Description:
We consider a dynamic auction problem motivated by the traditional single-leg, multi-period revenue management problem. A seller with Q units to sell, faces potential buyers who arrive and depart over the course of T time periods. The time at which a buyer arrives, the quantity she desires, the value she places on that quantity as well as the time by which she must make the purchase are private information. In this environment we derive the revenue maximizing Bayesian incentive compatible selling mechanism.
Joint with Rakesh Vohra.
Speaker(s):
Mallesh Pai, graduate student, Department of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University
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