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Diffusion of competing innovations in influence networks

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  • Jeehong Kim
  • Wonchang Hur

Abstract

Although an influence network is a crucial factor affecting diffusion processes, it is generally fixed or assumed to follow some typical topologies in traditional diffusion research. The purpose of this study is to examine how innovation diffusion is changed by different influence relationship structures existing among individuals. We introduce an extended version of the regular digraph that can represent various influence relationships among influentials and followers. We focus on three key features of influence relationships (i.e. monopolization, localization, and diversification of opinions) and examine how they are associated with certain macroscopic behavioral regularities by employing agent-based simulation. The simulation results show that market becomes “locked-in” to a single product when influences are monopolized by few influentials. We also find that when influence relationship becomes complex as influentials and followers increase, market cannot be categorized by a single typology, but becomes random and unpredictable. Our model demonstrates successfully an underlying principle of collective behavior that uniformity of behavior is promoted under monopolization of opinions and random, unpredictable behavioral patterns emerge from diversification of opinions. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Jeehong Kim & Wonchang Hur, 2013. "Diffusion of competing innovations in influence networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 109-124, April.
    • Handle: RePEc:spr:jeicoo:v:8:y:2013:i:1:p:109-124
    DOI: 10.1007/s11403-012-0106-5
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    References listed on IDEAS

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    1. Feder, Gershon & Savastano, Sara, 2006. "The role of opinion leaders in the diffusion of new knowledge: The case of integrated pest management," World Development, Elsevier, vol. 34(7), pages 1287-1300, July.
    2. Joseph Farrell & Garth Saloner, 1985. "Standardization, Compatibility, and Innovation," RAND Journal of Economics, The RAND Corporation, vol. 16(1), pages 70-83, Spring.
    3. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
    4. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    5. Mark Granovetter, 2005. "The Impact of Social Structure on Economic Outcomes," Journal of Economic Perspectives, American Economic Association, vol. 19(1), pages 33-50, Winter.
    6. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    7. Uchida, Makoto & Shirayama, Susumu, 2008. "Influence of a network structure on the network effect in the communication service market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5303-5310.
    8. Liebowitz, S J & Margolis, Stephen E, 1995. "Path Dependence, Lock-in, and History," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 11(1), pages 205-226, April.
    9. Chung-Yuan Huang & Chuen-Tsai Sun & Hsun-Cheng Lin, 2005. "Influence of Local Information on Social Simulations in Small-World Network Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-8.
    10. Eocman Lee & Jeho Lee & Jongseok Lee, 2006. "Reconsideration of the Winner-Take-All Hypothesis: Complex Networks and Local Bias," Management Science, INFORMS, vol. 52(12), pages 1838-1848, December.
    11. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    12. Jean-Philippe Cointet & Camille Roth, 2007. "How Realistic Should Knowledge Diffusion Models Be?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-5.
    13. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
    14. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
    15. Catherine Tucker, 2008. "Identifying Formal and Informal Influence in Technology Adoption with Network Externalities," Management Science, INFORMS, vol. 54(12), pages 2024-2038, December.
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