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Vertically Differentiated Simultaneous Vickrey Auctions: Theory and Experimental Evidence

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  • Ravi Bapna

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455; and Srini Raju Centre for IT and the Networked Economy, Indian School of Business, Hyderabad 500032, India)

  • Chrysanthos Dellarocas

    (School of Management, Boston University, Boston, Massachusetts 02215)

  • Sarah Rice

    (School of Business, University of Connecticut, Storrs, Connecticut 06269)

Abstract

We study settings where a number of sellers simultaneously offer vertically differentiated Vickrey auctions for imperfect substitute goods to unit-demand buyers. Vertical differentiation can arise from differences in item quality, item value certainty, seller reliability, or a combination of these factors. We characterize the form of the bidding equilibria and derive expressions for the corresponding allocative efficiency and expected seller revenue. When bidders are restricted to submit at most one bid, our theory predicts the existence of a unique Bayes-Nash equilibrium that resembles a form of probabilistic "mating-of-likes." Allowing unit-demand bidders to place an arbitrary number of bids induces complex strategy profiles where bidders place positive bids in all available auctions. Higher bidder types tend to follow more targeted strategies, focusing their "serious" bids on fewer and, generally, higher quality auctions. The nature of the bidding equilibria introduces allocative inefficiencies that arise from the lack of coordination in auction selection among bidders. We test our theoretical propositions in a controlled laboratory experiment while also utilizing a domain specific risk score to help assess how the bidders' risk type affects their bidding behavior. In support of our theory we find evidence of a probabilistic assortative matching between bidder and auction types. We also find that low risk type bidders tend to crowd on the highest auction and will pay a premium for the certainty it offers, whereas high risk type bidders fail to appropriately adjust for risk associated with the lowest auction, leading to overbidding. These lead to an interesting focal anomaly whereby bids are concentrated on the highest and lowest auctions, bypassing intermediate auctions.

Suggested Citation

  • Ravi Bapna & Chrysanthos Dellarocas & Sarah Rice, 2010. "Vertically Differentiated Simultaneous Vickrey Auctions: Theory and Experimental Evidence," Management Science, INFORMS, vol. 56(7), pages 1074-1092, July.
  • Handle: RePEc:inm:ormnsc:v:56:y:2010:i:7:p:1074-1092
    DOI: 10.1287/mnsc.1100.1176
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    Cited by:

    1. Yili Hong & Chong (Alex) Wang & Paul A. Pavlou, 2016. "Comparing Open and Sealed Bid Auctions: Evidence from Online Labor Markets," Information Systems Research, INFORMS, vol. 27(1), pages 49-69, March.
    2. Liangfei Qiu & Arunima Chhikara & Asoo Vakharia, 2021. "Multidimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Information Systems Research, INFORMS, vol. 32(3), pages 876-894, September.
    3. Timothy N. Cason & Karthik N. Kannan & Ralph Siebert, 2011. "An Experimental Study of Information Revelation Policies in Sequential Auctions," Management Science, INFORMS, vol. 57(4), pages 667-688, April.
    4. Matthew J. Hashim & Karthik N. Kannan & Sandra Maximiano, 2017. "Information Feedback, Targeting, and Coordination: An Experimental Study," Information Systems Research, INFORMS, vol. 28(2), pages 289-308, June.
    5. Liangfei Qiu & Asoo Vakharia & Arunima Chhikara, 2019. "Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Working Papers 19-01, NET Institute.
    6. Chrysanthos Dellarocas, 2012. "Double Marginalization in Performance-Based Advertising: Implications and Solutions," Management Science, INFORMS, vol. 58(6), pages 1178-1195, June.
    7. Ralf Buckley & Mary-Ann Cooper, 2021. "Assortative Matching of Tourists and Destinations: Agents or Algorithms?," Sustainability, MDPI, vol. 13(4), pages 1-10, February.
    8. Eric Overby & Karthik Kannan, 2015. "How Reduced Search Costs and the Distribution of Bidder Participation Affect Auction Prices," Management Science, INFORMS, vol. 61(6), pages 1398-1420, June.
    9. Thomas Kittsteiner & Marion Ott & Richard Steinberg, 2022. "Competing Combinatorial Auctions," Information Systems Research, INFORMS, vol. 33(4), pages 1130-1137, December.
    10. Tan, Gary & Cheong, Chee Seng & Zurbruegg, Ralf, 2019. "National culture and individual trading behavior," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 357-370.
    11. Kevin Yili Hong & Alex Chong Wang & Paul A. Pavlou, 2013. "How does Bid Visibility Matter in Buyer-Determined Auctions? Comparing Open and Sealed Bid Auctions in Online Labor Markets," Working Papers 13-05, NET Institute.

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