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Joint forecasting for airline pricing and revenue management

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Journal of Revenue and Pricing Management Aims and scope

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.

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Notes

  1. Classification models assign an object to a certain class. Maximum likelihood estimation is a classification algorithm

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Author notes

  1. Atul Malik: Contributed when working for Sabre Inc.

Authors and Affiliations

  1. Department of Management Studies, IIT Madras, Chennai, India

    Kavitha Balaiyan & R. K. Amit

  2. Fair Isaac Corporation, Bangalore, India

    Atul Kumar Malik

  3. Sabre Inc., Southlake, USA

    Xiaodong Luo & Amit Agarwal

  4. Sabre Inc., Bangalore, India

    Amit Agarwal

Authors
  1. Kavitha Balaiyan
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  2. R. K. Amit
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  3. Atul Kumar Malik
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  4. Xiaodong Luo
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  5. Amit Agarwal
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Correspondence to R. K. Amit.

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Balaiyan, K., Amit, R.K., Malik, A.K. et al. Joint forecasting for airline pricing and revenue management. J Revenue Pricing Manag 18, 465–482 (2019). https://doi.org/10.1057/s41272-019-00188-4

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