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Marketing Agencies and Collusive Bidding in Online Ad Auctions

Author

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  • Francesco Decarolis

    (Department of Economics and Innocenzo Gasparini Institute for Economic Research, Bocconi University, 20136 Milano, Italy)

  • Maris Goldmanis

    (Department of Economics, Royal Holloway, University of London, Egham TW20 0EX, United Kingdom;)

  • Antonio Penta

    (Catalan Institution for Research and Advanced Studies, Universitat Pompeu Fabra and Barcelona Graduate School of Economics, 08005 Barcelona, Spain; Toulouse School of Economics and Digital Center, 31015 Toulouse, France)

Abstract

The transition of the advertising market from traditional media to the internet has induced a proliferation of marketing agencies specialized in bidding in the auctions that are used to sell ad space on the web. We analyze how collusive bidding can emerge from bid delegation to a common marketing agency and how this can undermine the revenues and allocative efficiency of both the generalized second-price auction (GSP, used by Google, Microsoft Bing, and Yahoo!) and the Vickrey–Clarke–Groves (VCG) mechanism (used by Facebook). We find that despite its well-known susceptibility to collusion, the VCG mechanism outperforms the GSP auction in terms of both revenues and efficiency.

Suggested Citation

  • Francesco Decarolis & Maris Goldmanis & Antonio Penta, 2020. "Marketing Agencies and Collusive Bidding in Online Ad Auctions," Management Science, INFORMS, vol. 66(10), pages 4433-4454, October.
    • Handle: RePEc:inm:ormnsc:v:66:y:2020:i:10:p:4433-4454
    DOI: 10.1287/mnsc.2019.3457
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    Cited by:

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    3. Sadek, Biland, 2024. "Components and Strategic Routes of Corporate Transformations," MPRA Paper 120332, University Library of Munich, Germany, revised 26 Feb 2024.
    4. Dirk Bergemann & Alessandro Bonatti & Nicholas Wu, 2023. "How Do Digital Advertising Auctions Impact Product Prices?," Cowles Foundation Discussion Papers 2367, Cowles Foundation for Research in Economics, Yale University.
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    6. Baccara, Mariagiovanna & Asker, John & Lee, SangMok, 2021. "Patent Auctions and Bidding Coalitions: Structuring the Sale of Club Goods," CEPR Discussion Papers 15703, C.E.P.R. Discussion Papers.
    7. Amin Sayedi & Kinshuk Jerath & Marjan Baghaie, 2018. "Exclusive Placement in Online Advertising," Marketing Science, INFORMS, vol. 37(6), pages 970-986, November.
    8. John Asker & Mariagiovanna Baccara & SangMok Lee, 2021. "Patent auctions and bidding coalitions: structuring the sale of club goods," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 662-690, September.
    9. Thomas W. L. Norman, 2021. "Evolutionary stability in the generalized second-price auction," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(1), pages 235-250, February.
    10. Sylvain Chassang & Juan Ortner, 2019. "Collusion in Auctions with Constrained Bids: Theory and Evidence from Public Procurement," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 2269-2300.
    11. Hannes Wallimann & David Imhof & Martin Huber, 2023. "A Machine Learning Approach for Flagging Incomplete Bid-Rigging Cartels," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1669-1720, December.
    12. Margarida V. B. Santos & Isabel Mota & Pedro Campos, 2023. "Analysis of online position auctions for search engine marketing," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 409-425, September.
    13. Maximilian Schäfer & Geza Sapi, 2020. "Learning from Data and Network Effects: The Example of Internet Search," Discussion Papers of DIW Berlin 1894, DIW Berlin, German Institute for Economic Research.
    14. Francesco Decarolis & Gabriele Rovigatti, 2017. "Online Auctions and Digital Marketing Agencies," Working Papers 17-08, NET Institute.
    15. Xinyu Cao & T. Tony Ke, 2019. "Cooperative Search Advertising," Marketing Science, INFORMS, vol. 38(1), pages 44-67, January.
    16. Calvano, Emilio & Polo, Michele, 2021. "Market power, competition and innovation in digital markets: A survey," Information Economics and Policy, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    collusion; digital marketing agencies; Facebook; Google; GSP; internet auctions; online advertising; VCG;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

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