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The Timing of Bids in Internet Auctions: Market Design, Bidder Behavior, and Artificial Agents

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  • Axel Ockenfels
  • Alvin E. Roth

Abstract

Many bidders in eBay employ bidding strategies that involve late bids, incremental bids, or both. Based on field evidence, we discuss the manner in which late bids are caused both by sophisticated, strategic reasoning and by irrationality and inexperience, the interaction of late bidding and incremental bidding, and the relation between market design and artificial agent design.

Suggested Citation

  • Axel Ockenfels & Alvin E. Roth, 2001. "The Timing of Bids in Internet Auctions: Market Design, Bidder Behavior, and Artificial Agents," Papers on Strategic Interaction 2002-33, Max Planck Institute of Economics, Strategic Interaction Group.
    • Handle: RePEc:esi:discus:2002-33
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    References listed on IDEAS

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    1. Ockenfels, Axel & Roth, Alvin E., 2006. "Late and multiple bidding in second price Internet auctions: Theory and evidence concerning different rules for ending an auction," Games and Economic Behavior, Elsevier, vol. 55(2), pages 297-320, May.
    2. Dan Ariely & Axel Ockenfels & Alvin E. Roth, 2005. "An Experimental Analysis of Ending Rules in Internet Auctions," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 890-907, Winter.
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    Cited by:

    1. Dan Ariely & Axel Ockenfels & Alvin E. Roth, 2005. "An Experimental Analysis of Ending Rules in Internet Auctions," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 890-907, Winter.
    2. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.
    3. Nicola Dimitri, 2007. "Last minute bidding equilibrium in second price internet auctions," Department of Economic Policy, Finance and Development (DEPFID) University of Siena 001, Department of Economic Policy, Finance and Development (DEPFID), University of Siena.
    4. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    5. Axel Ockenfels, 2002. "New Institutional Structures on the Internet: The Economic Design of Online Auctions," Papers on Strategic Interaction 2002-08, Max Planck Institute of Economics, Strategic Interaction Group.
    6. Yu Zhang & Jingping Gu & Qi Li, 2011. "Nonparametric panel estimation of online auction price processes," Empirical Economics, Springer, vol. 40(1), pages 51-68, February.
    7. Bramsen, Jens-Martin, 2008. "Learning to bid, but not to quit – Experience and Internet auctions," MPRA Paper 14815, University Library of Munich, Germany.
    8. Carsten Schmidt & Jens Grossklags, 2004. "Interaction of Human and Artificial Agents on Double Auction Markets - Simulations and Laboratory Experiments," Papers on Strategic Interaction 2003-22, Max Planck Institute of Economics, Strategic Interaction Group.
    9. Nicola Dimitri, 2022. "Last minute only bidding is implausible in eBay sealed bid type-of-auctions," Electronic Commerce Research, Springer, vol. 22(2), pages 225-239, June.
    10. Jens Grossklags & Carsten Schmidt, 2002. "Artificial Software Agents on Thin Double Auction Markets - A Human Trader Experiment," Papers on Strategic Interaction 2002-45, Max Planck Institute of Economics, Strategic Interaction Group.
    11. Bramsen, Jens-Martin, 2008. "Bid early and get it cheap - Timing effects in Internet auctions," MPRA Paper 14811, University Library of Munich, Germany.

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