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Commentary--Bidders' Experience and Learning in Online Auctions: Issues and Implications

  • Kannan Srinivasan


    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Xin Wang


    (International Business School, Brandeis University, Waltham, Massachusetts 02454)

Registered author(s):

    This study explores the implications of rejecting the sealed-bid abstraction proposed by Zeithammer and Adams [Zeithammer, R., C. Adams. 2010. The sealed-bid abstraction in online auctions. Marketing Sci. 29(6) 964-987]. Using a conditional order statistic model that relies on the joint distribution of the top two proxy bids of an auction, Zeithammer and Adams show that inexperienced bidders' reactive bidding is the main cause of the rejection of the sealed-bid abstraction. Their empirical study suggests that a large percentage of bidders reactively bid, and there is weak evolutionary pressure for bidders to converge to sealed bidding. We discuss theoretical implications of this rejection and the role of bidder experience, as well as inferences about bidder learning. Tracking an inexperienced bidder's bidding behavior over time, we show that bidders learn and their bidding strategy gravitates toward rational bidding. Potential biases in bidder experience measurement and bidder learning can be assessed using a cross-sectional, time-series data set that tracks a random sample of new eBay bidders. Learning speed is faster with their complete bidding history rather than feedback ratings or winning observations only. We highlight the importance of proper measures of bidder experience and its effect on bidding strategy evolutions, both of which play important roles in clarifying bidding behavior in online auctions.

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    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 29 (2010)
    Issue (Month): 6 (11-12)
    Pages: 988-993

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    Handle: RePEc:inm:ormksc:v:29:y:2010:i:6:p:988-993
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    1. Axel Ockenfels & Alvin E. Roth, 2003. "Late and Multiple Bidding in Second Price Internet Auctions: Theory and Evidence Concerning Different Rules for Ending an Auction," CESifo Working Paper Series 992, CESifo Group Munich.
    2. Donald B. Hausch, 1987. "An Asymmetric Common-Value Auction Model," RAND Journal of Economics, The RAND Corporation, vol. 18(4), pages 611-621, Winter.
    3. Marshall Robert C. & Meurer Michael J. & Richard Jean-Francois & Stromquist Walter, 1994. "Numerical Analysis of Asymmetric First Price Auctions," Games and Economic Behavior, Elsevier, vol. 7(2), pages 193-220, September.
    4. Xin Wang & Ye Hu, 2009. "The effect of experience on Internet auction bidding dynamics," Marketing Letters, Springer, vol. 20(3), pages 245-261, September.
    5. Alvin E. Roth & Axel Ockenfels, 2002. "Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet," American Economic Review, American Economic Association, vol. 92(4), pages 1093-1103, September.
    6. Eric Maskin & John Riley, 2000. "Asymmetric Auctions," Review of Economic Studies, Oxford University Press, vol. 67(3), pages 413-438.
    7. Epple, D. & Argote, L. & Darr, E.D., 1995. "The Acquisition, Transfer and Depreciation of Knowledge in Service Organisations: Productivity in Franchises," GSIA Working Papers 1995-16, Carnegie Mellon University, Tepper School of Business.
    8. Robert Zeithammer & Christopher Adams, 2010. "The Sealed-Bid Abstraction in Online Auctions," Marketing Science, INFORMS, vol. 29(6), pages 964-987, 11-12.
    9. Eric T. Bradlow & Young-Hoon Park, 2007. "Bayesian Estimation of Bid Sequences in Internet Auctions Using a Generalized Record-Breaking Model," Marketing Science, INFORMS, vol. 26(2), pages 218-229, 03-04.
    10. Eric D. Darr & Linda Argote & Dennis Epple, 1995. "The Acquisition, Transfer, and Depreciation of Knowledge in Service Organizations: Productivity in Franchises," Management Science, INFORMS, vol. 41(11), pages 1750-1762, November.
    11. 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 329-55, Summer.
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