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Diffusion by imitation: The importance of targeting agents

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  • Tsakas, Nikolas

Abstract

We study the optimal targeting strategy of a planner who seeks to maximize the diffusion of an action in a society where agents imitate successful past behavior of others. The agents face individual decision problems under uncertainty, make reversible adoption choices and interact locally, so that each agent affects only her neighbors. We find that the optimal targeting strategy depends on two parameters: (i) the likelihood of the action being more successful than its alternative and (ii) the planner's patience. More specifically, for an infinitely patient planner, the optimal strategy is to cluster all the targeted agents in one connected group when her preferred action has higher probability of being more successful than its alternative; whereas it is optimal spreading them across the population when this probability is lower. Interestingly, for an impatient planner the optimal targeting strategy is exactly the opposite.

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  • Tsakas, Nikolas, 2017. "Diffusion by imitation: The importance of targeting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 118-151.
  • Handle: RePEc:eee:jeborg:v:139:y:2017:i:c:p:118-151
    DOI: 10.1016/j.jebo.2017.04.015
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    Cited by:

    1. Margherita Comola & Agnieszka Rusinowska & Marie Claire Villeval, 2024. "Competing for Influence in Networks Through Strategic Targeting [En compétition pour l'influence dans les réseaux grâce au ciblage stratégique]," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04706311, HAL.
    2. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    3. Nikolas Tsakas, 2014. "Optimal influence under observational learning," Gecomplexity Discussion Paper Series 4, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Nov 2014.
    4. Daniel C. Opolot & Théophile T. Azomahou, 2021. "Strategic diffusion in networks through contagion," Journal of Evolutionary Economics, Springer, vol. 31(3), pages 995-1027, July.
    5. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2018. "Strategic Influence in Social Networks," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 29-50, February.
    6. Tsakas, Nikolas, 2024. "Optimal influence under observational learning," Mathematical Social Sciences, Elsevier, vol. 128(C), pages 41-51.

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    More about this item

    Keywords

    Targeting; Diffusion; Imitation; Local interactions;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • 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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