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Rewards versus punishments in additive, weakest-link, and best-shot contests

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  • Kamijo, Yoshio

Abstract

In this study, we provide a theory to explain how bottom punishment or top reward enhances performance of teams when there is heterogeneity across players in cost–performance relationships. In contrast to the existing literature, we consider three types of performance functions: additive, weakest link (the performance is the min of performances of n contestants), and best shot (the performance is the max of performances of n contestants). For any of the three types, we derive easy-to-check sufficient conditions to judge whether reward or punishment is better. From the sufficient condition for the additive performance function, we know that punishment is better for less heterogeneous people and reward is better for more heterogeneous people. In addition, the sufficient conditions for the best-shot and weakest-link cases suggest that some unintuitive results hold; even under the best-shot (weakest link) performance function, the bottom punishment (top reward) becomes better when the gap in the abilities of contestants becomes very small (large).

Suggested Citation

  • Kamijo, Yoshio, 2016. "Rewards versus punishments in additive, weakest-link, and best-shot contests," Journal of Economic Behavior & Organization, Elsevier, vol. 122(C), pages 17-30.
  • Handle: RePEc:eee:jeborg:v:122:y:2016:i:c:p:17-30
    DOI: 10.1016/j.jebo.2015.11.013
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    Cited by:

    1. Aner Sela, 2020. "Optimal allocations of prizes and punishments in Tullock contests," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(3), pages 749-771, September.
    2. Aner Sela & Maya Amiad, 2016. "The Optimal Allocation Of Punishments In Tullock Contests," Working Papers 1613, Ben-Gurion University of the Negev, Department of Economics.
    3. Aner Sela & Amit Yeshayahu, 2022. "Contests with identity-dependent externalities," Working Papers 2203, Ben-Gurion University of the Negev, Department of Economics.
    4. Liu, Bin & Lu, Jingfeng, 2023. "Optimal orchestration of rewards and punishments in rank-order contests," Journal of Economic Theory, Elsevier, vol. 208(C).

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    More about this item

    Keywords

    Contest theory; Heterogeneity; Punishment; Reward;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

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