Understanding neighbourhood design impact on travel behaviour: An application of structural equations model to a British metropolitan data

Paulus Teguh Aditjandra, Xinyu Cao, Corinne Mulley

    Research output: Contribution to journalArticlepeer-review

    104 Scopus citations

    Abstract

    The objective of this study is to explore whether changes in neighbourhood characteristics bring about changes in travel choice. Residential self-selection is a concern in the connections between land-use and travel behaviour. The recent literature suggests that a longitudinal structural equations modelling (SEM) approach can be a powerful tool to assess the importance of neighbourhood characteristics on travel behaviour as opposed to the attitude-induced residential self-selection. However, the evidence to date is limited to particular geographical areas and evidence from one country might not be transferrable to another because of differences in land-use patterns and land-use policies. The paper is to address the gap by extending the evidence using British data. The case study is based on the metropolitan area of Tyne and Wear, North East of England, UK. A SEM is applied to 219 respondents who reported residential relocation. The results identify that neighbourhood characteristics do influence travel behaviour after controlling for self-selection. For instance, the more people are exposed to public transport access, the more likely they drive less. Neighbourhood characteristics also impact through their influence on car ownership. A social environment with vitality also reduces the amount of private car travel. These findings suggest that land-use policies at neighbourhood level can play an important role in reducing driving.

    Original languageEnglish (US)
    Pages (from-to)22-32
    Number of pages11
    JournalTransportation Research Part A: Policy and Practice
    Volume46
    Issue number1
    DOIs
    StatePublished - Jan 2012

    Keywords

    • Longitudinal analysis
    • Neighbourhood characteristics
    • Residential self-selection

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