| Many two-sided platforms (such as search engines and business directories) make profits from auctioning their user base to advertisers. Yet, auctioning users is different from selling standard commodities, since the participation decision by users (and, therefore, the size of the platform's user base) depends on the benefit users expect to receive from joining the platform. In this setting, what is the profit-maximizing auction? And how should a platform structure its user fees? In the first chapter of the thesis, we answer these questions by developing a model of two-sided auctions, in which the number of clicks that Google has to sell depends on the expectations that users have about the quality of the selected advertiser.;In the second chapter, we develop a Bayes-Nash analysis of the Generalized Second Price (GSP) auction. First, we characterize the efficient Bayes-Nash equilibrium of the GSP when such an equilibrium exists. We then obtain sufficient conditions on clickthrough rates that guarantee existence and show that an efficient equilibrium may fail to exist if click-through rates across slots are sufficiently close. Next, we derive the counterintuitive result that the seller's revenue may decrease as click-through rates increase. Fortunately, we show that setting optimal reserve prices reverses this result. Further, we prove that the GSP possesses no mixed strategy equilibrium and that no inefficient equilibrium can be symmetric.;In the third chapter, we study the matching rules that result from welfare and profit-maximization by a monopolistic two-sided platform in the presence of cross-side externalities. In order to investigate the optimality of a large variety of pricing strategies, we impose the minimally restrictive feasibility constraint on matching rules. Namely, feasible matching rules have to be reciprocal: if John belongs to Mary's matching set, so does Mary belong to John's. In this context, we derive necessary and sufficient conditions for such solutions to exhibit single or multi-homing. Single-homing matching rules assign agents on both sides of the market to mutually exclusive meeting places (also called two-sided networks), while multi-homing matching rules assign agents to increasing and nested matching sets. |
