Abstract
This paper investigates the influence of human factors on the evolution of inter-firm trade network emerging from bankruptcy. In particular, we concentrate on a local interaction mechanism, conceptualized as triangle structure, within the inter-firm human network. An agent-based model is employed to explore the effects of triangle structure-related properties in both real inter-firm human network constructed from empirical data of thousands Japanese firms, and artificially generated ones. The simulation results confirm the influential role of triangle structure-related human factors in bankruptcy: it not only enhances the benefits that firms can obtain from their inter-firm relationships, but also provides firms with few business partners the equal chance to survive in the bankrupt emergency.
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Notes
- 1.
Code of RandNetGen can be found in: https://github.com/polcolomer/RandNetGen.
- 2.
The website of NetworkX library: https://networkx.github.io/.
References
Ohnishi, T., Takayasu, H., Takayasu, M.: Network motifs in an inter-firm network. J. Econ. Interact. Coord. 5(2), 171–180 (2010)
Aggarwal, C., Subbian, K.: Evolutionary network analysis: a survey. ACM Comput. Surv. (CSUR) 47(1), 10 (2014)
Fujiwara, Y.: Chain of firms’ bankruptcy: a macroscopic study of link effect in a production network. Adv. Complex Syst. 11(05), 703–717 (2008)
Hong, B.H., Lee, K.E., Lee, J.W.: Power law in firms bankruptcy. Phys. Lett. A 361(1), 6–8 (2007)
Battiston, S., Gatti, D.D., Gallegati, M., Greenwald, B., Stiglitz, J.E.: Credit chains and bankruptcy propagation in production networks. J. Econ. Dyn. Control 31(6), 2061–2084 (2007)
Robins, G., Alexander, M.: Small worlds among interlocking directors: network structure and distance in bipartite graphs. Comput. Math. Organ. Theory 10(1), 69–94 (2004)
Wang, S., Songhori, M.J., Chang, S., Terano, T.: The impact of human relationship on bankruptcy-related evolution of inter-firm trade network. In: Winter Simulation Conference (WSC), pp. 3405–3416. IEEE Press (2016)
Coleman, J.S.: Social capital in the creation of human capital. Am. J. Sociol. 94, S95–S120 (1988)
Schilling, M.A., Phelps, C.C.: Interfirm collaboration networks: the impact of large-scale network structure on firm innovation. Manag. Sci. 53(7), 1113–1126 (2007)
Phelps, C.C.: A longitudinal study of the influence of alliance network structure and composition on firm exploratory innovation. Acad. Manag. J. 53(4), 890–913 (2010)
Simmel, G., Wolff, K.H.: The Sociology of Georg Simmel. Simon and Schuster, New York City (1950)
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., Alon, U.: Network motifs: simple building blocks of complex networks. Science 298(5594), 824–827 (2002)
Kossinets, G., Watts, D.J.: Empirical analysis of an evolving social network. Science 311(5757), 88–90 (2006)
Newman, M.E., Park, J.: Why social networks are different from other types of networks. Phys. Rev. E 68(3), 036122 (2003)
Choi, T.Y., Wu, Z.: Triads in supply networks: theorizing buyer-supplier-supplier relationships. J. Supply Chain Manag. 45(1), 8–25 (2009)
Kreiser, P.M.: Entrepreneurial orientation and organizational learning: the impact of network range and network closure. Entrepreneurship Theory Pract. 35(5), 1025–1050 (2011)
Howard, M., Cox Pahnke, E., Boeker, W.: Understanding network formation in strategy research: exponential random graph models. Strateg. Manag. J. 37(1), 22–44 (2016)
Greve, H.R.: Performance, aspirations, and risky organizational change. Adm. Sci. Q. 43(1), 58–86 (1998)
Huber, G.P.: Organizational learning: the contributing processes and the literatures. Organ. Sci. 2(1), 88–115 (1991)
Cyert, R.M., March, J.G.: A Behavioral Theory of the Firm, 2nd edn. Prentice Hall, Englewood Cliffs (1963)
Cybinski, P.: Description, explanation, prediction–the evolution of bankruptcy studies? Manag. Fin. 27(4), 29–44 (2001)
Basole, R.C., Bellamy, M.A.: Supply network structure, visibility, and risk diffusion: a computational approach. Decis. Sci. 45(4), 753–789 (2014)
Mahoney, J.T., Pandian, J.R.: The resource-based view within the conversation of strategic management. Strateg. Manag. J. 13(5), 363–380 (1992)
Pfeffer, J., Salancik, G.R.: The External Control of Organizations: A Resource Dependence Perspective. Stanford University Press, Palo Alto (2003)
Hite, J.M., Hesterly, W.S.: The evolution of firm networks: from emergence to early growth of the firm. Strateg. Manag. J. 22(3), 275–286 (2001)
Bhidé, A.V.: The origin and evolution of new businesses. Oxford University Press, Oxford (2003)
Rosenkopf, L., Almeida, P.: Overcoming local search through alliances and mobility. Manag. Sci. 49(6), 751–766 (2003)
Kauffman, S.A., Weinberger, E.D.: The NK model of rugged fitness landscapes and its application to maturation of the immune response. J. Theor. Biol. 141(2), 211–245 (1989)
Newman, M.E.J.: The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003)
Schank, T., Wagner, D.: Approximating clustering-coefficient and transitivity. Universität Karlsruhe, Fakultät für Informatik (2004)
Orsini, C., Dankulov, M.M., Colomer-de-Simón, P., Jamakovic, A., Mahadevan, P., Vahdat, A., Bassler, K.E., Toroczkai, Z., Boguñá, M., Caldarelli, G., Fortunato, S., Krioukov, D.: Quantifying randomness in real networks. Nat. Commun. 6(5), 8627 (2015)
Colomer-de-Simón, P., Boguñá, M.: Double percolation phase transition in clustered complex networks. Phys. Rev. X 4(4), 041020 (2014)
Albert, R., Barabási, A.-L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)
Goto, H., Takayasu, H., Takayasu, M.: Empirical analysis of firm-dynamics on japanese interfirm trade network. In: Takayasu, H., Ito, N., Noda, I., Takayasu, M. (eds.) International Conference on Social Modeling and Simulation, Plus Econophysics Colloquium 2014, pp. 195–204. Springer International Publishing, Cham (2015)
Acknowledgments
The research is partially supported by the Center for TDB Advanced Data Analysis and Modeling in Tokyo Institute of Technology and JSPS KAKENHI (Grant Number 25240048).
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Wang, S., Songhori, M.J., Chang, S., Terano, T. (2018). How Triangle Structure in Inter-firm Human Network Affects Bankruptcy Evolution: An Agent-Based Simulation Study with Real and Artificial Data. In: Cassenti, D. (eds) Advances in Human Factors in Simulation and Modeling. AHFE 2017. Advances in Intelligent Systems and Computing, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-319-60591-3_26
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DOI: https://doi.org/10.1007/978-3-319-60591-3_26
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