Trends in long-distance travel are of utmost importance for sustainable transport, and have the potential to offset promising trends in daily mobility such as 'peak car'. While the factors driving increasing demand for long-distance travel are still relatively poorly understood, existing research suggests that some factors may have different effects on short- and long-distance travel. There is growing evidence of important self-reinforcing dynamics in long-distance travel at the societal level, but also at the micro-level - over individual life courses and across generations. These issues identify the starting point for the project.
Firstly, long distance travel will be theoretically conceptualised from a mobility biography perspective. Secondly, three points will be empirically addressed using three datasets from the UK and Germany:
The findings will contribute to an improved understanding of how the social ‘need’ for high levels of long-distance travel is being locked-in, while providing important knowledge for sustainable transport policies.
Methodologically, the project will consist of quantitative analysis of existing survey data. Data analysis techniques will mainly include descriptive statistics, regression models, structural equation modelling and classification techniques (cluster analysis, latent class analysis). The datasets used will include a bespoke survey on integenerational mobility biographies developed by TU Dortmund/VPL, ´Understanding Society´and the National Travel Survery of England.
3 years (October 2018 – September 2021)
