Repository logo

Identification and mapping of spatial variations in travel choices through combining structural equation modelling and latent class analysis: findings for Great Britain

Published version

Change log


Jahanshahi, Kaveh 


This paper exploits some latest advances in structural equation modelling (SEM) and latent class analysis (LCA) for identification and mapping of the spatial variations in travel choices. The approach controls for a wide range of socioeconomic and demographic variables and changes in car fuel prices. The research is focused on employed and self-employed adults, and the method can be readily extended to cover other travellers where such needs arise. The developed methodology enables us to overcome some of the persistent issues that have in the past prevented researchers making a full use of highly correlated and endogenous variables found in good-quality, comprehensive travel surveys at the national or metropolitan scales. Empirical findings from an application of the methodology for Great Britain provide a precise geographical classification of neighbourhoods areas across Britain and reveal the extent to which land use and built form influence commuting travel choices, whilst accounting for residents’ self-selection, spatial sorting and endogenous interactions among the explanatory variables. The results are cogent for defining spatially adapted strategies for planning new transport and land use interventions, particularly in areas that are expected to grow the most in the coming decades.

Keywords: structural equation modelling, latent class analysis, UK National Travel Survey, commuting travel, built-up area classification, travel behaviour, influence of land use and built form on travel


Funder: UK Department for Transport


Structural equation modelling, Latent class analysis, UK National Travel Survey, Commuting travel, Built-up area classification, Travel behaviour, Influence of land use and built form on travel

Journal Title


Conference Name

Journal ISSN


Volume Title



Springer Nature
Engineering and Physical Sciences Research Council (EP/N021614/1)
UK Dept of Transport and Key Laboratory of Eco Planning and Green Building, Ministry of Education (Tsinghua University), China