Abstract
Besides its undeniable advantages, personal car use generates a wide array of problems, among which its contribution to global warming is probably the most severe. To implement sound policies that are effective in reducing private car use, it is essential to first understand its important antecedents. Structural, psychological and contextual predictors were extensively studied independently, yet integrative approaches that investigate all these factors in a single theoretical model are lacking. The present study contributes to a more comprehensive understanding of car use behavior by proposing a model that includes structural, psychological and contextual determinants and tests this model on an international sample of drivers (N = 414). Responses were analyzed using a structural equation modeling approach. Results show that car use habits, perceived behavioral control, policy measures, fuel cost, infrastructure, temperature and level of precipitations significantly influence car use behavior. Such results support the inclusion of both structural (i.e., hard) and psychological (i.e., soft) factors in the design of policy interventions, while also considering contextual situations. Implications for policy and practice are discussed.
Highlights
Road transportation serves many personal and societal needs, yet it generates a wide array of problems
Principal axis factoring with Promax rotation was used as the extraction method, resulting in nine factors with eigenvalues higher than 1, which explained together about 65% of the variability
Measures to lessen the impact of car use habits and to strengthen perceived behavioral control to use transportation alternatives have already been implemented with promising results
Summary
Road transportation serves many personal and societal needs, yet it generates a wide array of problems. TDM measures are generally classified into two categories: Measures aiming to modify travel behavior by modifying social conditions or structures are called structural measures, while those aiming to modify people’s perceptions, beliefs, attitudes, values or norms are the so-called psychological measures (Steg, 2003; Bamberg et al, 2011). These two types of measures change important structural and psychological determinants (e.g., individual variables, travel infrastructure, economic disincentives, etc.) in order to modify travel behavior. Aside from these two types of factors, research shows that people’s
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