Airline reservations forecasting--probabilistic and statistical models of the booking process

Abstract

In this thesis, we develop the necessary statistical framework to produce accurate forecasts of total bookings in a particular fare class on a specific flight number departing on a given date at various points before departure. After an introduction to the basic terminology of the airline booking process, a rigorous probabilistic model is developed. The booking process is modeled as a stochastic process with requests, reservations, and cancellations interspersed in the time before a flight departs. The key result of the probabilistic analysis is a censored Poisson model of the airline booking process. A comprehensive statistical framework views the booking process from a data analysis perspective. We describe models based on advance bookings (the traditional booking curve) and historical bookings (a traditional time series model). An important development is the

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