IDEAS home Printed from https://ideas.repec.org/p/tut/cremwp/200803.html
   My bibliography  Save this paper

Is the ebay feedback system really efficient ? an experimental study

Author

Listed:
  • David Masclet

    (CREM - CNRS - CIRANO)

  • Thierry Pénard

    (CREM – CNRS - University of Rennes 1)

Abstract

The eBay Feedback Forum is claimed to be a crucial component of the success of eBay. Many empirical studies have found that this feedback system exerts a deterrent effect on the opportunistic behavior the Internet's anonymity may incite buyers and sellers to adopt. The feedback system in place on eBay is however far from being perfect and may be especially vulnerable to strategic ratings (or nonratings) that might reduce the informational content of feedback profiles. This article aims to examine the efficiency of the eBay feedback system, through a set of experiments based on the trust game. Our experimental design consists of four different treatments. The baseline treatment corresponds to a finite repeated simultaneous trust game. The second treatment, called “eBay rating” is identical to the baseline treatment except that we added a second stage in which the players have the opportunity of rating their partner. In this treatment, each participant is given the choice to either evaluate immediately or wait, knowing that only one rating will be accepted. The third treatment, called "Sequential rating" is identical to the “eBay rating” treatment, except that the order in which players evaluate one another is randomly determined by the computer. Finally in the fourth treatment, called “Simultaneous rating”, both players are required to make their rating decisions simultaneously. Our experimental results indicate that the eBay feedback system could be improved by either constraining partners to leave ratings simultaneously or by predetermining the rating sequence.

Suggested Citation

  • 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.
  • Handle: RePEc:tut:cremwp:200803
    as

    Download full text from publisher

    File URL: https://ged.univ-rennes1.fr/nuxeo/site/esupversions/d6615bec-75f1-4454-afb3-b3ac875c7e90
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Gary E. Bolton & Elena Katok & Axel Ockenfels, 2004. "How Effective Are Electronic Reputation Mechanisms? An Experimental Investigation," Management Science, INFORMS, vol. 50(11), pages 1587-1602, November.
    3. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    4. Klein, T.J. & Lambertz, C. & Spagnolo, G. & Stahl, K.O., 2006. "Last minute feedback," Other publications TiSEM 10afaa8e-ec7f-4269-9535-a, Tilburg University, School of Economics and Management.
    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.
    6. 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.
    7. Dimitri,Nicola & Piga,Gustavo & Spagnolo,Giancarlo (ed.), 2006. "Handbook of Procurement," Cambridge Books, Cambridge University Press, number 9780521870733, January.
    8. 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.
    9. Berg Joyce & Dickhaut John & McCabe Kevin, 1995. "Trust, Reciprocity, and Social History," Games and Economic Behavior, Elsevier, vol. 10(1), pages 122-142, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lumeau, Marianne & Masclet, David & Penard, Thierry, 2015. "Reputation and social (dis)approval in feedback mechanisms: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 127-140.
    2. Matthias Wibral, 2015. "Identity changes and the efficiency of reputation systems," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 408-431, September.
    3. Judy E. Scott & Dawn G. Gregg & Jae Hoon Choi, 2015. "Lemon complaints: When online auctions go sour," Information Systems Frontiers, Springer, vol. 17(1), pages 177-191, February.
    4. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    5. Gesche, Tobias, 2018. "Reference Price Shifts and Customer Antagonism: Evidence from Reviews for Online Auctions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181650, Verein für Socialpolitik / German Economic Association.
    6. Sarah C. Rice, 2012. "Reputation and Uncertainty in Online Markets: An Experimental Study," Information Systems Research, INFORMS, vol. 23(2), pages 436-452, June.
    7. Naoki Masuda & Mitsuhiro Nakamura, 2012. "Coevolution of Trustful Buyers and Cooperative Sellers in the Trust Game," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-11, September.
    8. 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.
    9. 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.
    10. 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.
    11. Emma von Essen & Jonas Karlsson, 2019. "The effect of competition on discrimination in online markets—Anonymity and selection," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-18, August.
    12. José Canals-Cerdá, 2012. "The value of a good reputation online: an application to art auctions," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(1), pages 67-85, February.
    13. Chrysanthos Dellarocas & Charles A. Wood, 2008. "The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias," Management Science, INFORMS, vol. 54(3), pages 460-476, March.
    14. 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.
    15. Britta Hoyer & Dirk van Straaten, 2021. "Anonymity and Self-Expression in Online Rating Systems - An Experimental Analysis," Working Papers Dissertations 70, Paderborn University, Faculty of Business Administration and Economics.
    16. Natalia Levina & Manuel Arriaga, 2014. "Distinction and Status Production on User-Generated Content Platforms: Using Bourdieu’s Theory of Cultural Production to Understand Social Dynamics in Online Fields," Information Systems Research, INFORMS, vol. 25(3), pages 468-488, September.
    17. Przepiorka, Wojtek, 2014. "Reputation in offline and online markets: Solutions to trust problems in social and economic exchange," economic sociology. perspectives and conversations, Max Planck Institute for the Study of Societies, vol. 16(1), pages 4-10.
    18. Jolivet, Grégory & Jullien, Bruno & Postel-Vinay, Fabien, 2016. "Reputation and prices on the e-market: Evidence from a major French platform," International Journal of Industrial Organization, Elsevier, vol. 45(C), pages 59-75.
    19. Lingfang (Ivy) Li & Erte Xiao, 2014. "Money Talks: Rebate Mechanisms in Reputation System Design," Management Science, INFORMS, vol. 60(8), pages 2054-2072, August.
    20. Andreas J. Steur & Mischa Seiter, 2021. "Properties of feedback mechanisms on digital platforms: an exploratory study," Journal of Business Economics, Springer, vol. 91(4), pages 479-526, May.

    More about this item

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tut:cremwp:200803. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: GERMAIN Lucie (email available below). General contact details of provider: https://edirc.repec.org/data/crmrefr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.