Abstract

Urban Mobility is a complex phenomenon with many actors involved that has been changing due to the diffusion of Sharing Mobility. This shifting is affecting individual habits and cities dynamics, which need to be considered by policy makers and operators for better programming services and incentives. This paper aims at improving the way sharing mobility is analyzed and monitored. We propose and test a methodology, based on the theory of networks, aimed at studying sharing mobility dynamics among the districts of a city. The method uses data tracking people’s movements made with shared vehicles, developing a set of geo-localized measures with the potential to be suited to different purposes. Insights coming from this type of analysis, can be used as a support tool for decision-making processes in the mobility field. The methodology is applied to the city of Milan with data coming from BikeMi -Milan’s bike sharing program- and Urbi, a platform that handles real-time data from car sharing providers such as Enjoy, Car2go and Share’nGo.