بهینه‌سازی فرایند تبادل دانش در خوشه‌های صنعتی: مطالعه موردی در خوشه صنعتی گچ سمنان

نوع مقاله : مروری

نویسندگان

استادیار، دپارتمان مهندسی صنایع، دانشکده مهندسی، دانشگاه بوعلی سینا، همدان، ایران

چکیده

دانش به عنوان یک منبع حیاتی، می‌تواند برای شرکت‌ها مزیت رقابتی ایجاد کند و کسب و به‌کارگیری آن از وظایف مهم هر شرکتی است. خوشه صنعتی مجموعه‌ای از شرکت‌ها با محصولات مشابهند که در یک منطقه جغرافیایی مستقر هستند و شرکت‌های عضو خوشه به منظور صرفه‌جویی در منابع و افزایش توان رقابتیشان در فعالیت‌های مشترک با هم همکاری می‌کنند. یکی از این فعالیت‌های مشترک بین اعضای خوشه تبادل دانش است که موجب کاهش هزینه‌های کسب دانش، افزایش همکاری بین شرکت‌ها، بهبود توانایی، نوآوری و تقویت توان رقابت کلی شرکت‌های خوشه می‌شود. در این مقاله، ما با طراحی و استفاده از شبکه‌های جریان دانش قصد داریم با حداقل هزینه و زمان فرایند تبادل دانش بین اعضای خوشه را ماکزیمم کنیم. این مساله را با برنامه‌ریزی عدد صحیح مختلط فرموله کرده و با روش دقیق برای خوشه صنعتی گچ سمنان حل می‌کنیم. سپس با تحلیل حساسیت مدل، پارامترهای مهم و اثرگذار بر فرایند تبادل دانش شناسایی می‌شوند. نتایج حاصل از تحلیل نشان می‌دهد که از بین دو منبع بودجه و زمان، انعطاف مساله نسبت به بودجه خیلی کمتر است. یعنی کاهش آن اثر خیلی بیشتری در کاهش میزان تبادل دانش در خوشه دارد، اما کاهش مدت برنامه تبادل دانش به مقدار خیلی کمتری میزان تبادل دانش را می‌کاهد. همچنین با تقویت رابطه بین اعضای خوشه می‌توان هزینه تبادل دانش را کاهش داد و با بهبود توان تبادل دانش شرکت‌ها می‌توان برنامه تبادل دانش در خوشه را در مدت کوتاه‌تری انجام داد. این نتایج به مدیران خوشه درک بهتری می‌دهد تا بتوانند با توجه به منابع موجود، شرایط بازار کسب و کار و اهداف تدوین شده، طوری برنامه‌ریزی کنند که فرایند تبادل دانش بین اعضای خوشه ماکزیمم شود.

کلیدواژه‌ها


عنوان مقاله [English]

A New Model to Optimize the Knowledge Exchange in Industrial Cluster: A Case Study of Semnan Plaster Production Industrial Cluster

نویسندگان [English]

  • Hamidreza Dezfoulian
  • Parvaneh Samouei
Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran1
چکیده [English]

Industrial clusters bring member firms the opportunities and advantages to save resources and increase competitiveness through cooperation and joint activities. One of these opportunities is knowledge sharing, using shared resources. If cluster firms want to create knowledge directly or acquire it out of the cluster, it is necessary to spend much money and time. The aim is to maximize knowledge transfer between firms of a cluster regarding budget and time limitations, using existing knowledge flow networks. The issue is formulated with a new model of mixed integer programming and solved by the CPLEX solver for Semnan plaster production industrial clusters. The results of sensitivity analysis show that knowledge transfer is much more influenced by budget than by time constraints. The results help cluster managers to have a better understanding, regarding the available resources and business conditions, to maximize the results obtained from the knowledge transfer.
 

کلیدواژه‌ها [English]

  • Knowledge Sharing / Optimization / Industrial Cluster / New Mathematical Model / Organizational Social Relationships
Afrazeh, A. (2010), Knowledge management (introduction, models, measurement and implementation), Moalef Press, Tehran, Iran, (In Persian).
Bocquet, R. and Mothe, C. (2010), Knowledge governance within clusters: the case of small firms, Knowledge Management Research & Practice, 8, 229–239.
Chen, J., Chen, D. and Li, Z. (2008), The Analysis of Knowledge Network Efficiency in Industrial Clusters, International Seminar on Future Information Technology and Management Engineering 2008, IEEE, 257-260.
Dayasindhu, N. (2002), Embeddedness, knowledge transfer, industry clusters and global competitiveness: a case study of the Indian software industry, Technovation, 22, 551–560.
Fang, Y., Liang, Q. and Jia, Z. (2011), Knowledge Sharing Risk Warning of Industry Cluster: an Engineering Perspective, Systems Engineering Procedia 2, 412 – 421.
Fritsch, M., Kauffeld-Monz, M., (2010), The impact of network structure on knowledge transfer: an application of social network analysis in the context of regional innovation networks, The Annals of Regional Science, Volume 44, Issue 1, pp 21-38.
Giuliani, E. (2007), The selective nature of knowledge networks in clusters: evidence from the wine industry, Journal of Economic Geography, 7, pp. 139–168.
Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(Winter), 109–122.
Guo, J. and Guo, B. (2008), The Evolution of Knowledge Network in Manufacturing Cluster: A Case in China, Proceedings of the 2008 IEEE IEEM, 890-894.
Hansen, M.T. (2002), Knowledge networks: explaining effective knowledge sharing in multiunit companies, Organization Science, 13, 3, 232–248.
Hoffmann, V. E., Bandeira-de-Mello, R. and Molina-Morales, F. X. (2011), Innovation and Knowledge Transfer in Clustered Interorganizational Networks in Brazil, Latin American Business Review, 12, 143–163.
Hoffmann, V. E., Lopes, G. S. C. and Medeiros, J. J. (2014), Knowledge transfer among the small businesses of a Brazilian cluster, Journal of Business Research, 67, 856–864.
Hsu, C. (2008), “Knowledge sharing practices as a facilitating factor for improving organizational performance though human capital: Preliminary test”, Export Systems with Applications, Vol. 35, pp. 1316-1326.
Huang, Ch. (2009), “Knowledge sharing and group cohesiveness on performance: an empirical study of technology R&D teams in Taiwan”, Technovation, Vol. 29, pp. 786-797.
Huysman, M. and De Wit, D. (2000), “Knowledge management in practice”, In Edwards, J. and Kidd, J. (Eds.) Knowledge Management Conference, Birmingham, UK.
Ji L-M., Hung J., Chen S-W., Jou C. (2009), Fostering the determinants of knowledge sharing, virtual communities. Computers in Human Behavior, 929–939.
Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397.
Leung, Y.T. and Glissmann, S.M. (2011),  A clustering approach to the design of knowledge-intensive service providers. Available: http://domino.research.ibm.com/library/cyberdig.nsf/papers/ 58C6B1D509E8DCA68525780000603960 December 2011.
Liu, C. and Chen, S. (2005), “Determinants of knowledge sharing of e-learners”, International Journal of Innovation and Learning, Vol. 2 No. 4, pp. 434–445
Lopez-Saez, P., Navas-Lopez, J. E., Martin-de-Castro, G. and Cruz-Gonzalez, J. (2010), External knowledge acquisition processes in knowledge-intensive clusters, Journal of Knowledge Management, VOL. 14, NO. 5, pp. 690-707.
Malmberg A., Maskell P. (2002) The elusive concept of localization economies: towards a knowledge based theory of spatial clustering. Environ Plann 34(3):429–449
Porter, M. E. (1998), Clusters and the new economics of competition. Harv Bus Rev 76(6):77–90
Porter, M. E. (2000), Location, competition, and economic development: local clusters in a global economy. Econ Dev Q 14(1):15–34
Power, D. and Lundmark, M. (2004), Working through Knowledge Pools: Labor Market Dynamics, the Transference of Knowledge and Ideas, and Industrial Clusters, Urban Studies, Vol. 41, Nos 5/6, 1025–1044.
Renzle, B. (2012), “Trust in management and knowledge sharing: The mediating effects of fear and knowledge documentation”, Omega, Vol. 36, pp. 206-220.
Richardson, C. (2013), Knowledge-sharing through social interaction in a policy-driven industrial cluster, Journal of Entrepreneurship and Public Policy, Vol. 2, No. 2, pp. 160-177.
Sreckovic, M. and Windsperger, J. (2013), The Impact of Trust on the Choice of Knowledge Transfer Mechanisms in Clusters, Network Governance Contributions to Management Science, Springer-Verlag Berlin Heidelberg 2013, pp 73-85.
Sreckovic, M., Windsperger, J. (2011) Organization of knowledge transfer in clusters: a knowledge-based view, In: Tuunanen M,Windsperger J, Cliquet G, Hendrikse G (eds) New developments in the theory of networks. Franchising, alliances and cooperatives. Springer, Berlin, pp 318–334.
Stackea, A. R. N. P., Hoffmannb, V. E. and Araujo Costa, H. (2012), Knowledge transfer among clustered firms: a study of Brazil, Anatolia – An International Journal of Tourism and Hospitality Research, Vol. 23, No. 1, 90–106.
Teece, D.J. (2001), ‘‘Strategies for managing knowledge assets: the role of firm structure and industrial context’’, in Nonaka, I. and Teece, D.J. (Eds), Managing Industrial Knowledge. Creation, Transfer and Utilization, Sage, London, pp. 125-44.
Wang, S. and Noe, R. A. (2010), “Knowledge sharing: A review and directions for future research”, Human Resource Management Review, Vol. 20, pp. 115-131
Wijk, R. V., Jansen, J. J. P. and Lyles, M. A. (2008), Inter- and Intra-Organizational Knowledge Transfer: A Meta-Analytic Review and Assessment of its Antecedents and Consequences, Journal of Management Studies, 45, 830-853.
Wilson, L. and Spoehr, J. (2010), Labour Relations and the Transfer of Knowledge in Industrial Clusters: Why do Skilled Workers Share Knowledge with Colleagues in Other Firms?, Geographical Research, 48, 1, 42–51.
Xiong, J., Duan, Z. and Wang, Y. (2013), Modeling and Simulation of the Inter-Organizational Knowledge Transfer Impact Factors in Industrial Clusters, The 19th International Conference on Industrial Engineering and Engineering Management, Springer-Verlag Berlin Heidelberg 2013, 161-171.
Yu, J. (2008), Study on product knowledge ontology for industrial cluster, International Symposium on Knowledge Acquisition and Modeling, 2008 IEEE, 108-112.
Zhou, S. (2013), Study of Knowledge Diffusion FSAI Model for High-Tech SMES Clusters, The 19th International Conference on Industrial Engineering and Engineering Management, Springer-Verlag Berlin Heidelberg 2013, 783-794.
Zhuge, H. (2006), Knowledge flow network planning and simulation, Decision Support Systems, 42, 571–592.