An investigation into the impact of the built environment on the travel mobility gap using mobile phone data

The travel mobility gap is among the indicators that can be used to evaluate the level of social and transport inequity. To achieve a large and representative sample for this investigation of the different impacts of the built environment on travel mobility of various income and migrant groups, we have utilized big data from mobile phones for over 10 million users in Shenzhen, China. Travel mobility was measured by non-commute travel frequency and activity space. Our descriptive analysis demonstrates lower-income groups and migrant workers have lower levels of travel mobility than higher-income groups and non-migrant workers. The results produced by our linear regression models also reveal a significant travel mobility gap between different income and migration groups. That gap appears to be positively impacted by job density and bus stop distance and negatively impacted by residential density and metro station distance. Our modeling results also demonstrate that the travel mobility gap is larger in the outer suburbs than in the city center and inner suburbs. Our research findings reveal that the built environment influences the travel mobility gap, which implies that marginalized groups experience some degree of social inequality and exclusion. Based on these findings, we provide policy recommendations that aim to reduce the travel mobility gap between the marginalized and reference groups.