On Revenue Management with Strategic Customers Choosing When and What to Buy

We study a network revenue management model in which a decision maker offers multiple products, which consume capacitated resources, for sale to customers over a finite horizon. The decision maker employs an anonymous posted-price policy, and arriving customers strategize on (a) when, and (b) which product to purchase so as to maximize their utility. Customers' choices are driven by heterogeneous product valuations that decay over time at heterogeneous rates. Both initial valuations and decay rates are private information. We derive for all nonanticipating dynamic pricing policies an upper bound to expected revenues. We use our bound to conduct theoretical and numerical performance analyses of static pricing policies. In our theoretical analysis, we derive a constant factor guarantee for the performance of static pricing, for the classical fluid-type regime where inventory and demand grow large. Our numerical analysis shows static pricing to be able capture at least 75%-90% of maximum possible expected revenue under a wide range of realistic problem parameters, and suggests that static pricing is likely to perform better under higher product proliferation and lower load factor in the presence of strategic customers