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Last Minute Feedback

Author

Listed:
  • Klein, Tobias J.
  • Lambertz, Christian
  • Spagnolo, Giancarlo
  • Stahl, Konrad O.

Abstract

Feedback mechanisms that allow partners to rate each other after a transaction are considered crucial for the success of anonymous internet trading platforms. We document an asymmetry in the feedback behavior on eBay, propose an explanation based on the micro structure of the feedback mechanism and the time when feedbacks are given, and support this explanation by findings from a large data set. Our analysis implies that the informational content of feedback records is likely to be low. The reason for this is that agents appear to leave feedbacks strategically. Negative feedbacks are given late, in the "last minute," or not given at all, most likely because of the fear of retaliative negative feedback. Conversely, positive feedbacks are given early in order to encourage reciprocation. Towards refining our insights into the observed pattern, we look separately at buyers and sellers, and relate the magnitude of the effects to the trading partners' experience.

Suggested Citation

  • Klein, Tobias J. & Lambertz, Christian & Spagnolo, Giancarlo & Stahl, Konrad O., 2006. "Last Minute Feedback," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 62, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    • Handle: RePEc:trf:wpaper:62
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    File URL: https://epub.ub.uni-muenchen.de/13488/1/62.pdf
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    References listed on IDEAS

    as
    1. Luis Cabral & Ali Hortacsu, 2004. "The Dynamics of Seller Reputation: Theory and Evidence from eBay," NBER Working Papers 10363, National Bureau of Economic Research, Inc.
    2. Paul Resnick & Richard Zeckhauser & John Swanson & Kate Lockwood, 2006. "The value of reputation on eBay: A controlled experiment," Experimental Economics, Springer;Economic Science Association, vol. 9(2), pages 79-101, June.
    3. Alvin E. Roth, 2002. "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," Econometrica, Econometric Society, vol. 70(4), pages 1341-1378, July.
    4. Bajari, Patrick & Hortacsu, Ali, 2003. "The Winner's Curse, Reserve Prices, and Endogenous Entry: Empirical Insights from eBay Auctions," RAND Journal of Economics, The RAND Corporation, vol. 34(2), pages 329-355, Summer.
    5. Daniel Houser & John Wooders, 2006. "Reputation in Auctions: Theory, and Evidence from eBay," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 15(2), pages 353-369, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Bargagliotti, Anna E. & Li, Lingfang (Ivy), 2009. "Decision Making Using Rating Systems: When Scale Meets Binary," MPRA Paper 16947, University Library of Munich, Germany.
    2. Klein, Tobias J. & Lambertz, Christian & Stahl, Konrad O., 2013. "Market Transparency, Adverse Selection, and Moral Hazard," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 426, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    3. Li, Lingfang (Ivy) & Xiao, Erte, 2010. "Money Talks? An Experimental Study of Rebate in Reputation System Design," MPRA Paper 22401, University Library of Munich, Germany.
    4. Klein, T.J. & Lambertz, C. & Stahl, K., 2013. "Adverse Selection and Moral Hazard in Anonymous Markets," Discussion Paper 2013-032, Tilburg University, Center for Economic Research.
    5. Tobias J. Klein & Christian Lambertz & Konrad O. Stahl, 2016. "Market Transparency, Adverse Selection, and Moral Hazard," Journal of Political Economy, University of Chicago Press, vol. 124(6), pages 1677-1713.
    6. David Masclet & Thierry Pénard, 2008. "Is the ebay feedback system really efficient ? an experimental study," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 200803, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    7. 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).
    8. Friederike Mengel & Axel Ockenfels & Werner Güth, 2006. "The Dynamics of Trust and Trustworthiness on EBay. An Evolutionary Analysis of Buyer Insurance and Seller Reputation," Papers on Strategic Interaction 2006-03, Max Planck Institute of Economics, Strategic Interaction Group.
    9. Werner Güth & Friederike Mengel & Axel Ockenfels, 2007. "An Evolutionary Analysis of Buyer Insurance and Seller Reputation in Online Markets," Theory and Decision, Springer, vol. 63(3), pages 265-282, November.
    10. Li, Lingfang (Ivy), 2010. "What is the cost of venting? Evidence from eBay," Economics Letters, Elsevier, vol. 108(2), pages 215-218, August.
    11. 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.

    More about this item

    Keywords

    eBay; reputation mechanism; strategic feedback behavior; informational content; reciprocity; fear of retaliation;

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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