In a sponsored search auction, decisions about how to rank ads imposetradeoffs between objectives such as revenue and welfare. In this paper, weexamine how these tradeoffs should be made. We begin by arguing that the mostnatural solution concept to evaluate these tradeoffs is the lowest symmetricNash equilibrium (SNE). As part of this argument, we generalise the well knownconnection between the lowest SNE and the VCG outcome. We then propose a newranking algorithm, loosely based on the revenue-optimal auction, that uses areserve price to order the ads (not just to filter them) and give conditionsunder which it raises more revenue than simply applying that reserve price.Finally, we conduct extensive simulations examining the tradeoffs enabled bydifferent ranking algorithms and show that our proposed algorithm enablessuperior operating points by a variety of metrics.
展开▼
