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Reputation, Trust, and Rebates: How Online Auction Markets Can Improve Their Feedback Mechanisms

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Abstract

Reputation systems constitute an important institution, helping sustain trust in online auction markets. However, only half of buyers leave feedback after transactions, and nearly all feedback is positive. In this paper, I propose a mechanism whereby sellers can provide rebates (not necessarily in monetary form) to buyers contingent upon buyers' provision of reports. Using a game theoretical model, I show how the mechanism can increase unbiased reporting. There exists a pooling equilibrium where both good and bad sellers choose the rebate option, even though their true types are revealed through feedback. The mechanism also induces bad sellers to improve the quality of the contract.

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  • Lingfang (Ivy) Li, 2010. "Reputation, Trust, and Rebates: How Online Auction Markets Can Improve Their Feedback Mechanisms," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 19(2), pages 303-331, June.
    • Handle: RePEc:bla:jemstr:v:19:y:2010:i:2:p:303-331
    DOI: 10.1111/j.1530-9134.2010.00253.x
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    Cited by:

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    2. Annika Veh & Markus Göbel & Rick Vogel, 2019. "Corporate reputation in management research: a review of the literature and assessment of the concept," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 315-353, December.
    3. Andrey Fradkin & David Holtz, 2023. "Do Incentives to Review Help the Market? Evidence from a Field Experiment on Airbnb," Marketing Science, INFORMS, vol. 42(5), pages 853-865, September.
    4. Li, Lingfang (Ivy), 2010. "What is the cost of venting? Evidence from eBay," Economics Letters, Elsevier, vol. 108(2), pages 215-218, August.
    5. Robert Gazzale & Tapan Khopkar, 2011. "Remain silent and ye shall suffer: seller exploitation of reticent buyers in an experimental reputation system," Experimental Economics, Springer;Economic Science Association, vol. 14(2), pages 273-285, May.
    6. Luís Cabral & Lingfang (Ivy) Li, 2015. "A Dollar for Your Thoughts: Feedback-Conditional Rebates on eBay," Management Science, INFORMS, vol. 61(9), pages 2052-2063, September.
    7. 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.
    8. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    9. Kaiwei Zhang & Xi Weng & Xienan Cheng, 2022. "Optimal Pricing Schemes in the Presence of Social Learning and Costly Reporting," Papers 2211.07362, arXiv.org, revised Dec 2023.
    10. 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.
    11. Christina Aperjis & Ramesh Johari, 2010. "Optimal Windows for Aggregating Ratings in Electronic Marketplaces," Management Science, INFORMS, vol. 56(5), pages 864-880, May.

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