Truthful auctions for pricing search keywords
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Designing online auctions with past performance information
Decision Support Systems
Revenue analysis of a family of ranking rules for keyword auctions
Proceedings of the 8th ACM conference on Electronic commerce
Bayes-nash equilibria of the generalized second price auction
Proceedings of the 10th ACM conference on Electronic commerce
Ex Ante Information and the Design of Keyword Auctions
Information Systems Research
Auctions with revenue guarantees for sponsored search
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Simulation-based game theoretic analysis of keyword auctions with low-dimensional bidding strategies
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
Reserve prices in internet advertising auctions: a field experiment
Proceedings of the 12th ACM conference on Electronic commerce
Stochastic variability in sponsored search auctions: observations and models
Proceedings of the 12th ACM conference on Electronic commerce
On the efficiency of equilibria in generalized second price auctions
Proceedings of the 12th ACM conference on Electronic commerce
On revenue in the generalized second price auction
Proceedings of the 21st international conference on World Wide Web
Efficient ranking in sponsored search
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Ranking and tradeoffs in sponsored search auctions
Proceedings of the fourteenth ACM conference on Electronic commerce
Ranking and tradeoffs in sponsored search auctions
Proceedings of the fourteenth ACM conference on Electronic commerce
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In a sponsored search auction, decisions about how to rank ads impose tradeoffs between objectives such as revenue and welfare. In this paper, we examine how these tradeoffs should be made. We begin by arguing that the most natural solution concept to evaluate these tradeoffs is the lowest symmetric Nash equilibrium (SNE). As part of this argument, we generalise the well known connection between the lowest SNE and the VCG outcome. We then propose a new ranking algorithm, loosely based on the revenue-optimal auction, that uses a reserve price to order the ads (not just to filter them) and give conditions under which it raises more revenue than simply applying that reserve price. Finally, we conduct extensive simulations examining the tradeoffs enabled by different ranking algorithms and show that our proposed algorithm enables superior operating points by a variety of metrics.