IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v69y2023i7p4027-4050.html
   My bibliography  Save this article

Best of Both Worlds Ad Contracts: Guaranteed Allocation and Price with Programmatic Efficiency

Author

Listed:
  • Maxime C. Cohen

    (Desautels Faculty of Management, McGill University, Montreal, Quebec H3A 1G5, Canada)

  • Antoine Désir

    (Technology and Operations Management, INSEAD, 77305, Fontainebleau, France)

  • Nitish Korula

    (Google, New York 10011)

  • Balasubramanian Sivan

    (Google Research, New York 10011)

Abstract

Buying display ad impressions via real-time auctions comes with significant allocation and price uncertainties. We design and analyze a contract that mitigates this uncertainty risk by providing guaranteed allocation and prices while maintaining the efficiency of buying in an auction. We study how risk aversion affects the desire for guarantees and how to price a guaranteed allocation. We propose to augment the traditional auction with a programmatic purchase option (which we call a Market-Maker contract ) that removes allocation and price uncertainties. Instead of participating in the auction, advertisers can secure impressions in advance at a fixed premium price offered by the Market-Maker. It is then the responsibility of the Market-Maker to procure these impressions by bidding in the auction. We model buyers as risk-averse agents and analyze the equilibrium outcome when buyers face two purchase options (auction and Market-Maker contract). We derive analytical expressions for the Market-Maker price that reveal insightful relationships with uncertainties in the auction price and buyers’ risk levels. We also show the existence of a Market-Maker price that simultaneously improves the seller’s revenue and the sum of buyers’ utilities. As a building block to our analysis, we establish the truthfulness of the multiunit auction when buyers have nonquasilinear utilities because of risk aversion. Recently, the Google’s Display & Video 360 platform started offering a product akin to Market-Maker called “Guaranteed Packages,” which was inspired by this paper.

Suggested Citation

  • Maxime C. Cohen & Antoine Désir & Nitish Korula & Balasubramanian Sivan, 2023. "Best of Both Worlds Ad Contracts: Guaranteed Allocation and Price with Programmatic Efficiency," Management Science, INFORMS, vol. 69(7), pages 4027-4050, July.
  • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:7:p:4027-4050
    DOI: 10.1287/mnsc.2022.4542
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2022.4542
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2022.4542?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Victor F. Araman & Ioana Popescu, 2010. "Media Revenue Management with Audience Uncertainty: Balancing Upfront and Spot Market Sales," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 190-212, December.
    3. Amin Sayedi, 2018. "Real-Time Bidding in Online Display Advertising," Marketing Science, INFORMS, vol. 37(4), pages 553-568, August.
    4. Shunda, Nicholas, 2009. "Auctions with a buy price: The case of reference-dependent preferences," Games and Economic Behavior, Elsevier, vol. 67(2), pages 645-664, November.
    5. Nautz, D. & Wolfstetter, E., 1997. "Bid shading and risk aversion in multi-unit auctions with many bidders," Economics Letters, Elsevier, vol. 56(2), pages 195-200, October.
    6. Markowitz, Harry, 2014. "Mean–variance approximations to expected utility," European Journal of Operational Research, Elsevier, vol. 234(2), pages 346-355.
    7. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    8. Ang, Andrew, 2014. "Asset Management: A Systematic Approach to Factor Investing," OUP Catalogue, Oxford University Press, number 9780199959327.
    9. Martin A. Lariviere, 2006. "A Note on Probability Distributions with Increasing Generalized Failure Rates," Operations Research, INFORMS, vol. 54(3), pages 602-604, June.
    10. John Turner, 2012. "The Planning of Guaranteed Targeted Display Advertising," Operations Research, INFORMS, vol. 60(1), pages 18-33, February.
    11. Devanur, Nikhil R. & Peres, Yuval & Sivan, Balasubramanian, 2019. "Perfect Bayesian Equilibria in repeated sales," Games and Economic Behavior, Elsevier, vol. 118(C), pages 570-588.
    12. Gérard P. Cachon, 2004. "The Allocation of Inventory Risk in a Supply Chain: Push, Pull, and Advance-Purchase Discount Contracts," Management Science, INFORMS, vol. 50(2), pages 222-238, February.
    13. René Caldentey & Gustavo Vulcano, 2007. "Online Auction and List Price Revenue Management," Management Science, INFORMS, vol. 53(5), pages 795-813, May.
    14. Maskin, Eric S & Riley, John G, 1984. "Optimal Auctions with Risk Averse Buyers," Econometrica, Econometric Society, vol. 52(6), pages 1473-1518, November.
    15. Milgrom,Paul, 2004. "Putting Auction Theory to Work," Cambridge Books, Cambridge University Press, number 9780521536721, September.
    16. Susan Athey & Emilio Calvano & Joshua Gans, 2013. "The Impact of the Internet on Advertising Markets for News Media," NBER Working Papers 19419, National Bureau of Economic Research, Inc.
    17. René Kirkegaard & Per Baltzer Overgaard, 2008. "Buy‐out prices in auctions: seller competition and multi‐unit demands," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 770-789, September.
    18. Soo-Haeng Cho & Christopher S. Tang, 2013. "Advance Selling in a Supply Chain Under Uncertain Supply and Demand," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 305-319, May.
    19. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-317, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaplan, Todd R. & Zamir, Shmuel, 2015. "Advances in Auctions," Handbook of Game Theory with Economic Applications,, Elsevier.
    2. Shunda, Nicholas, 2009. "Auctions with a buy price: The case of reference-dependent preferences," Games and Economic Behavior, Elsevier, vol. 67(2), pages 645-664, November.
    3. 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.
    4. Peyman Khezr, 2018. "Why Sellers Avoid Auctions: Theory and Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 56(2), pages 163-182, February.
    5. Bettina Klose & Paul Schweinzer, 2022. "Auctioning risk: the all-pay auction under mean-variance preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(4), pages 881-916, June.
    6. Ernan Haruvy & Peter Popkowski Leszczyc & Octavian Carare & James Cox & Eric Greenleaf & Wolfgang Jank & Sandy Jap & Young-Hoon Park & Michael Rothkopf, 2008. "Competition between auctions," Marketing Letters, Springer, vol. 19(3), pages 431-448, December.
    7. Frank Schuhmacher & Hendrik Kohrs & Benjamin R. Auer, 2021. "Justifying Mean-Variance Portfolio Selection when Asset Returns Are Skewed," Management Science, INFORMS, vol. 67(12), pages 7812-7824, December.
    8. Santiago R. Balseiro & Jon Feldman & Vahab Mirrokni & S. Muthukrishnan, 2014. "Yield Optimization of Display Advertising with Ad Exchange," Management Science, INFORMS, vol. 60(12), pages 2886-2907, December.
    9. Subir Bose & Arup Daripa, 2009. "Optimal sale across venues and auctions with a buy-now option," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 38(1), pages 137-168, January.
    10. Li, Yanhai, 2020. "Optimal reserve prices in sealed-bid auctions with reference effects," International Journal of Industrial Organization, Elsevier, vol. 71(C).
    11. Shunda, Nicholas, 2009. "Auctioning with Aspirations: Keep Them Low (Enough)," MPRA Paper 16242, University Library of Munich, Germany.
    12. Vasserman, Shoshana & Watt, Mitchell, 2021. "Risk aversion and auction design: Theoretical and empirical evidence," International Journal of Industrial Organization, Elsevier, vol. 79(C).
    13. 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.
    14. Olarte, Rafael & Haghani, Ali, 2018. "Introducing and testing a game-theoretic model for a lottery-based metering system in Minneapolis, United States," Transport Policy, Elsevier, vol. 62(C), pages 63-78.
    15. Anwar, Sajid & Zheng, Mingli, 2015. "Posted price selling and online auctions," Games and Economic Behavior, Elsevier, vol. 90(C), pages 81-92.
    16. Inami, Yusuke, 2011. "The buy price in auctions with discrete type distributions," Mathematical Social Sciences, Elsevier, vol. 61(1), pages 1-11, January.
    17. Hu, Audrey & Offerman, Theo & Zou, Liang, 2011. "Premium auctions and risk preferences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2420-2439.
    18. Embrey, Matthew & Hyndman, Kyle & Riedl, Arno, 2021. "Bargaining with a residual claimant: An experimental study," Games and Economic Behavior, Elsevier, vol. 126(C), pages 335-354.
    19. Axel Ockenfels & David Reiley & Abdolkarim Sadrieh, 2006. "Online Auctions," NBER Working Papers 12785, National Bureau of Economic Research, Inc.
    20. Bauner, Christoph, 2015. "Mechanism choice and the buy-it-now auction: A structural model of competing buyers and sellers," International Journal of Industrial Organization, Elsevier, vol. 38(C), pages 19-31.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:69:y:2023:i:7:p:4027-4050. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.