Research team: Niccolò Salvini, Luca Secondi and Tiziana Laureti
The research activity focused on statistical analysis and predictive modeling, with particular attention to spatial dependence and the provision of robust estimates of inequalities in access to transport. In parallel, the results were disseminated through participation in scientific conferences and the publication of articles in international peer-reviewed journals.
Phase 1: Literature review and definition of the conceptual framework
In the first phase of the research activity, an in-depth review of the scientific literature on transport poverty was conducted, with particular attention to the definition and conceptualization of transport poverty in its main dimensions: accessibility, affordability, and exposure to transport externalities; the existing methodologies for measuring transport poverty at the individual, household, and territorial levels; approaches integrating the monetary and temporal dimensions of transport burden; and the role of spatial dependence in the distribution of transport opportunities. The literature review highlighted that studies integrating income data with geographically explicit mobility patterns are still relatively scarce, thus identifying a significant research gap that the present work aims to address.
Phase 2: Data acquisition and integration
The research activity required the acquisition and integration of multiple data sources.
Commuting flow data
Data from the origin–destination matrix of commuting flows from the 2021 ISTAT Census were acquired, documenting the flows of workers between Italian municipalities. For the study area (Tuscany), all pairs of municipalities with commuting flows to and from the Province of Florence were selected, for a total of 4,389 unique origin–destination pairs.