Sequences of Take-It-or-Leave-It Offers: Near-Optimal Auctions Without Full Valuation Revelation
We introduce take-it-or-leave-it auctions (TLAs) as an allocation mechanism that allows buyers to retain much of their private valuation information, yet generates close-to-optimal expected utility for the seller. We show that if each buyer receives at most one oﬀer, each buyer’s dominant strategy is to act truthfully. In more general TLAs, the buyers’ optimal strategies are more intricate, and we derive the perfect Bayesian equilibrium for the game. We develop algorithms for ﬁnding the equilibrium and also for optimizing the oﬀers so as to maximize the seller’s expected utility. In several example settings we show that the seller’s expected utility already is close to optimal for a small number of oﬀers. As the number of buyers increases, the seller’s expected utility increases, and becomes increasingly (but not monotonically) more competitive with Myerson’s expected utility maximizing auction.