Estimating unconstrained demand rate functions using customer choice sets

A good demand forecast should be at the heart of every revenue management model. Yet most demand models focus on product demand and do not incorporate customer choice behavior under offered alternatives. We use the ideas of customer choice sets to model the customer's buying behavior. A customer choice set is a set of product classes representing the buying preferences and choice decisions of a certain customer group. In this article we present a demand estimation method for these choice sets. The procedure is based on the maximum likelihood method, and to overcome the problem of incomplete data or information we additionally apply the expectation maximization method. Using this demand information per choice sets, the revenue manager obtains a clear view of the underlying demand. In doing so, the sales consequences from different booking control actions can be compared and the overall revenue maximized. © 2011 Macmillan Publishers Ltd