The social dimension of cities is more and more being influenced by people’s capability to benefit from basic services, including urban mobility, one of the most important ones. Socioeconomic and demographic disparities may lead to inequalities in access to public transport and hove significant implications for social inclusion, quality of life and environmental sustainability. This paper examines the effect of some selected sociodemographic variables on public transport use in Genoa (Italy) using an ordered logistic regression approach. Residential location and sex are found to be the most important determinants of public transport use in the empirical results. Residents of suburban areas show a consistently lower tendency to use the public transit, and women tend to be the users more frequently than men. Such patterns reveal the structural mobilities of access in which inequalities in social well-being are produced across urban space. In this scenario, the inclusion of AI in urban transportation systems is examined as a possible policy 'lever' for reducing mobility inequalities and promoting collective well being. AI solutions – including predictive demand analysis, dynamic scheduling and personalised routing – could increase efficiency and access to services in areas of weaker transport provision. In promoting more reactive and inclusive mobility systems, such technologies could potentially promote not only environmental sustainability but also equity in urban living. In summary, this study demonstrates the importance of considering sociodemographic in shaping accessibility to mobility as a primary dimension of social well-being and fosters evidence-based use of data-driven and AI-enabled tools for urban transport planning. Discussion The results feed into the wider debate about how selective mobility policies might be used to counter social inequalities and contribute to more sustainable and inclusive urban development.
Measuring Well-Being and Territorial Inequalities: Multidimensional and Non-Compensatory Approaches to Sustainable Development
DE ANNA, MARTINA
2026-04-01
Abstract
The social dimension of cities is more and more being influenced by people’s capability to benefit from basic services, including urban mobility, one of the most important ones. Socioeconomic and demographic disparities may lead to inequalities in access to public transport and hove significant implications for social inclusion, quality of life and environmental sustainability. This paper examines the effect of some selected sociodemographic variables on public transport use in Genoa (Italy) using an ordered logistic regression approach. Residential location and sex are found to be the most important determinants of public transport use in the empirical results. Residents of suburban areas show a consistently lower tendency to use the public transit, and women tend to be the users more frequently than men. Such patterns reveal the structural mobilities of access in which inequalities in social well-being are produced across urban space. In this scenario, the inclusion of AI in urban transportation systems is examined as a possible policy 'lever' for reducing mobility inequalities and promoting collective well being. AI solutions – including predictive demand analysis, dynamic scheduling and personalised routing – could increase efficiency and access to services in areas of weaker transport provision. In promoting more reactive and inclusive mobility systems, such technologies could potentially promote not only environmental sustainability but also equity in urban living. In summary, this study demonstrates the importance of considering sociodemographic in shaping accessibility to mobility as a primary dimension of social well-being and fosters evidence-based use of data-driven and AI-enabled tools for urban transport planning. Discussion The results feed into the wider debate about how selective mobility policies might be used to counter social inequalities and contribute to more sustainable and inclusive urban development.
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