On the selection of relevant historical demand data for revenue management applied to transportation

Ernst Ahlberg (), Irina Mirkina, Alfred Olsson (), Christian Söyland () and Lars Carlsson ()
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Ernst Ahlberg: Uppsala University
Alfred Olsson: Stena Line
Christian Söyland: Stena Line
Lars Carlsson: University of London

Journal of Revenue and Pricing Management, 2023, vol. 22, issue 4, No 4, 266-275

Abstract: Abstract The success of revenue management models depends to a large extent on the quality of historical data used to forecast future bookings. Several theoretical models and best practices of handing historical data have been developed over the years, that all rely on assumptions about underlying distribution and seasonality in the historical data. In this paper, we describe a novel method that compares the fingerprints of the departure to optimise and selects historical departures without making assumptions on data distribution or seasonality. By evaluating the method at the departure level and using the Nemenyi rank test, we show the method’s application in the ferry transportation business and discuss its advantages.

Keywords: Revenue management; Pricing; Historical demand; Departure clustering (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1057/s41272-022-00371-0

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