Whether, when and which: Modelling advanced seat reservations by airline passengers. (February 2020) - Shao, Shuai; Kauermann, Göran; Smith, Michael Stanley
Abstract: Motivated by the growing importance of ancillary revenues in the airline industry, we propose a statistical model for Advanced Seat Reservation (ASR). We focus on the questions of whether, when and which seats are selected by passengers. To answer these questions, we employ a discrete time duration model, combined with a multinomial choice model with varying consideration set. Unknown smooth covariate effects are used, along with seat-specific random effect terms for seat selection. The model is applied to a rich dataset of 485, 279 bookings on five intercontinental routes, extracted from the complete booking database of a major European airline. We find strong evidence of 'middle seat avoiding' and 'front seat preferring' effects, along with substantial additional seat-specific heterogeneity. We also show that the probability of making an ASR depends on its price in relation to the ticket price, the distribution channel, the number of days to departure and seasonal effects. These and other insights allow for product differentiation and variable pricing in ASR for each and every seat. In addition, simple variations of the statistical model can also be used for other ancillary products—such as on-board dining and preferential baggage checking—that are purchased in the same way as ASR.