Psychological factors are generally thought to play an important role in the prediction of individual variations in travel behavior and travel related choices. To assess their effects in statistical models, three assumptions are typically made, namely: (1) the psychological factors influence behavior/choices and not vice versa, (2) psychological factors can be conceptualized as latent variables measured by observed indicators and (3) estimated between-person relationships are indicative of within-person relationships. Recent research has shown that each of these assumptions is conceptually and empirically problematic. This paper introduces to the field of travel behavior research an alternative modeling approach which has its roots in the emerging field of Network Psychometrics. This so-called psychological network model avoids the above mentioned problematic assumptions, by modeling the relationships between attitudinal and behavioral indicators as dynamic causal systems which can be operationalized as a network. We illustrate the new insights that may be gained from this approach in a travel behavior context. In particular, we estimate between-person and within-person network models using data from a (two-wave) panel survey containing indicators regarding travel modality use and related attitudes. Our results indicate that the extent to which the use of a mode is considered convenient is most strongly connected to the actual use of the corresponding mode, and that the convenience of using the car takes a central position in the attitude-behavior network. At the within-person level, no strong connections between attitudes and behaviors seem to exist. This latter finding serves as a warning against the practice, embodied in many popular travel behavior models, of interpreting associations between attitudes and (travel) behaviors as causal within-person relations.
|Number of pages||13|
|Journal||Transportation Research Part A: Policy and Practice|
|Publication status||Published - 2020|
- Between-person and within-person
- Latent variable
- Psychological network model
- Travel behavior