Grouping travelers on the basis of their different car and transit levels of use

Bibliographic Data

ID19338528
AuthorsMarco Diana (0000-0003-3832-6834, Politecnico di Torino, corresponding author), Patricia L Mokhtarian (0000-0001-7104-499X, University of California, Davis)
Year2009
Volume36
Issue4
Pages455-467
Publication date2009-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueTransportation (JOURNAL)
Journal identifiersISSN: 0049-4488 • E-ISSN: 1572-9435
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11116-009-9207-y
OpenAlexW2135058383
LanguageEN
Citations received8
References cited14

Market segmentation studies in travel behavior research are ordinarily based on socioeconomic characteristics and personality traits. This study explores the usefulness of a different approach, where the actual overall mobility levels across different ground transportation modes, along with desired changes in the use of cars and transit, are used as clustering variables. Using a given mode can in fact influence the personal representation of that mode, which in turn has been proven to be a key element in transport behaviours. We form such multimodality-based clusters from two field studies, one involving employees of the French transportation research institute INRETS and the other a representative sample of residents of the US San Francisco Bay Area. We find that strong users of a given mode would like to bring more balance to their “modal consumptions” by decreasing the use of this mode more than the average, and increasing the use of the alternative mode. However, concerning ground transport travel budgets, the desire to travel more (or less) overall seems less strongly related to the composition of the modal balance. The US dataset shows also a greater latent demand for travel than the French one. Socioeconomic characteristics of the clusters could not explain the patterns that were found, confirming the importance of taking into account multimodality issues in travel behavior research. Some policy implications from these findings are finally reported

Balance (ability) · Business · Econometrics · Economic geography · Economics · Geography · Market segmentation · Modal · Mode (computer interface) · Mode choice · Multimodality · Public transport · Regional science · Sample (material) · Socioeconomic status · Sociology · Transport engineering · Travel behavior · Travel survey · Computer Science · Consumer Behavior in Brand Consumption and Identification · Demography · Engineering · Marketing · Psychology · Transportation Planning and Optimization · Urban Transport and Accessibility

Tools

Open DOISci-HubOpen Access