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Revenue non-equivalence between auctions with soft and hard closing mechanisms: New evidence from Yahoo!

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  • Glover, Brent
  • Raviv, Yaron
Abstract
We use a unique dataset to examine the revenue differences between auctions with a hard-close ending rule versus those with a soft-close ending rule. We find that selling items using the soft-close rule increases the selling price by an amount between $25 and $44 (or 13–20 percent) over the hard-close format. One possible theoretical explanation for these results is that the hard-close ending rule accommodates the practice of sniping, which leads to a lower expected selling price. We find empirically that a lack of experience could help to explain why, in spite of the revenue differences, some sellers select the hard-close ending rule.

Suggested Citation

  • Glover, Brent & Raviv, Yaron, 2012. "Revenue non-equivalence between auctions with soft and hard closing mechanisms: New evidence from Yahoo!," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 129-136.
    • Handle: RePEc:eee:jeborg:v:81:y:2012:i:1:p:129-136
    DOI: 10.1016/j.jebo.2011.09.003
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    References listed on IDEAS

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    4. 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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    7. William Vickrey, 1961. "Counterspeculation, Auctions, And Competitive Sealed Tenders," Journal of Finance, American Finance Association, vol. 16(1), pages 8-37, March.
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    9. Jennifer Brown & John Morgan, 2009. "How Much Is a Dollar Worth? Tipping versus Equilibrium Coexistence on Competing Online Auction Sites," Journal of Political Economy, University of Chicago Press, vol. 117(4), pages 668-700, August.
    10. 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.
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    Cited by:

    1. Marie BLUM & Régis BLAZY, 2021. "The three stages of an auction: how do the bid dynamics influence auction prices? Evidence from live art auctions," Working Papers of LaRGE Research Center 2021-10, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
    2. Chen, Kong-Pin & Lai, Hung-pin & Yu, Ya-Ting, 2018. "The seller's listing strategy in online auctions: Evidence from eBay," International Journal of Industrial Organization, Elsevier, vol. 56(C), pages 107-144.
    3. Matthew Backus & Tom Blake & Dimitriy V. Masterov & Steven Tadelis, 2015. "Is Sniping A Problem For Online Auction Markets?," NBER Working Papers 20942, National Bureau of Economic Research, Inc.
    4. 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.
    5. Carpenter, Jeffrey & Holmes, Jessica & Matthews, Peter Hans, 2011. "Jumping and sniping at the silents: Does it matter for charities?," Journal of Public Economics, Elsevier, vol. 95(5-6), pages 395-402, June.
    6. Wen Cao & Qinyang Sha & Zhiyong Yao & Dingwei Gu & Xiang Shao, 2019. "Sniping in soft-close online auctions: empirical evidence from overstock," Marketing Letters, Springer, vol. 30(2), pages 179-191, June.
    7. Stylianos Despotakis & Isa Hafalir & R. Ravi & Amin Sayedi, 2017. "Expertise in Online Markets," Management Science, INFORMS, vol. 63(11), pages 3895-3910, November.
    8. Yoshimoto, Hisayuki & Nakabayashi, Jun, 2019. "Search and resale frictions in a two-sided online platform: A case of multi-use assets," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 85-105.

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    More about this item

    Keywords

    Auctions; Sniping; Ending rules;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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