Smart mobility in Milan, Italy. A cluster analysis at district level.


  • Nicola Cornali
  • Matteo Seminati
  • Paolo Maranzano Department of Economics, Management and Statistics (DEMS), University of Milano-Bicocca & Fondazione Eni Enrico Mattei (FEEM)
  • Paola Maddalena Chiodini Department of Statistics and Quantitative Methods (DISMEQ), University of Milano-Bicocca, Italy



Clustering, Aggregative indices, AMPI Index, Milano NILs, Smart mobility


We aim at evaluating the level of mobility services and infrastructures in the neighborhoods of Milan to establish which areas are better equipped concerning the citizens’ needs. We propose to study the overall degree of smart mobility in the city by ranking the 88 administrative districts, according to their transportation services. We perform a statistical analysis that allows us both to quantify the degree of mobility at district level as well as to group and sort them by increasing levels of smart mobility. In the first step, we built a set of composite indicators, including the AMPI and the Static Jevons Index, quantifying the smart mobility
level for each neighborhood of the city. In the second stage, the composite indices are used to cluster the districts into homogeneous groups characterized by similar mobility levels. The empirical application shows that, whether using the indices individually or in combination, the cluster analyses successfully distinguish key areas of the city, such as the interchange hubs, the university zones, the city center, workplaces, and suburbs. We identify four classes of districts, characterized by increasingly levels of smart mobility and highlighting critical differences among the city center and the peripheral areas of Milan.




How to Cite

Cornali, N., Seminati, M., Maranzano, P., & Chiodini, P. M. (2023). Smart mobility in Milan, Italy. A cluster analysis at district level. Statistica Applicata - Italian Journal of Applied Statistics, 34(3).



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