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Influence of a network structure on the network effect in the communication service market

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  • Uchida, Makoto
  • Shirayama, Susumu

Abstract

In this study, we analyze the network effect in a model of a personal communication market, by using a multi-agent based simulation approach. We introduce into the simulation model complex network structures as the interaction patterns of agents. With complex network models, we investigate the dynamics of a market in which two providers are competing. We also examine the structure of networks that affect the complex behavior of the market. By a series of simulations, we show that the structural properties of complex networks, such as the clustering coefficient and degree correlation, have a major influence on the dynamics of the market. We find that the network effect is increased if the interaction pattern of agents is characterized by a high clustering coefficient, or a positive degree correlation. We also discuss a suitable model of the interaction pattern for reproducing market dynamics in the real world, by performing simulations using real data of a social network.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:21:p:5303-5310
    DOI: 10.1016/j.physa.2008.06.012
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    References listed on IDEAS

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    1. Church, Jeffrey & Gandal, Neil, 1992. "Network Effects, Software Provision, and Standardization," Journal of Industrial Economics, Wiley Blackwell, vol. 40(1), pages 85-103, March.
    2. Hidalgo, Cesar A. & Rodriguez-Sickert, C., 2008. "The dynamics of a mobile phone network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3017-3024.
    3. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    4. Denis Phan & Stephane Pajot & Jean-Pierre Nadal, 2003. "The Monopolist's Market with Discrete Choices and Network Externality Revisited: Small-Worlds, Phase Transition and Avalanches in an ACE Framework," Computing in Economics and Finance 2003 150, Society for Computational Economics.
    5. Katz, Michael L & Shapiro, Carl, 1992. "Product Introduction with Network Externalities," Journal of Industrial Economics, Wiley Blackwell, vol. 40(1), pages 55-83, March.
    6. Arthur, W. Brian & Lane, David A., 1993. "Information contagion," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 81-104, June.
    7. 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.
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    Cited by:

    1. Torsten Heinrich, 2018. "Network Externalities and Compatibility Among Standards: A Replicator Dynamics and Simulation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 809-837, October.
    2. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    3. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng, 2022. "An agent-based algorithm for dynamic routing in service networks," European Journal of Operational Research, Elsevier, vol. 303(2), pages 719-734.
    4. Tatsuhiro Shichijo & Emiko Fukuda, 2019. "A dynamic game analysis of Internet services with network externalities," Theory and Decision, Springer, vol. 86(3), pages 361-388, May.
    5. Giovanni Pegoretti & Francesco Rentocchini & Giuseppe Vittucci Marzetti, 2012. "An agent-based model of innovation diffusion: network structure and coexistence under different information regimes," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 145-165, October.
    6. Gräbner, Claudius & Heinrich, Torsten & Kudic, Muhamed, 2016. "Structuration processes in complex dynamic systems - an overview and reassessment," MPRA Paper 69095, University Library of Munich, Germany.
    7. Heinrich, Torsten, 2016. "The Narrow and the Broad Approach to Evolutionary Modeling in Economics," MPRA Paper 75797, University Library of Munich, Germany.
    8. Xiaomin Zhou, 2022. "Moderating Effect of Structural Holes on Absorptive Capacity and Knowledge-Innovation Performance: Empirical Evidence from Chinese Firms," Sustainability, MDPI, vol. 14(10), pages 1-13, May.
    9. Peres, Renana, 2014. "The impact of network characteristics on the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 330-343.
    10. 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.
    11. Heinrich, Torsten, 2015. "A Replicator Dynamic and Simulation Analysis of Network Externalities and Compatibility Among Standards," MPRA Paper 67198, University Library of Munich, Germany.
    12. Guseo, Renato & Guidolin, Mariangela, 2010. "Cellular Automata with network incubation in information technology diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2422-2433.

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