Estimation method of sell-up potential based on the stochastic nature of


	passengers′ willingness to pay

Abstract

Abstract:

Regarding the issue that the stochastic nature of passengers′ willingness to pay is neglected by the sell-up potential estimation method of the Massachusetts Institute of Technology, which results in the underestimation of

the demand for intermediate class cabin, a sell-up potential estimation method that takes into account the probability distribution law of passengers′ willingness to pay was proposed. Firstly, assuming that passengers′ willingness to pay follows a normal distribution. Then, based on its probability characteristics, an estimation model

for sell-up potential was derived. Subsequently, the parameters of the distribution of passengers′ willingness to

pay were fitted from historical data to realize the estimation of the sell-up potential. To validate the effectiveness

of the proposed method, this article draws on the famous simulation system ideas from abroad, using Gaussian

mixture distribution to statistically analyze the data of passengers arrival, and a flight passenger arrival simulation software was designed and implemented for simulation evaluation. The system simulation combining real

data from three representative flight routes showed that the method proposed in this paper can effectively

strengthen the control of intermediate-class cabin and increase flight revenue.

Key words:

sell-up potential, willingness to pay, cabin class demand forecasting, revenue management

CLC Number:

FAN Wei , ZHANG Yongxiang.

Estimation method of sell-up potential based on the stochastic nature of

passengers′ willingness to pay

[J]. Journal of Civil Aviation University of China, 2025, 43(5): 82-89.

References 22

[1]	GALLEGO G, TOPALOGLU H. Revenue management and pricing ana－
	lytics[M]. New York: Springer, 2019.
[2]	林贵华, 唐艳, 陈拼博. 随机需求下航空公司收益管理定价模型[J]. 系统工程, 2022, 40(2): 109-117.
[3]	熊浩, 鄢慧丽. 考虑旅客跨区间流转的机票多预定区间折扣优化模型研究[J]. 中国管理科学, 2019, 27(8): 172-180.
[4]	樊玮, 苏秋波. 基于分布估计算法的多航段座位分配模型[J]. 信息与控制, 2012, 41(6): 774-778, 785.
[5]	胡玉生, 李金林, 冉伦, 等. 基于乘客惰性行为的平行航班动态定价[J]. 运筹与管理, 2018, 27(4): 112-117.
[6]	霍佳震, 秦瑛. 旅客需求双向转移的多等级舱位控制优化问题[J].系统工程, 2016, 34(1): 116-121.
[7]	WEATHERFORD L. The history of unconstraining models in revenue
	management[J]. Journal of Revenue and Pricing Management, 2016, 15(3): 222-228.
[8]	FIIG T, WEATHERFORD L R, WITTMAN M D. Can demand forecast
	accuracy be linked to airline revenue?[J]. Journal of Revenue and Pricing Management, 2019, 18(4): 291-305.
	[9]
	BELOBABA P P. Did LCCs save airline revenue management?[J]. Journal of Revenue and Pricing Management, 2011, 10(1): 19-22.
[10]	LE M L, LU M H. Network revenue management with dependent demand under overlapping segments[C]//2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
	(ICNC-FSKD), July 28-30, 2018, Huangshan, China. IEEE, 2018: 677-684.
[11]	TALLURI K, VAN RYZIN G. Revenue management under a general
	discrete choice model of consumer behavior[J]. Management Science,2004, 50(1): 15-33.
[12]	ALGERS S, BESER M. Modelling choice of flight and booking class-a
	study using stated preference and revealed preference data[J]. International Journal of Services Technology and Management, 2001, 2 (1/2):28-45.
[13]	梅虎, 朱金福, 汪侠. 基于旅客舱位选择的航空收益管理[J]. 系统工程, 2006, 24(9): 11-17.
[14]	FUKUSHI M, DELGADO F, RAVEAU S, et al. CHAIRS: a choice based air transport simulator applied to airline competition and revenue management[J]. Transportation Research Part A: Policy and Practice,
	2022, 155: 297-315.
[15]	CHIAMBARETTO P. Air passengers′willingness to pay for ancillary
	services on long-haul flights[J]. Transportation Research Part E: Logistics and Transportation Review, 2021, 147: 102234.
[16]	CARRIER E, WEATHERFORD L. Implementation of MNL choice models in the passenger origin-destination simulator (PODS)[J]. Journal of Revenue and Pricing Management, 2015, 14(6): 400-407.
[17]	WEATHERFORD L R. Intelligent aggressiveness: using forecast
	multipliers, hybrid forecasting, fare adjustment, and unconstraining
	methods to increase revenue[J]. Decision Sciences, 2017, 48(3): 391-419.
[18]	樊玮, 杨同杰, 衡红军. 基于卖高行为的航班舱位优化[J]. 计算机工程与设计, 2015, 36(7): 1948-1952.
[19]	王洪建. 航班座位控制模型实现与分析[J]. 软件工程, 2022, 25(2):26-28.
[20]	JIANG H Y, MIGLIONICO G. Airline network revenue management
	with buy-up[J]. Optimization, 2014, 63(6): 849-865.
[21]	BELOBABA P P. Optimal vs. heuristic methods for nested seat allocation[C]//Presentation at ORSA/TIMS Joint National Meeting, Brussels,Belgium. 1992: 28-53.
[22]	HOPPERSTAD C, ZERBIB G, BELOBABA P P. Methods for estimating
	sell-up[C]//AGIFORS Revenue Management and Distribution Study
	Group Meeting, Cancun, Mexico. 2006.

Estimation method of sell-up potential based on the stochastic nature of

passengers′ willingness to pay

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