Social network analysis of electric vehicles adoption: a data-based approach

Mobility is undergoing dramatic transformations, that are driven by new needs of the users and environmental concerns. The most mature one is the process of Electric Vehicles (EVs) adoption, but it is still struggling to affirm itself due to many social and economic barriers that play a crucial role in this process, ranging from level of education, environmental awareness, age and census. This work aims at contributing to the study of this adoption process through a data-based lens. To this end we setup a social network, whose topology is built by using proximity measures that emerge from the analysis of real trips, while the initial disposition of the each driver towards the EV technology is inferred from its real mobility patterns. A cascade model is then simulated to investigate the dynamics of the adoption process under different scenarios.