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Technology Adoption in Critical Mass Games: Theory and Experimental Evidence

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  • Claudia Keser
  • Irina Suleymanova
  • Christian Wey

Abstract

We analyze the choices between two technologies A and B that both exhibit network effects. We introduce a critical mass game in which coordination on either one of the standards constitutes a Nash equilibrium outcome while coordination on standard B is assumed to be payoff-dominant. We present a heuristic definition of a critical mass and show that the critical mass is inversely related to the mixed strategy equilibrium. We show that the critical mass is closely related to the risk dominance criterion, the global game theory, and the maximin criterion. We present experimental evidence that both the relative degree of payoff dominance and risk dominance explain players' choices. We finally show that users' adoption behavior induces firms to select a relatively unrisky technology which minimizes the problem of coordination failure to the benefit of consumers.

Suggested Citation

  • Claudia Keser & Irina Suleymanova & Christian Wey, 2009. "Technology Adoption in Critical Mass Games: Theory and Experimental Evidence," Discussion Papers of DIW Berlin 961, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp961
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    Cited by:

    1. Arasteh, Abdollah, 2017. "Considering the investment decisions with real options games approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1282-1294.
    2. David Smerdon & Theo Offerman & Uri Gneezy, 2020. "‘Everybody’s doing it’: on the persistence of bad social norms," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 392-420, June.
    3. Gu, Yiquan & Wenzel, Tobias, 2012. "Transparency, entry, and productivity," Economics Letters, Elsevier, vol. 115(1), pages 7-10.
    4. Seiya Hirano, 2024. "Consumer Coordination and Optimal Pricing under Network Externalities," ISER Discussion Paper 1267, Institute of Social and Economic Research, The University of Osaka.
    5. Battiston, Pietro & Harrison, Sharon G., 2024. "Believe it or not: Experimental evidence on sunspot equilibria with social networks," Games and Economic Behavior, Elsevier, vol. 143(C), pages 223-247.
    6. Hoffmann, Eric J. & Sabarwal, Tarun, 2019. "Global games with strategic complements and substitutes," Games and Economic Behavior, Elsevier, vol. 118(C), pages 72-93.
    7. Masiliūnas, Aidas, 2017. "Overcoming coordination failure in a critical mass game: Strategic motives and action disclosure," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 214-251.
    8. Schouten, Jop & Cognolato, Davide & Borm, Peter & Cruijssen, Frans, 2024. "Technology Selection with Peer-Based Network Effects," Other publications TiSEM f0f45255-e4f9-44ad-8679-d, Tilburg University, School of Economics and Management.
    9. Clémence Christin, 2013. "Entry Deterrence Through Cooperative R&D Over-Investment," Recherches économiques de Louvain, De Boeck Université, vol. 79(2), pages 5-26.
    10. Kornelia Hagen & Christian Wey, 2009. "Verbraucherpolitik zwischen Markt und Staat: Editorial," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 78(3), pages 5-29.
    11. Eric J. Hoffmann & Tarun Sabarwal, 2018. "Monotone Global Games," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201903, University of Kansas, Department of Economics.
    12. Malte Müller & Jens Rommel & Christian Kimmich, 2018. "Farmers’ Adoption of Irrigation Technologies: Experimental Evidence from a Coordination Game with Positive Network Externalities in India," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 119-139, May.
    13. Haucap, Justus & Herr, Annika & Frank, Björn, 2011. "In vino veritas: Theory and evidence on social drinking," DICE Discussion Papers 37, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    14. Bradley J. Ruffle, Avi Weiss, Amir Etziony, 2015. "The Role of Critical Mass in Establishing a Successful Network Market: An Experimental Investigation," LCERPA Working Papers 0092, Laurier Centre for Economic Research and Policy Analysis, revised 12 May 2015.
    15. Stühmeier Torben & Wenzel Tobias, 2012. "Regulating Advertising in the Presence of Public Service Broadcasting," Review of Network Economics, De Gruyter, vol. 11(2), pages 1-23, June.
    16. Keser, Claudia & Suleymanova, Irina & Wey, Christian, 2012. "Technology adoption in markets with network effects: Theory and experimental evidence," Information Economics and Policy, Elsevier, vol. 24(3), pages 262-276.
    17. Joann F. de Zegher & Dan A. Iancu & Hau L. Lee, 2019. "Designing Contracts and Sourcing Channels to Create Shared Value," Manufacturing & Service Operations Management, INFORMS, vol. 21(2), pages 271-289, May.

    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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