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Credibility and Strategic Learning in Networks

Author

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  • Chatterjee, Kalyan
  • Dutta, Bhaskar
Abstract
This paper studies a model of diffusion in a fixed, finite connected network. There is an interested party that knows the quality of the product or idea being propagated and chooses an implant in the network to influence other agents to buy or adopt. Agents are either “innovators”, who adopt immediately, or rational. Rational consumers buy if buying rather than waiting maximizes expected utility. We consider the conditions on the network under which efficient diffusion of the good product with probability one is a perfect Bayes equilibrium. Centrality measures and the structure of the entire network are both important. We also discuss various inefficient equilibria.

Suggested Citation

  • Chatterjee, Kalyan & Dutta, Bhaskar, 2011. "Credibility and Strategic Learning in Networks," Economic Research Papers 270752, University of Warwick - Department of Economics.
  • Handle: RePEc:ags:uwarer:270752
    DOI: 10.22004/ag.econ.270752
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    References listed on IDEAS

    as
    1. Goyal, Sanjeev & Galeotti, Andrea, 2007. "A Theory of Strategic Diffusion," Coalition Theory Network Working Papers 9096, Fondazione Eni Enrico Mattei (FEEM).
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    7. Andrea Galeotti & Sanjeev Goyal, 2009. "Influencing the influencers: a theory of strategic diffusion," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 509-532, September.
    8. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
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    11. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    12. 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.
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    Cited by:

    1. Foerster, Manuel & Hellmann, Tim & Vega-Redondo, Fernando, 2024. "Strategic use of social media influencer marketing," UC3M Working papers. Economics 43985, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Comola, Margherita & Rusinowska, Agnieszka & Villeval, Marie Claire, 2024. "Competing for Influence in Networks through Strategic Targeting," IZA Discussion Papers 17315, Institute of Labor Economics (IZA).
    3. 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.
    4. Kimberley Scharf, 2014. "Private Provision Of Public Goods And Information Diffusion In Social Groups," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(4), pages 1019-1042, November.
    5. Sadick Mohammed & Awudu Abdulai, 2022. "Do Egocentric information networks influence technical efficiency of farmers? Empirical evidence from Ghana," Journal of Productivity Analysis, Springer, vol. 58(2), pages 109-128, December.
    6. Tsakas, Nikolas, 2017. "Diffusion by imitation: The importance of targeting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 118-151.
    7. Bravard, Christophe & Durieu, Jacques & Sarangi, Sudipta & Sémirat, Stéphan, 2023. "False information from near and far," Games and Economic Behavior, Elsevier, vol. 137(C), pages 152-174.
    8. 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.
    9. Tsakas, Nikolas, 2024. "Optimal influence under observational learning," Mathematical Social Sciences, Elsevier, vol. 128(C), pages 41-51.

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