Original Article
Journal of Revenue and Pricing Management advance online publication 29 May 2009; doi: 10.1057/rpm.2009.19
A model for airline seat control considering revenue uncertainty and risk
Kuancheng Huang1 and Ko-Chen Chang2
Correspondence: Kuancheng Huang, National Chiao Tung University, No. 1001, Ta Hsueh Road, Hsinchu City 300, Taiwan. E-mail: kchuang@cc.nctu.edu.tw
1is an assistant professor in the Department of Transportation Technology and Management, National Chiao Tung University, Taiwan. He received his BSc and MSc degrees in Electrical Engineering from National Taiwan University and University of California at Los Angeles, respectively, and PhD degree in Civil and Environment Engineering from Cornell University. His research interests include the optimisation problems in the areas of logistics and air transportation.
2is currently working for the ground-handling service of China Airlines (CAL) at Taiwan Taoyuan International Airport (TPE). He received his BSc and MSc degrees in transportation from National Chiao Tung University, Taiwan. His research interests focus on revenue management for airlines.
Received 23 March 2009; Revised 23 March 2009; Published online 29 May 2009.
Abstract
Most revenue management (RM) models rely on the concept of marginal seat revenue and the assumption of risk neutrality to develop an expected-revenue maximisation policy for airline seat-inventory control. For the single-leg dynamic RM problem, this study developed a modified seat control policy to take risk into consideration by discounting the marginal seat revenue and relaxing the optimality condition in the dynamic programming model. The effectiveness of the modified policy was examined by a series of simulation experiments. In particular, another risk-aversion RM model with the objective of utility maximisation was tested. The simulation analysis shows that both models can balance expected revenue and revenue variation in a systematic way so as to address risk-aversion preferences of different airlines.
Keywords:
revenue management, seat control policy, risk management, dynamic programming, simulation





