Prioritizing Urban Policy Measures for Sustainable Electric Vehicle Using Fuzzy DAHP

Urban transport systems require policy choices that reflect financial constraints and public response while addressing environmental pressures. The development of sustainable electric vehicle (EV) mobility in cities depends on selecting measures that align with municipal budgets and public expectations. This study applies the Fuzzy Delphi Analytical Hierarchy Process (FDAHP) to prioritize urban policy measures for sustainable electric mobility in Calabria, southern Italy. Expert judgments were collected through pairwise comparisons and converted into triangular fuzzy numbers to account for uncertainty in subjective evaluations. The aggregated fuzzy comparison matrix was then used to calculate and defuzzify the relative weights of six policy alternatives. The results indicate that Public Fleet Electrification and Free Urban Parking for EVs receive the highest priority, followed by Charging Infrastructure Investment. These findings suggest that, under constrained municipal budgets and local implementation challenges, policies directly manageable by urban authorities may offer more feasible pathways for promoting sustainable electric mobility.