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Hybrid Advertising Auctions

Yi Zhu

University of Minnesota - Carlson School of Management

Kenneth C. Wilbur

University of California, San Diego (UCSD) - Rady School of Management

August 21, 2010

2009 INFORMS Marketing Science Conference
NET Institute Working Paper No. 08-25

Facebook and Google offer hybrid advertising auctions that allow advertisers to bid on a per-impression or a per-click basis for the same advertising space. This paper studies the properties of equilibrium and considers how to increase efficiency in this new auction format. Rational expectations require the publisher to consider past bid types in order to prevent revenue losses to strategic advertiser behavior. The equilibrium results contradict publisher statements and suggest that, conditional on setting rational expectations, publishers should consider offering multiple bid types to advertisers. For a special case of the model, we provide a payment scheme that achieves the socially optimal allocation of advertisers to slots and maximizes publisher revenues within the class of socially optimal payment schemes. When this special case does not hold, no payment scheme will always achieve the social optimum.

Number of Pages in PDF File: 57

Keywords: Advertising, Auctions, Internet Marketing, Search Advertising

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Date posted: April 2, 2009 ; Last revised: October 26, 2012

Suggested Citation

Zhu, Yi and Wilbur, Kenneth C., Hybrid Advertising Auctions (August 21, 2010). 2009 INFORMS Marketing Science Conference; NET Institute Working Paper No. 08-25. Available at SSRN: https://ssrn.com/abstract=1371758 or http://dx.doi.org/10.2139/ssrn.1371758

Contact Information

Yi Zhu
University of Minnesota - Carlson School of Management ( email )
321 - 19th Ave. South, Suite 3-150
Minneapolis, MN 55455
United States
Kenneth C. Wilbur (Contact Author)
University of California, San Diego (UCSD) - Rady School of Management ( email )
9500 Gilman Drive
Rady School of Management
La Jolla, CA 92093
United States
HOME PAGE: http://kennethcwilbur.com
Feedback to SSRN

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