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사회 네트워크 상의 기술 확산 경쟁에서 확산 시작 지점의 중심성에 따른 확산 경쟁의 결과

The Effect of Diffusion Starters' Centralities on Diffusion Extent in Diffusion of Competing Innovations on a Social Network

  • 투고 : 2015.03.09
  • 심사 : 2015.09.02
  • 발행 : 2015.11.30

초록

Diffusion of innovation is the process in which an innovation is communicated through certain channels over time among the members of a social system. The literatures have emphasized the importance of interpersonal network influences on individuals in convincing them to adopt innovations and thereby promoting its diffusion. In particular, the behavior of opinion leaders who lead in influencing others' opinion is important in determining the rate of adoption of innovation in a system. Centrality has been recognized as a good indicator that quantifies a node's influences on others in a given network. However, recent studies have questioned its relevance on various different types of diffusion processes. In this regard, this study aims at examining the effect of a node exhibiting high centrality on expediting diffusion of innovations. In particular, we considered the situation where two innovations compete with each other to be adopted by potential adopters who are personally connected with each other. In order to analyze this competitive diffusion process, we developed a simulation model and conducted regression analyses on the outcomes of the simulations performed. The results suggest that the effect of a node with high centrality can be substantially reduced depending upon the type of a network structure or the adoption thresholds of potential adopters in a network.

키워드

참고문헌

  1. 김도훈, "양면시장형 산업생태계에서 플랫폼 경쟁에 관한 진화게임 모형", 한국경영과학회 학술대회논문집, (2010), pp.39-69.
  2. 최대헌, "네트워크 외부효과를 고려한 두 단계 공급체인에서의 신기술 도입과 확산속도에 대한 연구 : 구매자-공급자간 관계 요인에 대한 모형", 한국경영과학회지, 제38권, 제3호(2013), pp.51-70. https://doi.org/10.7737/JKORMS.2013.38.3.051
  3. 홍정식, 구훈영, "확산이론 관점에서 로지스틱 모형과 Bass 모형의 비교", 한국경영과학회지, 제37권, 제2호(2012), pp.113-125. https://doi.org/10.7737/JKORMS.2012.37.2.113
  4. Abrahamson, E. and L. Rosenkopf, "Social network effects on the extent of innovation diffusion: A computer simulation," Organization Science, Vol.8, No.3(1997), pp.2389-2390.
  5. Ancona, D.G. and D.F, Caldwell, "Demography and design : Predictors of new product team productivity," Organization Science, Vol.3, No.3(1992), pp.321-341. https://doi.org/10.1287/orsc.3.3.321
  6. Arthur, W.B., "Competing technologies, increasing returns, and lock-in by historical events," Economic Journal, Vol.99, No.34 (1989), pp.116-131. https://doi.org/10.2307/2234208
  7. Arthur, W.B., "Increasing Returns and the Two Worlds of Business," Harvard Business Review, Vol.74, No.4(1996), pp.100-109.
  8. Bala, V. and S. Goyal, "Learning from neighbours," Review of Economic Studies, Vol.65, No.3(1998), pp.595-621. https://doi.org/10.1111/1467-937X.00059
  9. Bantel, K.A. and Susan E.J., "Top management and innovations in banking : does the composition of the top team make a difference?," Strategic Management Journal, Vol. 10(1989), pp.107-124. https://doi.org/10.1002/smj.4250100709
  10. Borgatti, S.P., Centrality and network flow, Social Networks, Vol.27(2005), pp.55-71. https://doi.org/10.1016/j.socnet.2004.11.008
  11. Burt, R.S., "Social contagion and innovation : cohesion versus structural equivalence," American Journal of Sociology, Vol.92, No.6(1987), pp.1287-1335. https://doi.org/10.1086/228667
  12. Carter Jr., F.J., T. Jambulingam, V.K. Gupta, and Melone, N., "Technological innovations : a framework for communicating diffusion effects," Information and Management, Vol. 38(2001), pp.277-287. https://doi.org/10.1016/S0378-7206(00)00065-3
  13. Centola, D., "The Spread of Behavior in an Online Social Network Experiment," Science, Vol.329, No.5996(2010), pp.1194-1197. https://doi.org/10.1126/science.1185231
  14. Farrell, J. and G. Saloner, "Installed Base and Compatibility : Innovation, Product Preannouncements, and Predation," American Economic Review, Vol.76, No.5(1986), pp.940-955.
  15. Farrell, J. and G. Saloner, "Standardization, Compatibility, and Innovation," Rand Journal of Economics, Vol.16, No.1(1985), pp.70-83. https://doi.org/10.2307/2555589
  16. Freeman, L.C., "Centrality in networks : I. Conceptual clarification," Social Networks, Vol.1(1979), pp.215-239.
  17. Freeman, L.C., S.P. Borgatti, and D.R. White, "Centrality in valued graphs : a measure of betweenness based on network flow," Social Networks, Vol.13(1991), pp.141-154. https://doi.org/10.1016/0378-8733(91)90017-N
  18. Granovetter, M., "Threshold models of collective behavior," The American Journal of Sociology, Vol.83, No.6(1978), pp.1420-1443. https://doi.org/10.1086/226707
  19. Hur, W., "Dynamics of Technology Adoption in Markets Exhibiting Network Effects," Asia Pacific Journal of Information System, Vol.20, No.1(2010), pp.127-140.
  20. Katz, E. and P.F. Lazarsfeld, "Personal influence : the part played by people in the flow of mass communications," Free Press, Glencoe, Ill, 1955.
  21. Katz, M.L. and C. Shapiro, "Network Externality, Competition and Compatibility," American Economic Review, Vol.75, No.3(1985), pp.424-440.
  22. Katz, M.L. and C. Shapiro, "Systems Competition and Network Effects," Journal of Economic Perspectives, Vol.8(1994), pp.93-113. https://doi.org/10.1257/jep.8.2.93
  23. Kim, J. and W. Hur, "Diffusion of competing innovations in influence networks," Journal of Economic Interaction and Coordination, Vol.8, No.1(2013), pp.109-124. https://doi.org/10.1007/s11403-012-0106-5
  24. Kiss, C. and M. Bitchler, "Identification of influencer : measuring influence in customer networks," Decision Support Systems, Vol.47 (2008), pp.233-253.
  25. Lee, E. and J. Lee, "Reconsideration of the Winner-Take-All Hypothesis : Complex Networks and Local Bias," Management Science, Vol.52, No.12(2006), pp.1838-1865. https://doi.org/10.1287/mnsc.1060.0571
  26. Reagans, R. and E.W. Zuckerman, "Networks, Diversity, and Productivity : The Social Capital of Corporate R&D Teams," Organization Science, Vol.12, No.4(2001), pp.502-517. https://doi.org/10.1287/orsc.12.4.502.10637
  27. Rogers, E.M., Diffusion of Innovations : 5th edition, FreePress, NewYork., 2003.
  28. Rosenkopf, L. and E. Abrahamson, "Modeling reputational and informational influences in threshold models of bandwagon innovation diffusion," Computational and Mathematical Organizational Theory, Vol.5, No.4 (1999), pp.361-384. https://doi.org/10.1023/A:1009620618662
  29. Valente T.W., "Network Models of the Diffusion of Innovations, Hampton Press," Cresskill, NJ., 1995.
  30. Valente, T.W., "Social network thresholds in the diffusion of innovations," Social Networks, Vol.18(1996), pp.69-89. https://doi.org/10.1016/0378-8733(95)00256-1
  31. Watts, D.J. and P.S. Dodds, "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Vol.34, No.4(2007), pp.441-458. https://doi.org/10.1086/518527
  32. Weitzel, T., D. Beimborn, and W.A. Konig, "Unified Economic Model of Standard Diffusion : The Impact of Standardization Cost, Network Effects, and Network Topology," MIS Quarterly, Vol.30, No.1(2006), pp.489-514. https://doi.org/10.2307/25148770