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Buy-It-Now or Take-a-Chance: Price Discrimination Through Randomized Auctions

Author

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  • L. Elisa Celis

    () (École Polytechnique Fédérale de Lausanne, CH-1015, Lausanne, Switzerland)

  • Gregory Lewis

    () (Microsoft Research New England, Cambridge, Massachusetts 02142)

  • Markus Mobius

    () (Microsoft Research New England, Cambridge, Massachusetts 02142)

  • Hamid Nazerzadeh

    () (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

Increasingly detailed consumer information makes sophisticated price discrimination possible. At fine levels of aggregation, demand may not obey standard regularity conditions. We propose a new randomized sales mechanism for such environments. Bidders can “buy-it-now” at a posted price, or “take-a-chance” in an auction where the top d > 1 bidders are equally likely to win. The randomized allocation incentivizes high-valuation bidders to buy-it-now. We analyze equilibrium behavior and apply our analysis to advertiser bidding data from Microsoft Advertising Exchange. In counterfactual simulations, our mechanism increases revenue by 4.4% and consumer surplus by 14.5% compared to an optimal second-price auction. This paper was accepted by Assaf Zeevi, stochastic models and simulation.

Suggested Citation

  • L. Elisa Celis & Gregory Lewis & Markus Mobius & Hamid Nazerzadeh, 2014. "Buy-It-Now or Take-a-Chance: Price Discrimination Through Randomized Auctions," Management Science, INFORMS, vol. 60(12), pages 2927-2948, December.
  • Handle: RePEc:inm:ormnsc:v:60:y:2014:i:12:p:2927-2948
    DOI: 10.1287/mnsc.2014.2009
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    References listed on IDEAS

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    1. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    2. Bulow, Jeremy & Klemperer, Paul, 1996. "Auctions versus Negotiations," American Economic Review, American Economic Association, vol. 86(1), pages 180-194, March.
    3. Bergemann, Dirk & Pesendorfer, Martin, 2007. "Information structures in optimal auctions," Journal of Economic Theory, Elsevier, vol. 137(1), pages 580-609, November.
    4. Péter Eső & Balázs Szentes, 2007. "Optimal Information Disclosure in Auctions and the Handicap Auction," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 705-731.
    5. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    6. Avi Goldfarb & Catherine Tucker, 2011. "Online Display Advertising: Targeting and Obtrusiveness," Marketing Science, INFORMS, vol. 30(3), pages 389-404, 05-06.
    7. Stanley Reynolds & John Wooders, 2009. "Auctions with a buy price," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 38(1), pages 9-39, January.
    8. Randall Lewis & Justin M. Rao & David H. Reiley, 2015. "Measuring the Effects of Advertising: The Digital Frontier," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 191-218, National Bureau of Economic Research, Inc.
    9. Ostrovsky, Michael & Schwarz, Michael, 2009. "Reserve Prices in Internet Advertising Auctions: A Field Experiment," Research Papers 2054, Stanford University, Graduate School of Business.
    10. Madarász, Kristóf & Prat, Andrea, 2010. "Screening with an Approximate Type Space," CEPR Discussion Papers 7900, C.E.P.R. Discussion Papers.
    11. Lewis, Tracy R & Sappington, David E M, 1994. "Supplying Information to Facilitate Price Discrimination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(2), pages 309-327, May.
    12. Budish, Eric B. & Takeyama, Lisa N., 2001. "Buy prices in online auctions: irrationality on the internet?," Economics Letters, Elsevier, vol. 72(3), pages 325-333, September.
    13. R. McAfee, 2011. "The Design of Advertising Exchanges," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 39(3), pages 169-185, November.
    14. Milgrom, Paul & Shannon, Chris, 1994. "Monotone Comparative Statics," Econometrica, Econometric Society, vol. 62(1), pages 157-180, January.
    15. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2012. "Auctions for Online Display Advertising Exchanges: Approximations and Design," Working Papers 12-11, NET Institute.
    16. Pascal Courty & Li Hao, 2000. "Sequential Screening," Review of Economic Studies, Oxford University Press, vol. 67(4), pages 697-717.
    17. Maskin, Eric S & Riley, John G, 1984. "Optimal Auctions with Risk Averse Buyers," Econometrica, Econometric Society, vol. 52(6), pages 1473-1518, November.
    18. Sham M. Kakade & Ilan Lobel & Hamid Nazerzadeh, 2013. "Optimal Dynamic Mechanism Design and the Virtual-Pivot Mechanism," Operations Research, INFORMS, vol. 61(4), pages 837-854, August.
    19. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    20. R. Preston McAfee & John McMillan & Michael D. Whinston, 1989. "Multiproduct Monopoly, Commodity Bundling, and Correlation of Values," The Quarterly Journal of Economics, Oxford University Press, vol. 104(2), pages 371-383.
    21. Jonathan Levin & Paul Milgrom, 2010. "Online Advertising: Heterogeneity and Conflation in Market Design," American Economic Review, American Economic Association, vol. 100(2), pages 603-607, May.
    22. Philip A. Haile & Elie Tamer, 2003. "Inference with an Incomplete Model of English Auctions," Journal of Political Economy, University of Chicago Press, vol. 111(1), pages 1-51, February.
    23. R. McAfee & Kishore Papineni & Sergei Vassilvitskii, 2013. "Maximally representative allocations for guaranteed delivery advertising campaigns," Review of Economic Design, Springer;Society for Economic Design, vol. 17(2), pages 83-94, June.
    24. Cremer, Jacques & McLean, Richard P, 1988. "Full Extraction of the Surplus in Bayesian and Dominant Strategy Auctions," Econometrica, Econometric Society, vol. 56(6), pages 1247-1257, November.
    25. Dobzinski, Shahar & Lavi, Ron & Nisan, Noam, 2012. "Multi-unit auctions with budget limits," Games and Economic Behavior, Elsevier, vol. 74(2), pages 486-503.
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    Cited by:

    1. Dirk Bergemann & Alessandro Bonatti, 2015. "Selling Cookies," American Economic Journal: Microeconomics, American Economic Association, vol. 7(3), pages 259-294, August.
    2. Lu, Y. & Gupta, A. & Ketter, W. & van Heck, H.W.G.M., 2017. "Information Transparency in B2B Auction Markets: The Role of Winner Identity Disclosure," ERIM Report Series Research in Management ERS-2017-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2015. "Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design," Management Science, INFORMS, vol. 61(4), pages 864-884, April.
    4. Stourm, Valeria & Bax, Eric, 2017. "Incorporating hidden costs of annoying ads in display auctions," International Journal of Research in Marketing, Elsevier, vol. 34(3), pages 622-640.

    More about this item

    Keywords

    online advertising; real-time bidding; advertisement exchange; optimal auctions;

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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