Revenue Management with End-of-Period Discounts in the Presence of Customer Learning

Abstract

Consider a firm that sells identical products over a series of selling periods (e.g., weekly all-inclusive vacations at the same resort). To stimulate demand and enhance revenue, in some periods, the firm may choose to offer a part of its available inventory at a discount. As customers learn to expect such discounts, a fraction may wait rather than purchase at a regular price. A problem the firm faces is how to incorporate this waiting and learning into its revenue management decisions. To address this problem we summarize two types of learning behaviors and propose a general model that allows for both stochastic consumer demand and stochastic waiting. For the case with two customer classes we develop a novel solution approach to the resulting dynamic program. We then examine two simplified models, where either the demand or the waiting behavior are deterministic, and present the solution in a closed form. We extend the model to incorporate three customer classes and discuss the effects of overbooking. Through numerical simulations we study the value of offering end-of-period deals optimally and analyze how this value changes under different consumer behavior, demand, and capacity scenarios.

Keywords: revenue, management, strategic, consumer, behavior, overbooking, pricing, dynamic