides, R. and Um, J., "The application of a knowledge-based reference framework to support the provision of requisite variety and customisation across collaborative networks" ?" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Makris, S. and Chryssolouris, G., "Web-services-based supply-chain-control logic: an automotive case study" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Michaelides, R., Morton, S. C., Michaelides, Z., Lyons, A. C. and Liu, W., "Collaboration networks and collaboration tools: a match for SMEs?" ?" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Piorkowski, B. A., Gao, J. X., Evans, R. D. and Martin, N., "A dynamic knowledge management framework for the high value manufacturing industry" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Renna, P., "Decision model to support the SMEs’ decision to participate or leave a collaborative network", International Journal of Production Research, volume xx, number yy, 2013, pages aa. Shankar, R., Mittal, N., Rabinowitz, S., Baveja, A., and Acharia, S., "A collaborative framework to minimise knowledge loss in new product development?" International Journal of Production Research, volume xx, number yy, 2013, pages aa. Smirnov, A., Sheremetov, L., Sánchez, C., and Shilov, N., "Dynamic configuration of flexible supply networks based on semantic service composition", International Journal of Production Research, volume xx, number yy, 2013, pages aa. Trappey, A.J. C., Trappey, C.V., Chiang, T., and Huang, Yi-Hsuan., "Ontology-based neural network for patent knowledge management in design collaboration", International Journal of Production Research, volume xx, number yy, 2013, pages aa. Yang, J., "Harnessing value in knowledge management for performance in buyer–supplier collaboration, International Journal of Production Research, volume xx, number yy, 2013, pages aa.
