New Data Sources to Study Airport Competition

Traditionally, there is a lack of detailed information on passengers’ movements from and to the airports. This is due to the limitations in accuracy and coverage of methodologies like local surveys commonly used to obtain data in this context. As a consequence, managers and policy makers must take decisions based on partial information on passengers’ transport demands. Recent developments and popularization of the use of Information and Communication Technologies (ICT) provide new alternative data-sources allowing for the precise derivation of individual mobility at different spatial scales. This data may pose some challenges in terms of correcting potential biases, but it overcomes many of the traditional methods limitations. Here, we investigate how the availability of ICT data depicts a new comprehensive perspective on door-to-door air transport mobility. We do this by proposing three case studies involving three new sources of data: i) GPS records of taxi pickups; ii) a database of geolocated tweets including 10 million users tracked for two years in Europe; and iii) the travel-times between the user’s home and the alternative airports (provided by Google’s API). By integrating this data into simplified discrete choice models, we exemplify how the description of airport catchment areas can be treated in large cities served by more than one airport. This works illustrates how the air transportation system interacts with other transport modes in the passengers decision process. While passengers can still be described within the classical rational choice paradigm, new models must be developed to include the influence of ground transportation aspects in the passenger’s travel decisions.