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Online Auction Demand

Author

Listed:
  • Song Yao

    () (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Carl F. Mela

    () (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

Abstract

With $40 billion in annual gross merchandise volume, electronic auctions comprise a substantial and growing sector of the retail economy. Using unique data on Celtic coins, we estimate a structural model of buyer and seller behavior via Markov chain Monte Carlo (MCMC) with data augmentation. Results indicate that buyer valuations are affected by item, seller, and auction characteristics; buyer costs are affected by bidding behavior; and seller costs are affected by item characteristics and the number of listings. The model enables us to compute fee elasticities even though there is no variation in fees in our data. We find that commission elasticities exceed per item fee elasticities because they target high-value sellers and enhance their likelihood of listing. By targeting commission reductions to high-value sellers, auction house revenues can be increased by 3.9%. Computing customer value, we find that attrition of the largest seller would decrease fees paid to the auction house by $97. Given the seller paid $127 in fees, competitive effects offset only 24% of those fees. In contrast, competition offsets 81% of the buyer attrition effect. In both events, the auction house would overvalue its customers by neglecting competitive effects.

Suggested Citation

  • Song Yao & Carl F. Mela, 2008. "Online Auction Demand," Marketing Science, INFORMS, vol. 27(5), pages 861-885, 09-10.
  • Handle: RePEc:inm:ormksc:v:27:y:2008:i:5:p:861-885
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    File URL: http://dx.doi.org/10.1287/mksc.1070.0351
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    References listed on IDEAS

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    Cited by:

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    2. repec:eee:jouret:v:92:y:2016:i:1:p:96-108 is not listed on IDEAS
    3. Jason Shachat & Lijia Wei, 2012. "Procuring Commodities: First-Price Sealed-Bid or English Auctions?," Marketing Science, INFORMS, vol. 31(2), pages 317-333, March.
    4. repec:eee:ijrema:v:28:y:2011:i:2:p:76-88 is not listed on IDEAS
    5. Jiang, Yuanchun & Shang, Jennifer & Liu, Yezheng & May, Jerrold, 2015. "Redesigning promotion strategy for e-commerce competitiveness through pricing and recommendation," International Journal of Production Economics, Elsevier, vol. 167(C), pages 257-270.
    6. S. Sriram & Puneet Manchanda & Mercedes Bravo & Junhong Chu & Liye Ma & Minjae Song & Scott Shriver & Upender Subramanian, 2015. "Platforms: a multiplicity of research opportunities," Marketing Letters, Springer, vol. 26(2), pages 141-152, June.
    7. Anja Lambrecht & Avi Goldfarb & Alessandro Bonatti & Anindya Ghose & Daniel Goldstein & Randall Lewis & Anita Rao & Navdeep Sahni & Song Yao, 2014. "How do firms make money selling digital goods online?," Marketing Letters, Springer, vol. 25(3), pages 331-341, September.
    8. Ronald Peeters & Martin Strobel & Dries Vermeulen & Markus Walzl, 2016. "The Impact of the Irrelevant: Temporary Buy-Options and Bidding Behavior in Auctions," Games, MDPI, Open Access Journal, vol. 7(1), pages 1-19, March.

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