The number of studies using discrete choice models in the analysis of airtravel choice behaviour has increased steadily over recent years. The majority of such research has made use of Revealed Preference (RP) data, generally in the form of survey data collected from departing air passengers. In many of these studies, the absence of adequate and detailed level-of-service information relating to the choices actually faced by respondents leads to an inability to offer a reliable treatment of factors such as air fares, flight availability and airline allegiance. The main aim of this paper is to illustrate how Stated Preference (SP) data can be used to alleviate these problems. The biggest advantage of SP data in the present contextcomes in the form of exact data on the choices that respondents were actually faced with. As such, aside from having detailed level-of-service information, the issue of uncertainty with regards to flight availability doesnot come into play. However, another major difference arises between the use of RP and SP data in air travel research. In general, one of the variables with the greatest explanatory power in RP case studies of air travel choice behaviour is flight frequency. However, it should be noted that, with the possible exception of travellers on very flexible tickets, frequency is not taken into account by travellers in the way it is modelled. Rather, it captures a host of other factors, most notably visibility, capacity,and schedule delay between the actual and optimal departure time, on the basis of an assumption of a relatively even spread of departure times. In the case of SP data, visibility and capacity need not be taken into account, as described above. And by presenting travellers with a set of actual disaggregate flight options, frequency does not play a role in the description of the alternatives. However, given the use of disaggregate flight options, a treatment of schedule delay becomes possible, given that information is now generally available on the differences between the actual and desired arrival times for each of the flight options. Aside from illustrating the potential advantages of SP data in the analysis of air travel choicebehaviour, this paper however also looks at two issues related to modelling methodology. Firstly, the study aims to explore continuous interactionsbetween taste coefficients and socio-demographic variables, thus for example allowing for decreasing sensitivity to access time or flight fare on longer flights. This treatment of deterministic taste heterogeneity, which has clear conceptual advantages over more arbitrary segmentation approaches, does not seem to have found widespread application in air travel research thus far. It should also be said that the rise in popularity of mixturemodels has contributed to this situation, with modellers increasingly relying purely on a random treatment of taste heterogeneity, despite the advantages of the other methods in terms of interpretation. Secondly, the mainestimation work is preceded by a detailed investigation of the non-linearities in response to changes in explanatory variables, using a preliminaryanalysis based on Box-Cox transforms. The aim of this analysis is to explore the potential for using non-linear transforms for a number of attributes that are generally treated in a linear fashion. Finally, the study usesmixture as well as closed-form model structures, where the former allow for a representation of random variations in tastes across individuals, in addition to those variations explained in a deterministic fashion, such asfor example with the use of the continuous interactions described above. In common with many previous studies, the results of the analysis presented in this paper highlight the important role that ground-level distance plays in airport choice behaviour. However, while, in RP studies, it has often not been possible to retrieve a significant and meaningful effect of changes in air fares, the results from this SP study show air fare to be thevariable with the most explanatory power, across the three population segments used in the analysis. This result is consistent with intuition, and highlights a certain advantage of SP data in this context, given that reliable information is available on the choices that respondents were actually faced with. Additionally, in the context of SP data, data protection issues in relation to frequent flier programmes do not apply. For the covering abstract see ITRD E135582.
Samenvatting