Abstract
Airlines are increasingly trying to differentiate their offers, so one airline’s bare bones low fare may, for some travelers, be equivalent to another airline’s high fare, if the low fare bundles some ancillaries a traveler wants. Because of differentiation of airline offers the air traveler must simultaneously compare air fares and the ancillaries included. Price comparison is also difficult as the same cabin offers vary by the ancillaries included across the competing airlines. We are proposing a shelf product assortment method for categorizing airline offers into utility levels, thus facilitating the choice task of air travelers. We describe possible known approaches, describe Sabre’s proposal, provide information on the optimization methods used, and propose future work in the field.
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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
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Szymanski, T., Darrow, R. (2023). Shelf placement optimization for air products. In: Vinod, B. (eds) Artificial Intelligence and Machine Learning in the Travel Industry. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-25456-7_9
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DOI: https://doi.org/10.1007/978-3-031-25456-7_9
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Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-031-25455-0
Online ISBN: 978-3-031-25456-7
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