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Motivational Ratings
[Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions]

Author

Listed:
  • Johannes Hörner
  • Nicolas S Lambert

Abstract

Performance evaluation (“rating”) systems not only provide information to users but also motivate the rated worker. This article solves for the optimal (effort-maximizing) rating within the standard career concerns framework. We prove that this rating is a linear function of past observations. The rating, however, is not a Markov process, but rather the sum of two Markov processes. We show how it combines information of different types and vintages. An increase in effort may adversely affect some (but not all) future ratings.

Suggested Citation

  • Johannes Hörner & Nicolas S Lambert, 2021. "Motivational Ratings [Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1892-1935.
    • Handle: RePEc:oup:restud:v:88:y:2021:i:4:p:1892-1935.
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    File URL: http://hdl.handle.net/10.1093/restud/rdaa070
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    Cited by:

    1. Allen Vong, 2025. "Dynamic Mediation and Moral Hazard: From Private To Public Communication," Papers 2511.02436, arXiv.org, revised Dec 2025.
    2. Hakenes, Hendrik & Katolnik, Svetlana, 2017. "On the incentive effects of job rotation," European Economic Review, Elsevier, vol. 98(C), pages 424-441.
    3. Ichihashi, Shota, 2025. "Information and policing," Journal of Economic Theory, Elsevier, vol. 225(C).
    4. Sergey Kovbasyuk & Giancarlo Spagnolo, 2024. "Memory and Markets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(3), pages 1775-1806.
    5. Yasui, Yuta, 2021. "Controlling Fake Reviews," MPRA Paper 108177, University Library of Munich, Germany.
    6. Kaya, Ayça & Roy, Santanu, 2022. "Market screening with limited records," Games and Economic Behavior, Elsevier, vol. 132(C), pages 106-132.
    7. Yildirim, Huseyin, 2025. "The economics of career concerns in teamwork," Journal of Economic Theory, Elsevier, vol. 226(C).
    8. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    9. Kuo, Fang-Chang, 2024. "Shirking with good reputation? Evidence from hotel industry," International Journal of Industrial Organization, Elsevier, vol. 97(C).
    10. Tan, Teck Yong, 2023. "Optimal transparency of monitoring capability," Journal of Economic Theory, Elsevier, vol. 209(C).
    11. Gradwohl, Ronen & Jelnov, Artyom, 2024. "Partial credence goods on review platforms," Games and Economic Behavior, Elsevier, vol. 148(C), pages 517-534.

    More about this item

    Keywords

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    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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