Abstract
Traditionally, airlines have been limited to a set of fixed fare classes and, in turn, price points, to distribute their fare products. The advent of IATA’s new distribution capability (NDC) will soon enable airlines to quote any fare from a continuous range. In theory, such continuous pricing could increase revenues by extracting more of the consumer surplus, through its ability to offer more granular fares, closer to the customer’s willingness-to-pay (WTP). In this article, we describe several algorithms that lead to the quotation of a single fare from a continuous range. These algorithms either rely on traditional fare classes for the purpose of forecasting and optimization (class-based), or completely abandon the notion of fare classes, instead assuming different WTP distributions within each booking period prior to departure (classless). We describe how these algorithms build upon and differ from their traditional RM counterparts. Performance of these heuristics is then benchmarked against traditional class-based RM, and competitive impacts are analyzed when continuous pricing is adopted by one airline asymmetrically or both airlines symmetrically in a hypothetical 2-carrier network in the passenger origin–destination simulator (PODS). We find that continuous pricing is generally revenue-positive, and the revenue gains can be as high as 2.0% for the first-mover and reach up to 1.2% when both airlines adopt the new method. In addition, we show that these gains depend on the number of fare classes in the traditional fare structure used as a baseline, and that they are smaller under lower demand-to-capacity ratios.
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Acknowledgements
The authors would like to dedicate this paper to the memory of Craig A. Hopperstad, the original developer of the Passenger Origin Destination Simulator (PODS) and a primary source of inspiration for the concepts behind the continuous pricing algorithms described in this paper. Craig continued to work on the implementation of continuous pricing methods into PODS until his death in January 2019, giving us the foundation for further development and testing of these algorithms.
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Szymański, B., Belobaba, P.P. & Papen, A. Continuous pricing algorithms for airline RM: revenue gains and competitive impacts. J Revenue Pricing Manag 20, 669–688 (2021). https://doi.org/10.1057/s41272-021-00350-x
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DOI: https://doi.org/10.1057/s41272-021-00350-x