IDEAS home Printed from https://ideas.repec.org/p/hbs/wpaper/10-055.html
   My bibliography  Save this paper

Competing Ad Auctions

Author

Listed:
  • Itai Ashlagi

    (Harvard Business School, Negotiation, Organizations & Markets Unit)

  • Benjamin G. Edelman

    (Harvard Business School, Negotiation, Organizations & Markets Unit)

  • Hoan Soo Lee

    (Harvard Business School, Negotiation, Organizations & Markets Unit)

Abstract

We present a two-stage model of competing ad auctions. Search engines attract users via Cournot-style competition. Meanwhile, each advertiser must pay a participation cost to use each ad platform, and advertiser entry strategies are derived using symmetric Bayes-Nash equilibrium that lead to the VCG outcome of the ad auctions. Consistent with our model of participation costs, we find empirical evidence that multi-homing advertisers are larger than single-homing advertisers. We then link our model to search engine market conditions: We derive comparative statics on consumer choice parameters, presenting relationships between market share, quality, and user welfare. We also analyze the prospect of joining auctions to mitigate participation costs, and we characterize when such joins do and do not increase welfare.

Suggested Citation

  • Itai Ashlagi & Benjamin G. Edelman & Hoan Soo Lee, 2010. "Competing Ad Auctions," Harvard Business School Working Papers 10-055, Harvard Business School, revised Sep 2013.
  • Handle: RePEc:hbs:wpaper:10-055
    as

    Download full text from publisher

    File URL: http://www.hbs.edu/faculty/pages/download.aspx?name=10-055.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alison Watts, 2018. "Generalized Second Price Auctions over a Network," Games, MDPI, vol. 9(3), pages 1-11, September.
    2. Mohammad Zia & Ram C. Rao, 2019. "Search Advertising: Budget Allocation Across Search Engines," Marketing Science, INFORMS, vol. 38(6), pages 1023-1037, November.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:hbs:wpaper:10-055. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: HBS (email available below). General contact details of provider: https://edirc.repec.org/data/harbsus.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.