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Ratings with Heterogeneous Preferences

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  • Jonathan Lafky
  • Robin Ng

Abstract

We examine how product ratings are interpreted in the presence of heterogeneous preferences among both raters and consumers. Raters with altruistic motives should rate for the benefit of future consumers, however an ambiguity arises when preferences are heterogeneous. Multiple equilibria exist in which ratings may reflect the preferences of raters or the preferences of future consumers. In an online experiment, we examine how ratings are selected by raters and interpreted by consumers, and how information about rater preferences or product attributes can influence equilibrium selection. We show how both raters and consumers update their evaluation of what a rating represents in each environment, doing so in similar ways.

Suggested Citation

  • Jonathan Lafky & Robin Ng, 2024. "Ratings with Heterogeneous Preferences," CRC TR 224 Discussion Paper Series crctr224_2024_594, University of Bonn and University of Mannheim, Germany.
  • Handle: RePEc:bon:boncrc:crctr224_2024_594
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    1. Tobias Gesche, 2022. "Reference‐price shifts and customer antagonism: Evidence from reviews for online auctions," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(3), pages 558-578, August.
    2. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    3. Steven Tadelis, 1999. "What's in a Name? Reputation as a Tradeable Asset," American Economic Review, American Economic Association, vol. 89(3), pages 548-563, June.
    4. Andrey Fradkin & Elena Grewal & David Holtz, 2021. "Reciprocity and Unveiling in Two-Sided Reputation Systems: Evidence from an Experiment on Airbnb," Marketing Science, INFORMS, vol. 40(6), pages 1013-1029, November.
    5. Halliday, Simon D. & Lafky, Jonathan, 2019. "Reciprocity through ratings: An experimental study of bias in evaluations," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 83(C).
    6. Davide Proserpio & Wendy Xu & Georgios Zervas, 2018. "You get what you give: theory and evidence of reciprocity in the sharing economy," Quantitative Marketing and Economics (QME), Springer, vol. 16(4), pages 371-407, December.
    7. Cai, Hongbin & Jin, Ginger Zhe & Liu, Chong & Zhou, Li-an, 2014. "Seller reputation: From word-of-mouth to centralized feedback," International Journal of Industrial Organization, Elsevier, vol. 34(C), pages 51-65.
    8. Yan Chen & F. Maxwell Harper & Joseph Konstan & Sherry Xin Li, 2010. "Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens," American Economic Review, American Economic Association, vol. 100(4), pages 1358-1398, September.
    9. Lingfang (Ivy) Li & Steven Tadelis & Xiaolan Zhou, 2020. "Buying reputation as a signal of quality: Evidence from an online marketplace," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 965-988, December.
    10. Lafky, Jonathan, 2014. "Why do people rate? Theory and evidence on online ratings," Games and Economic Behavior, Elsevier, vol. 87(C), pages 554-570.
    11. Dandan Qiao & Shun-Yang Lee & Andrew B. Whinston & Qiang Wei, 2020. "Financial Incentives Dampen Altruism in Online Prosocial Contributions: A Study of Online Reviews," Information Systems Research, INFORMS, vol. 31(4), pages 1361-1375, December.
    12. Dimitri,Nicola & Piga,Gustavo & Spagnolo,Giancarlo (ed.), 2006. "Handbook of Procurement," Cambridge Books, Cambridge University Press, number 9780521870733, October.
    13. Gary Bolton & Ben Greiner & Axel Ockenfels, 2013. "Engineering Trust: Reciprocity in the Production of Reputation Information," Management Science, INFORMS, vol. 59(2), pages 265-285, January.
    14. Christoph Schneider & Markus Weinmann & Peter N.C. Mohr & Jan vom Brocke, 2021. "When the Stars Shine Too Bright: The Influence of Multidimensional Ratings on Online Consumer Ratings," Management Science, INFORMS, vol. 67(6), pages 3871-3898, June.
    15. Hoyer, B. & van Straaten, D., 2022. "Anonymity and self-expression in online rating systems—An experimental analysis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    16. Luís Cabral & Ali Hortaçsu, 2010. "The Dynamics Of Seller Reputation: Evidence From Ebay," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 54-78, March.
    17. Samuel Bowles & Sandra Polania-Reyes, 2012. "Economic Incentives and Social Preferences: Substitutes or Complements?," Journal of Economic Literature, American Economic Association, vol. 50(2), pages 368-425, June.
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    More about this item

    Keywords

    Ratings and Reviews; Altruism;

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D64 - Microeconomics - - Welfare Economics - - - Altruism; Philanthropy; Intergenerational Transfers
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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