Abstract
Motivated by the practice of airlines, this paper considers the following problem. Tickets are offered at a limited number of predetermined price levels, and the price is only allowed to change monotonically. Management needs to determine the number of seats to be sold at each discount fare with an objective of maximizing the revenue. Such a semi-dynamic pricing and seat allocation approach improves the static pricing approach, as it allows a certain degree of pricing flexibility, but it compromises the potential revenue maximization of the dynamic pricing approach. Therefore, a natural question is what is the magnitude of the revenue loss by such a semi-dynamic approach? The primary objective of this paper is to gain insights into this question. Based on structural results, numerical experiments show that the semi-dynamic pricing approach generates near-optimal revenue.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Belobaba PP (1987) Air travel demand and airline seat inventory management. PhD thesis, Flight Transportation Laboratory, Massachusetts Institute of Technology, Cambridge, MA
Bitran GR, Caldentey R (2003) An overview of pricing models for revenue management. Manuf Serv Oper Manag 5(3):203–229
Boyd EA, Kallesen R (2004) The science of revenue management when passenger purchase the lowest available fare. J Rev Pricing Manag 3(2):171–177
Brumelle SL, McGill JI (1993) Airline seat allocation with multiple nested fare classes. Oper Res 41(1):127–137
Brumelle SL, McGill JI, Oum TH, Sawaki K, Tretheway MW (1990) Allocation of airline seats between stochastically dependent demands. Transp Sci 24:183–192
Curry RE (1990) Optimum airline seat allocation with fare classes nested by origins and destinations. Transp Sci 24:193–204
Feng YY, Gallego G (1995) Optimal starting times for end-of-season sales and optimal stopping times for promotional fares. Manage Sci 41:1371–1391
Feng YY, Xiao BC (2000a) Optimal policies of yield management with multiple predetermined prices. Oper Res 48(2):332–343
Feng YY, Xiao BC (2000b) A continuous-time yield management model with multiple prices and reversible price changes. Manage Sci 46(5):644–657
Kimes SE (2002) Perceived fairness of yield management. Cornell Hotel Restaur Adm Q 43(1): 21–30
Lee TC, Hersh M (1993) A model for dynamic airline seat inventory control with multiple seat bookings. Transp Sci 27:252–265
Liang Y (1999) Solution to the continuous time dynamic yield management model. Transp Sci 33:117–123
Lin GY, Lu YD, Yao DD (2003) The stochastic knapsack revisited: structure, switch-over policies and dynamic pricing. Working Paper, IEOR Department, Columbia University, New York, NY
Littlewood K (1972) Forecasting and control of passenger bookings. AGIFORS 12th Annual Symposium Proceedings, pp 95–128
McGill JI, Van Ryzin GJ (1999) Revenue management: research overview and prospects. Transp Sci 33(2):233–256
Pfeifer PE (1989) The airline discount fare allocation problem. Decis Sci 20:149–157
Robinson LW (1995) Optimal and approximate control policies for airline booking with sequential nonmonotonic fare classes. Oper Res 43(2):252–263
Ross SM (1996) Stochastic processes. 2nd ed. Wiley, New York
Subramanian J, Stidham S, Lautenbacher CJ (1999) Airline yield management with overbooking, cancellations, and no-shows. Transp Sci 33(2):147–167
Talluri KT, Van Ryzin GJ (2004a) Revenue management under a general discrete choice model of consumer behavior. Manage Sci 50(1):15–33
Talluri KT, Van Ryzin GJ (2004b) The theory and practice of revenue management. Kluwer, New York
Van Slyke R, Young Y (2000) Finite horizon stochastic knapsacks with applications to yield management. Oper Res 48:155–172
Van Ryzin GJ, McGill JI (2000) Revenue management without forecasting or optimization: an adaptive algorithm for determining airline seat protection levels. Manage Sci 46(6):760–775
Wollmer RD (1992) An airline seat management model for a single leg route when lower fare classes book first. Oper Res 40(1):26–37
Zhao W, Zheng YS (2000) Optimal dynamic pricing for perishable assets with nonhomogeneous demand. Manage Sci 46(3):375–388
Author information
Authors and Affiliations
Corresponding author
Additional information
Comments by two anonymous referees are appreciated. This research was partially supported by the National Science Foundation of China (NSFC) under Project No. 70321001 and 70329001, and the Research Grants Council of Hong Kong (SAR) under Project No. 2150393.
Rights and permissions
About this article
Cite this article
Xiao, Y.B., Chen, J. & Chen, Y. On a semi-dynamic pricing and seat inventory allocation problem. OR Spectrum 29, 85–103 (2007). https://doi.org/10.1007/s00291-005-0017-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00291-005-0017-0