Joint forecasting for airline pricing and revenue management

Kavitha Balaiyan (), R. K. Amit (), Atul Kumar Malik (), Xiaodong Luo () and Amit Agarwal ()
Additional contact information
Kavitha Balaiyan: IIT Madras
R. K. Amit: IIT Madras
Atul Kumar Malik: Fair Isaac Corporation
Xiaodong Luo: Sabre Inc.
Amit Agarwal: Sabre Inc.

Journal of Revenue and Pricing Management, 2019, vol. 18, issue 6, No 7, 465-482

Abstract: Abstract We develop three parametric forecasting models that jointly estimate the volume component and the choice component of airline demand. These models—JFM-WPA, JFM-PA, and JFM-WTPU—account for (a) demand volume by considering the average demand of an O–D market, booking curve, seasonality and day-of-the-week indices, and (b) customer behavior by including the maximum willingness-to-pay of the customer and the choice attributes of the available options. We use a mixed logit function to formulate the willingness-to-pay and customer choice behavior. JFM-WPA excludes price from the set of choice attributes. JFM-PA considers price as one of the choice attributes. The utilities of maximum willingness-to-pay and choices are combined in JFM-WTPU. We propose a sequential method to estimate the forecasting models. We utilize the data generated by Airline Planning and Operations Simulator (APOS) from real airline historic data. We compare the models and present the results. These demand models can also be used as an input for optimization models, for joint seat allocation and pricing.

Keywords: Revenue management; Demand forecasting; Customer choice model; Mixed logit; Discrete-choice model; Sequential estimation; Maximum willingness-to-pay; APOS simulator (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1057/s41272-019-00188-4

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