Investigating observed and unobserved variation in the probability of ‘not travel’ as a behavioural response to restrictive policies

•With mixed logit models, we investigate ‘not travel’ as a behavioral response.•The data includes close to 17,000 stated mode choices.•Car users are more prone to react with ‘not travel’ compared to PT-users.•The probability for ‘not travel’ is lower for work trips.•Travel distance has a significant...

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Bibliographic Details
Published inTransportation research. Part D, Transport and environment Vol. 77; pp. 63 - 76
Main Authors Flügel, Stefan, Fearnley, Nils, Killi, Marit
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2019
Subjects
Diversion
Monte-Carlo simulations
Passenger demand
Restrictive policy
Suppressed demand
Trip cancellation
Passenger demand
Monte-Carlo simulations
Restrictive policy
Diversion
Suppressed demand
Trip cancellation
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Summary:•With mixed logit models, we investigate ‘not travel’ as a behavioral response.•The data includes close to 17,000 stated mode choices.•Car users are more prone to react with ‘not travel’ compared to PT-users.•The probability for ‘not travel’ is lower for work trips.•Travel distance has a significantly positive effect. Besides technological improvements, restrictive car policies are likely to be the most effective measures for reducing greenhouse gas emissions from local passenger transport. Restrictive policies may lead some individuals to choose to not travel to otherwise useful or enjoyable activities. This paper therefore explores what factors drive the probability of ‘not travel’ as a behavioural response to restrictive policies. Using stated choice data among car owners in the 10 largest cities in Norway, we investigate observed and unobserved taste variation for ‘not travel’ given different (hypothetical) policies. The empirical evidence suggests that the likelihood of ‘not travel’ (a) is lower for work-related trips; (b) is higher where respondents state they have no decent alternatives; (c) increases with trip distance; and (d) increases with the intensity of the policy. We perform Monte-Carlo simulations illustrating different predicted choice behaviour for car users and public transport users under different types of stylized policies (travel time changes versus travel cost changes).
ISSN:1361-9209
1879-2340
DOI:10.1016/j.trd.2019.10.008