Modeling Airline Passenger Choice: Passenger Preference for Schedule in the Passenger Origin-Destination Simulator (PODS)

This thesis examines how to model the choice of individual travelers among various possible travel alternatives in the airline industry. A review of the models used to represent that choice situation in the Passenger OriginDestination Simulator (PODS) was undertaken for two reasons. First, the development of computational capabilities has lead to advancements in consumer choice theory that enabled the implementation of more flexible models like mixed logit models. Second, the increasing competition of low-cost new entrant airlines has put great pressure on pricing practices of traditional network carriers. This increasing competition has also compelled these carriers to focus on their strengths, for example, schedule coverage. In this thesis, after a comparison between the PODS Passenger Choice Model and the literature on consumer choice theory, we will then focus on how to model passenger preference for schedule. The review of the literature on air traveler choice reveals that most authors have used discrete choice models, like standard logit or nested logit models, to represent the choice of individual passengers among travel alternatives. However, the logit model has two limitations in the air traveler choice problem: it can accommodate neither random taste variation in some elements of the passenger utility function nor the complex substitution patterns across travel alternatives modeled in PODS. However, we show that the highly flexible mixed logit model brings a solution to these limitations and the choice process modeled in PODS can be approximated by a set of mixed logit models.