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Disentangling capacity control from price optimization

Author

Listed:
  • Jonas Rauch

    (Lufthansa Group, Distribution and RM Strategy)

  • Karl Isler
  • Stefan Poelt

    (Lufthansa Group, RM and Pricing IT)

Abstract

Standard revenue management (RM) methods typically work with an integrated forecast of demand and customer choice at booking class level and then maximize revenue by optimally controlling class availability. We show that the structure of the RM problem can be decomposed into two sub-problems: capacity control and price optimization for incoming customer requests. For capacity control in practice often bid prices, the dual variables to the capacity constraints, are used. Price optimization on the other hand needs forecasts of passengers’ willingness to pay. We propose to use two separate and tailored forecast models for both optimization tasks and discuss the advantages of this forecast separation. Furthermore, for the task of bid price calculation, we present a robust forecast model that is independent of booking classes and the actual control mechanism. It depends on historical booking data and bid prices only, but does not require historical fares and availabilities, which are often not available in good quality.

Suggested Citation

  • Jonas Rauch & Karl Isler & Stefan Poelt, 2018. "Disentangling capacity control from price optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(2), pages 48-62, April.
    • Handle: RePEc:pal:jorapm:v:17:y:2018:i:2:d:10.1057_s41272-017-0118-9
    DOI: 10.1057/s41272-017-0118-9
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    References listed on IDEAS

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    1. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    2. Catherine Cleophas & Michael Frank & Natalia Kliewer, 2009. "Recent developments in demand forecasting for airline revenue management," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 3(3), pages 252-269.
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    Cited by:

    1. Jost Daft & Sascha Albers & Sebastian Stabenow, 2021. "From product-oriented flight providers to customer-centric retailers: a dynamic offering framework and implementation guidelines for airlines," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 615-625, December.
    2. Tiago Gonçalves & Bernardo Almada-Lobo, 2024. "Enhancing robustness to forecast errors in availability control for airline revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(4), pages 346-354, August.
    3. Claudia Schütze & Catherine Cleophas & Monideepa Tarafdar, 2020. "Revenue management systems as symbiotic analytics systems: insights from a field study," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 1007-1031, November.

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