Mungamuru, Bobji and Garcia-Molina, Hector (2008) Predictive Pricing and Revenue Sharing. Technical Report. Stanford.
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Abstract
Predictive pricing (e.g., Google's "Smart Pricing" and Yahoo's "Quality-Based Pricing") and revenue sharing are two important tools that online advertising networks can use in order to attract content publishers and advertisers. We develop a simple model of the pay-per-click advertising market to study the market effects of these tools. We then present an algorithm, PricingPolicy, for computing an advertising network's best response i.e., given the predictive pricing and revenue sharing policies used by its competitors, what policy should an advertising network use in response? Using PricingPolicy, we gain insight into the structure of optimal predictive pricing and revenue sharing policies.
Item Type: | Techreport (Technical Report) | |
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Uncontrolled Keywords: | predictive pricing, revenue sharing, pay-per-click, online advertising, game theory | |
Subjects: | Computer Science > E-Commerce | |
Projects: | PORTIA (DB-Privacy) | |
Related URLs: | Project Homepage | http://crypto.stanford.edu/portia/ |
ID Code: | 844 | |
Deposited By: | Import Account | |
Deposited On: | 17 Jul 2008 17:00 | |
Last Modified: | 10 Dec 2008 16:07 |
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