Name
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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-92185-1_14 | WINE |
Keywords | Field | DocType |
optimal predictive pricing,smart pricing,online advertising network,predictive pricing,best response,revenue sharing,pay-per-click advertising market,advertising network use,market effect,advertising network,e commerce,online advertising | Share of voice,Revenue sharing,Computer science,Best response,Microeconomics,Online advertising,Revenue model,E-commerce,Competitor analysis | Conference |
Volume | ISSN | Citations |
5385 | 0302-9743 | 1 |
PageRank | References | Authors |
0.40 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bobji Mungamuru | 1 | 5 | 1.51 |
| Héctor García-Molina | 2 | 24359 | 5652.13 |