Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/66804 
Year of Publication: 
2011
Citation: 
[Journal:] Journal of Choice Modelling [ISSN:] 1755-5345 [Volume:] 4 [Issue:] 3 [Publisher:] University of Leeds, Institute for Transport Studies [Place:] Leeds [Year:] 2011 [Pages:] 75-87
Publisher: 
University of Leeds, Institute for Transport Studies, Leeds
Abstract: 
A good demand forecast should be at the heart of every Revenue Management model. Yet most demand models do not incorporate customer choice behavior under offered alternatives. We are using the ideas of customer choice sets to model the customer's buying behavior. The demand estimation method, as described in Haensel and Koole (2011), is based on maximum likelihood and the expectation maximization (EM) algorithm. The main focus of the paper is the application case on real airline reservation data. The reservation data, consisting of the airline's daily flight offers, is used to unconstrain the underlying customer demand in terms of price sensitivity. Using this demand information per choice sets, the revenue manager obtains a clear view of the real underlying demand.
Subjects: 
customer choice behavior
demand estimation and unconstraining
revenue management
Creative Commons License: 
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Document Type: 
Article
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