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The Impact of Fake Reviews on Reputation Systems and Efficiency

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  • Krügel, Jan Philipp
  • Paetzel, Fabian

Abstract

Online interactions are frequently governed by reputation systems that allow users to evaluate each other after an interaction. Effective reputation systems can increase trust and may improve efficiency in market settings. In recent years, however, fake reviews have become increasingly prevalent. Since it is difficult to clearly identify fake reviews in field studies, we design a lab10 oratory experiment. Using a repeated public good game with a reputation system, we study (i) how feedback manipulation influences the reliability of average ratings and (ii) whether the existence of manipulated ratings reduces efficiency. We find that feedback manipulation generally decreases the reliability of average ratings in comparison to a control treatment where cheating is not possible. When manipulation is possible and free, average ratings become less 15 reliable, expectations are lower and both cooperation and efficiency are significantly reduced. When there are costs of manipulation, however, average ratings are more reliable and contributions and efficiency are not impaired. Interestingly, this is the case even when costs of manipulation are comparatively low.

Suggested Citation

  • Krügel, Jan Philipp & Paetzel, Fabian, 2021. "The Impact of Fake Reviews on Reputation Systems and Efficiency," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242415, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc21:242415
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    1. 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.
    2. Susan Athey & Michael Luca, 2019. "Economists (and Economics) in Tech Companies," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 209-230, Winter.
    3. Xiaofei Pan & Daniel Houser, 2017. "Social approval, competition and cooperation," Experimental Economics, Springer;Economic Science Association, vol. 20(2), pages 309-332, June.
    4. Gary Charness & David Masclet & Marie Claire Villeval, 2014. "The Dark Side of Competition for Status," Management Science, INFORMS, vol. 60(1), pages 38-55, January.
    5. Fischbacher, Urs & Gachter, Simon & Fehr, Ernst, 2001. "Are people conditionally cooperative? Evidence from a public goods experiment," Economics Letters, Elsevier, vol. 71(3), pages 397-404, June.
    6. Verena Dorner & Marcus Giamattei & Matthias Greiff, 2020. "The Market for Reviews: Strategic Behavior of Online Product Reviewers with Monetary Incentives," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(3), pages 397-435, July.
    7. 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.
    8. Greiff, Matthias & Paetzel, Fabian, 2016. "Second-order beliefs in reputation systems with endogenous evaluations – an experimental study," Games and Economic Behavior, Elsevier, vol. 97(C), pages 32-43.
    9. Urs Fischbacher & Simon Gachter, 2010. "Social Preferences, Beliefs, and the Dynamics of Free Riding in Public Goods Experiments," American Economic Review, American Economic Association, vol. 100(1), pages 541-556, March.
    10. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    11. Johannes Abeler & Daniele Nosenzo & Collin Raymond, 2019. "Preferences for Truth‐Telling," Econometrica, Econometric Society, vol. 87(4), pages 1115-1153, July.
    12. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    13. Urs Fischbacher & Franziska Föllmi-Heusi, 2013. "Lies In Disguise—An Experimental Study On Cheating," Journal of the European Economic Association, European Economic Association, vol. 11(3), pages 525-547, June.
    14. Gary Charness & David Masclet & Marie Claire Villeval, 2014. "The Dark Side of Competition for Status (preprint)," Working Papers halshs-01090241, HAL.
    15. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    16. Matthias Greiff & Fabian Paetzel, 2015. "Incomplete Information Strengthens The Effectiveness Of Social Approval," Economic Inquiry, Western Economic Association International, vol. 53(1), pages 557-573, January.
    17. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    18. Xiang Hui & Maryam Saeedi & Zeqian Shen & Neel Sundaresan, 2016. "Reputation and Regulations: Evidence from eBay," Management Science, INFORMS, vol. 62(12), pages 3604-3616, December.
    19. Gary E. Bolton & David J. Kusterer & Johannes Mans, 2019. "Inflated Reputations: Uncertainty, Leniency, and Moral Wiggle Room in Trader Feedback Systems," Management Science, INFORMS, vol. 65(11), pages 5371-5391, November.
    20. Stahl, Dale O., 2013. "An experimental test of the efficacy of a simple reputation mechanism to solve social dilemmas," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 116-124.
    21. David Masclet & Thierry P鮡rd, 2012. "Do reputation feedback systems really improve trust among anonymous traders? An experimental study," Applied Economics, Taylor & Francis Journals, vol. 44(35), pages 4553-4573, December.
    22. Michael Luca, 2017. "Designing Online Marketplaces: Trust and Reputation Mechanisms," Innovation Policy and the Economy, University of Chicago Press, vol. 17(1), pages 77-93.
    23. Bock, Olaf & Baetge, Ingmar & Nicklisch, Andreas, 2014. "hroot: Hamburg Registration and Organization Online Tool," European Economic Review, Elsevier, vol. 71(C), pages 117-120.
    24. Steven Tadelis, 2016. "Reputation and Feedback Systems in Online Platform Markets," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 321-340, October.
    25. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
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    More about this item

    Keywords

    Reputation Systems; Fake Reviews; Reliability of Ratings; Efficiency;
    All these keywords.

    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
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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