Analyzing the sanctions action in the ambidextrous business cluster dispute using game theory

Document Type : Original Article

Authors

1 Ph.D. Candidate in Entrepreneurship, Razi University

2 Assistant Prof. of Management and Entrepreneurship, Razi University

3 Associate Prof. of Economics, Razi University

Abstract

Business clusters evolve as a spatial focus of firms with shared opportunities and threats in a nonlinear behavior, with a multiple feedback mechanism between cluster actors, and require attention to ambidexterity- exploiting of current capabilities and exploring future opportunities- in order to survive in a complex and competitive environment. In recent decades, the harsh sanctions of the arrogant powers have been one of the obstacles to accessing the world's latest technical knowledge and technology to help economic growth and development, which has been considered a source of serious controversy in reducing the competitiveness of enterprises. In this study, in order to investigate the issue of sanctions in interaction with other actors, information collection through reading articles, policy documents, reports and receiving expert opinions through interviews has been considered. Due to the complexity of this conflict, using a game theory model called the graph model, the interactions and preferences between different actors in the business cluster are modeled and the most probable results are presented. According to the analysis, the government, business clusters and scientific and research centers have an improved equilibrium point, but there is no preferential financing for the centers to change the current situation.

Keywords

References

  •  

    • Alizadeh, Y., Jetter A.J. (2018). Pathways for Balancing Exploration and Exploitation in Innovations: A Review and Expansion of Ambidexterity Theory. International Journal of Innovation and Technology Management,17(1): 1-33.
    • Aziz, K. A., & Norhashim, M. (2008). Cluster-Based Policy Making: Assessing Performance and Sustaining Competitiveness. Review of Policy Research, 25(1), 349-375.
    • Bettis-Outland, H., Felzensztein, C., Gimmon, E., & Aqueveque, C. (2012). Clusters or un-clustered industries? Where inter-firm marketing cooperation matters. Journal of Business & Industrial Marketing, 27(5), 392-402.
    • Bocquet, R. Mothe, C. Can a governance structure foster cluster ambidexterity through knowledge management? An empirical study of two French SME clusters. Knowledge Management Research and Practice, Palgrave Macmillan, 2015, 13 (3), pp.329-343.
    • Casanueva, C., Castro, I., & Galán, J. L. (2013). Informational networks and innovation in mature industrial clusters. Journal of Business Research, 665), 603-613.
    • Eisingerich, A. B., Bell, S. J., & Tracey, P. (2010). How can clusters sustain performance? The role of network strength, network openness, and environmental uncertainty. Research Policy, 39(2), 239-253.
    • Fang, L., Hipel, K. W., Kilgour, D. M., & Peng, X (2003b). A decision support system forinteractive decision making-part II: analysis and output interpretation, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 33(1), 56-66.
    • Ferrary, M. (2011). Specialized organizations and ambidextrous clusters in the open innovation paradigm. European Management Journal, 29(3), 181–192.
    • Gibson, C. B., & Birkinshaw, J. (2004). The Antecedents, Consequences, and Mediating Role of Organizational Ambidexterity, Academy of Management Journal, 47(2): 209–226.
    • Giuliani, E. (2007). The selective nature of knowledge networks in clusters: evidence from the wine industry. Journal of Economic Geography 7 (2):139–168.
    • Handayani, N.U Cakravastia, A.Diawati, L. Nur Bahagia, S. (2012). A conceptual assessment model to identify phase of industrial cluster life cycle in Indonesia. Journal of Industrial Engineer in g and Management. 5(1): 198-227.
    • Hipel, K.W., Fang, L., Kilgour, D.M. (2020). The Graph Model for Conflict Resolution: Reflections on Three Decades of Development. Group Decision and Negotiation. 29(1): 1-60.
    • Janson J. p., Simsek Z., Cao Q. (2012). Ambidexterity and performance attributes. Strategic Management Journal in multiunit contexts: Cross-level moderating effects of structural and resource, 33(11):1286-1303.
    • Kang, S., Morris, S. S. and Snell, S. A. (2007) ‘Relational Archetypes, Organizational Learning, and Value Creation: Extending the Human Resource Architecture’, Academy of Management Review, 32(1): 236–256.
    • Kauppila, O. (2007). Towards a network model of ambidexterity (No. W-429) (p. 429). Helsinki School of Economics Working Papers.
    • Kilgour, D.M., and Hipel, K.W. (2001). Coalition Analysis in Group Decision Support, Group Decision, and Negotiation, 10(2): 159–175.
    • Kilgour, D.M., and Hipel, K.W. (2010). Conflict Analysis Methods: The Graph Model for Conflict Resolution, In Kilgour, D.M. and Eden, C. (Editors), “Handbook of Group Decision and Negotiation, Springer, Dordrecht, the Netherlands, pp. 203-222.
    • Malemberg A. and Maskell P. (2002). The elusive concept of localization economies: towards a knowledge-based theory of spatial clustering, Environment and Planning 34, 429–449.
    • Matbouli, Y., Kilgour, D. M. W. (2015).Robustness of equilibria in the graph model for conflict resolution. Journal of Systems Science and Systems Engineering, (December 2015) 24(4): 450-465.
    • McDonald, F., Huang, Q. H., Tsagdis, D., & Tuselmann, H. J. (2007) .Is there evidence to support porter-type cluster policies? Regional Studies, 411, 39-49.
    • Menzel M.P., Fornahl D. (2010). Cluster life cycles—dimensions and rationales of cluster evolution, Industrial and Corporate Change, 19(1): 205–238
    • Mihajlović, I. (2014). Possibilities for development of business cluster network between SMEs from Visegrad countries and Serbia. Serbian Journal of Management, 9(2), 145-148.
    • Nazari, M., Hasangholipour, T., Soleimani, G., Abbasian, E., & Moussavi Neghabi, S. M. (2017). Investigation of the Productivity of Networking Activities and Improvement Projects on the Sales and Employment of Iranian Agricultural Clusters. Iranian Economic Review, 21(1), 45-70.
    • Oak, Myung Kim and Sam Jaffe (2010). The new Korea: an inside look at South Korea's economic rise. New York: AMACOM.
    • O'Reilly, C. and Tushman, M. (2008). Ambidexterity as a dynamic capability: Resolving the innovator's dilemma. Research in Organizational Behavior, 28: 185–206.
    • Popadiuk, S., Souza Luz, A.R., Kretschmer, C., (2018). Dynamic Capabilities and Ambidexterity: How is These Concepts Related? Revista de Administração Contemporânea, 22(5):639-660
    • Reid, R., and Harris, R.I.D. (2004). Family-Owned SME Growth in Scotland: A Comparison with the UK. Report to Scotecon.
    • Rivlin, P., (2006). Iran’S Energy Vulnerability, Middle East Review of International Affairs, 10(4). 125-142.
    • Romanelli, E., & Khessina, O. M. (2005). Regional industrial identity: Cluster configurations and economic development. Organization science, 16(4), 344-358.
    • Springer International Publishing.
    • Stadler, C., Rajwani, T., & Karaba, F. (2014). Solutions to the exploration/exploitation dilemma: networks as a new level of analysis. International Journal of Management Reviews, 16(2), 172-193.
    • Trippl, M. Grillitsch, M. Isaksen, A. Sinozic T. (2015) Perspectives on Cluster Evolution: Critical Review and Future Research Issues, European Planning Studies, 23(10), 2028-2044.
    • Wolf, T., Cantner U., Graf H., Rothgang M. (2017). Cluster ambidexterity towards exploration and exploitation: strategies and cluster management.  Journal of Technology Transfer, 44(6):1840-1866.
    • Xu H, Hipel KW, Kilgour DM, Fang L. (2018). Conflict resolution using the graph model: Strategic interactions in competition and cooperation. Cham:

    Zhou, Zh. K. (2006). Innovation, imitation, and new product performance: The case of China. Journal of Industrial Marketing Management, 35(1): 394–415.

Files

Share

How to cite

Statistics