Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers

Eric Molin, Patricia Mokhtarian, Maarten Kroesen

Research output: Contribution to journalArticleScientificpeer-review

86 Citations (Scopus)
265 Downloads (Pure)


For developing sustainable travel policies, it may be helpful to identify multimodal travelers, that is, travelers who make use of more than one mode of transport within a given period of time. Of special interest is identifying car drivers who also use public transport and/or bicycle, as this group is more likely to respond to policies that stimulate the use of those modes. It is suggested in the literature that this group may have less biased perceptions and different attitudes towards those modes. This supposition is examined in this paper by conducting a latent class cluster analysis, which identifies (multi)modal travel groups based on the self-reported frequency of mode use. Simultaneously, a membership function is estimated to predict the probability of belonging to each of the five identified (multi)modal travel groups, as a function of attitudinal variables in addition to structural variables. The results indicate that the (near) solo car drivers indeed have more negative attitudes towards public transport and bicycle, while frequent car drivers who also use public transport have less negative public transport attitudes. Although the results suggest that in four of the five identified travel groups, attitudes are congruent with travel mode use, this is not the case for the group who uses public transport most often. This group has relatively favorable car attitudes, and given that many young, low-income travelers belong to this group, it may be expected that at least part of this group will start using car more often once they can afford it. Based on the results, challenges for sustainable policies are formulated for each of the identified (multi)modal travel groups.

Original languageEnglish
Pages (from-to)14-29
Number of pages16
JournalTransportation Research. Part A: Policy & Practice
Publication statusPublished - 2016

Bibliographical note

Available online 10-12-2016


  • Attitude
  • Factor analysis
  • Latent class cluster analysis
  • Mode choice
  • Mode frequency
  • Multimodality


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