Publication type
Journal Article
Series Number
Author
Publication date
December 1, 2025
Summary:
Amid the growing enthusiasm to use land-use and transport policy measures to encourage greater sustainable travel, the need to understand the nuance of where such interventions are effective, how they work, and who they impact is essential. Yet, the relative importance of who we are and where we live in shaping travel behaviours remains contested. This paper examines this relationship more closely by studying the relative importance of built environment characteristics, life-stage transitions, and selection mechanisms in shaping commuting behaviours across the UK. To do this, linear probability models are used to investigate how these variables impact the probability of switching commute mode. Individual-level longitudinal data capturing the period immediately before relocation and multiple periods post-relocation are paired with highly disaggregated spatial data. I find that life-events and selection mechanisms exert greater influence over the probability of switching commute mode than static built environment measures, while dynamic measures appear more prominent (especially when considering the probability of switching to public transport), implying that commute mode choices depend less on where people live than on how easily they can move. The probability of switching to cars is linked to life disruptions and socioeconomic pressures, particularly among low-income individuals. The probability of switching to active modes is highly individualised, especially among high-income individuals. Mid-income individuals respond dynamically to a broad range of triggers, appearing sensitive to cost and convenience. From a policy standpoint then, interventions targeting accessibility and socioeconomic constraints may be more effective in shaping travel behaviour than static land-use strategies.
Published in
Papers in Regional Science
Volume
Volume: 104
DOI
https://doi.org/10.1016/j.pirs.2025.100128
ISSN
10568190
Subjects
Notes
Open Access
Under a Creative Commons license
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