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Nonparametric Estimation of Demand Structures in Airline Revenue Management

Authors:
Johannes Ferdinand Jörg
Catherine Cleophas

Keywords: nonparametric; demand segments; estimation; revenue management

Abstract:
Airline revenue management employs forecasting and optimization techniques to offer the right price at the right time to the right customer. With the ability to store large amounts of data comes the challenge to incorporate the information contained in those data sets. This contribution considers the estimation of demand segments present in a specific market using nonparametrical methods on panel data. We employ finite mixtures to model booking events in different time frames and to obtain an estimator for the number of demand segments. Via an airline revenue management simulation tool, we perform an experimental study of the derived estimator. We discuss the results with respect to the underlying demand structure of the simulation and identified demand segments. The findings are discussed with respect to theoretical and practical use. Finally, we discuss the real world applicability and possible further research intentions.

Pages: 130 to 133

Copyright: Copyright (c) IARIA, 2015

Publication date: June 21, 2015

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-416-9

Location: Brussels, Belgium

Dates: from June 21, 2015 to June 26, 2015