# Beyond person‐centered approaches: Integrating individual, sociodemographic and socio‐spatial factors to better understand active and sustainable mobility

## TL;DR

This study explores how personal, social, and environmental factors together influence sustainable travel choices like walking, biking, and public transport.

## Contribution

The study integrates individual, sociodemographic, and socio-spatial factors in a multi-level analysis of sustainable mobility.

## Key findings

- Socio-spatial, sociodemographic, and individual factors independently predict active and sustainable mobility.
- Intention toward sustainable mobility interacts with bike and transport pass ownership.
- Local-specific factors like mountainous terrain influence mobility behavior.

## Abstract

Although several determinants of travel mode choices have been identified, most research has adopted a mono‐disciplinary perspective. This study simultaneously investigated individual, socio‐spatial (at the national and local level), and sociodemographic factors of active and sustainable mobility (walking, biking, and public transportation) to better understand their relationships. A mixed‐methods was used, combining an online quantitative survey (N = 538, 54.83% women), three focus groups (n = 9, three women), and eight individual interviews (five women). The survey examined the facilitators and barriers of active and sustainable mobility (ASM) during a typical week using multiple linear regressions. Interviews and focus groups, with mobility experts and car users wishing to reduce their car use in Grenoble, were analyzed through reflexive thematic analysis. Quantitative results highlighted socio‐spatial (e.g., having a transport pass, trip chain complexity), sociodemographic (having children aged 12+), and individual factors (e.g., car attitudes, ASM habits, perceived health) as independent predictors of ASM. Moreover, intention toward ASM interacted with bike and transport pass ownership. Qualitative findings revealed local‐specific factors, such as living in mountainous areas. These results emphasize the importance of studying behavior as part of a complex system with multi‐level factors and using both national and local samples to better identify facilitators and barriers.