Grouping Travelers on the Basis of their Different Car and Transit Levels of Use
AbstractMarket 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 â€˜â€˜modal consumptionsâ€™â€™ 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.
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Bibliographic InfoPaper provided by Institute of Transportation Studies, UC Davis in its series Institute of Transportation Studies, Working Paper Series with number qt6dr2j387.
Date of creation: 26 Apr 2009
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Other versions of this item:
- Marco Diana & Patricia Mokhtarian, 2009. "Grouping travelers on the basis of their different car and transit levels of use," Transportation, Springer, vol. 36(4), pages 455-467, July.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Diana, Marco & Pronello, Cristina, 2010. "Traveler segmentation strategy with nominal variables through correspondence analysis," Transport Policy, Elsevier, vol. 17(3), pages 183-190, May.
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