Air and HST multimodal products. A segmentation analysis for policy makers

Abstract

Different solutions for the integration of high-speed rail (HSR) and air transport could be implemented, ranging from very basic integration to more sophisticated systems that include ticket and handling integration. This paper uses two statistical techniques, name cluster analysis and discrete choice models in order to investigate how different market segments have a determining influence in being more proactive to change to HSR for the second leg in multimodal trips. A discrete choice experiment is conducted to better understand passengers' preferences. We obtain a number of clusters and estimate flexible choice models, taking into account the panel nature of stated preference data. We obtain a range of willingness-to-pay values for service quality attributes, finding results that can be used to infer policy conclusions about the real attractiveness of the Air-HSR integrated alternative. In this respect, clusters and schedule coordination, which reduces connecting time, are crucial to explain HSR attractiveness.