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Agency, potential and contagion

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  • Newton, Jonathan
  • Sercombe, Damian

Abstract

We consider two fundamental forces that can drive the diffusion of an innovation on a network. The first of these forces is potential maximization, a method of aggregating payoff incentives of players under individual agency. Potential maximization is related to the graph theoretic property of close-knittedness (Young, 2011). The second force is collective agency, under which sets of players decide together on whether to adjust their strategies. Collective agency is shown to be related to the graph theoretic property of cohesion (Morris, 2000). We compare the relative strengths of these forces under (i) different payoff specifications in coordination games and (ii) different network structures.

Suggested Citation

  • Newton, Jonathan & Sercombe, Damian, 2020. "Agency, potential and contagion," Games and Economic Behavior, Elsevier, vol. 119(C), pages 79-97.
    • Handle: RePEc:eee:gamebe:v:119:y:2020:i:c:p:79-97
    DOI: 10.1016/j.geb.2019.10.007
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    References listed on IDEAS

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    Cited by:

    1. Cui, Zhiwei, 2023. "Linking friction, social coordination and the speed of evolution," Games and Economic Behavior, Elsevier, vol. 140(C), pages 410-430.
    2. Sawa, Ryoji & Wu, Jiabin, 2023. "Statistical inference in evolutionary dynamics," Games and Economic Behavior, Elsevier, vol. 137(C), pages 294-316.
    3. Simon D Angus & Jonathan Newton, 2020. "Collaboration leads to cooperation on sparse networks," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-11, January.
    4. Naono, Miharu, 2022. "Cost heterogeneity and the persistence of bilingualism," Games and Economic Behavior, Elsevier, vol. 136(C), pages 325-339.
    5. Santiago Guisasola & Donald Saari, 2020. "With Potential Games, Which Outcome Is Better?," Games, MDPI, vol. 11(3), pages 1-20, August.

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