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Diffusion of Behavior in Network Games Orchestrated by Social Learning

Author

Listed:
  • Jia-Ping Huang

    (VU University Amsterdam)

  • Maurice Koster

    (University of Amsterdam)

  • Ines Lindner

    (VU University Amsterdam)

Abstract

The novelty of our model is to combine models of collective action on networks with models of social learning. Agents are connected according to an undirected graph, the social network, and have the choice between two actions: either to adopt a new behavior or technology or stay with the default behavior. The individual believed return depends on how many neighbors an agent has, how many of those neighbors already adopted the new behavior and some agent-specic cost-benefit parameter. There are four main insights of our model: (1) A variety of collective adoption behaviors is determined by the network. (2) Average inclination governs collective adoption behavior. (3) Initial inclinations determine the critical mass of adoption which ensures the new behavior to prevail. (4) Equilibria and dynamic be- havior changes as we change the underlying network and other parameters. Given the complexity of the system we use a standard technique for estimating the solution.

Suggested Citation

  • Jia-Ping Huang & Maurice Koster & Ines Lindner, 2013. "Diffusion of Behavior in Network Games Orchestrated by Social Learning," Tinbergen Institute Discussion Papers 13-208/II, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20130208
    as

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    File URL: https://papers.tinbergen.nl/13208.pdf
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    References listed on IDEAS

    as
    1. Kuran, Timur, 1991. "The East European Revolution of 1989: Is It Surprising That We Were Surprised?," American Economic Review, American Economic Association, vol. 81(2), pages 121-125, May.
    2. Matthew O. Jackson & Leeat Yariv, 2007. "Diffusion of Behavior and Equilibrium Properties in Network Games," American Economic Review, American Economic Association, vol. 97(2), pages 92-98, May.
    3. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Diffusion; Social Networks; Social Learning; Tipping; Technology Adoption;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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