Chris K. Anderson

Priceline.com is an Internet-based corporation offering services (airline tickets, hotel rooms, rental cars, and home mortgages) with the option for consumers to dictate prices. Priceline's original success stemmed from its innovative “name your price” approach whereby consumers bid for service with Priceline to find a willing provider at the bid price. Consumers are only allowed to bid once on a service so they must be strategic in bidding—bid too low and potentially lose out on service, bid too high and overpay for the service. While they are only allowed to bid once per product, bidders can slightly alter their service and potentially re-bid in an effort to get new information (from failed attempts)—such alterations may include a different class of hotel (3 star versus 4), a flight with 1 stop versus direct, or (as in the case below) a different class (economy versus luxury) of rental car. The case is designed to cover a broad range of topics while introducing students to auctions. The case teaches strategic bidding while covering probability, decision analysis, and integer programming. The case has had great success at the undergraduate and MBA levels as students enjoy the setting, are familiar with Priceline, and immediately see an everyday use of management science. Case Teaching Note: Interested Instructors please see the Instructor Materials page for access to the restricted materials. To maintain the integrity and usefulness of cases published in ITE, unapproved distribution of the case teaching notes and other restricted materials to any other party is prohibited.

Case Teaching Note: Interested Instructors please see the Instructor Materials page for access to the restricted materials. To maintain the integrity and usefulness of cases published in ITE, unapproved distribution of the case teaching notes and other restricted materials to any other party is prohibited.

We consider a two‐period airline yield management problem where customers may act strategically. Specifically, we allow for the possibility that a customer may decide to defer purchase in the hope that a ticket cheaper than those currently on offer will become available. We also allow for the possibility that some customers will buy a more expensive ticket if the cheaper tickets are not available. We show how to find optimal booking limits in the presence of such strategic customer behavior. We also explicitly incorporate the fact that, once a booking limit has been reached, demand distributions are now censored distributions.