Towards Sustainable Cities: A KPI-Based Method to Compare Cities’ Performance and Encourage the Spread of Electric Cars

Alvaro Menendez Agudin, Claudia Caballini (), Francesco Paolo Deflorio, Gregorio Fernandez Aznar, Leopold Herman and Klemen Knez
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Alvaro Menendez Agudin: DC Systems, Energy Conversion and Storage Group, Department of Electrical Sustainable Energy, Delft University of Technology, 2600 AA Delft, The Netherlands
Claudia Caballini: Department DIATI-Transport Systems, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Francesco Paolo Deflorio: Department DIATI-Transport Systems, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Gregorio Fernandez Aznar: CIRCE, Centro de Investigación de Recursos y Consumos Energéticos, Parque Empresarial Dinamiza, Avda. Ranillas, 50018 Zaragoza, Spain
Leopold Herman: Faculty of Electrical Engineering, University of Ljubljana, Kongresni trg 12, 1000 Ljubljana, Slovenia
Klemen Knez: Faculty of Electrical Engineering, University of Ljubljana, Kongresni trg 12, 1000 Ljubljana, Slovenia

Sustainability, 2025, vol. 17, issue 7, 1-27

Abstract: European cities have adopted different solutions to address the challenges of charging infrastructure for electric vehicles, depending on their specific characteristics and needs. The widespread adoption of effective solutions could accelerate the transition towards more sustainable urban mobility. However, as cities differ in socio-economic, infrastructural, and environmental aspects, a one-size-fits-all approach may not be suitable. Currently, there is a lack of studies in the literature that identify similarities among cities to support the development of shared strategies for sustainable electric mobility. This paper contributes to filling this gap by proposing a methodology based on Key Performance Indicators (KPIs) to classify and compare cities according to their electric vehicle infrastructure. Using quantitative data from 80 European cities across civil, social, and transport-related factors, as well as electric vehicle charging characteristics, we identified five reference city clusters. A sensitivity analysis, conducted across 30 scenarios, validated the robustness of the KPI framework. This approach provides a tool for policymakers to monitor the evolution of charging infrastructure, supporting data-driven decision-making for sustainable urban mobility. By promoting efficient and adaptable electric vehicle policies, this study aligns with the objectives of the 2030 Agenda for Sustainable Development, particularly in fostering sustainable cities and clean energy adoption.

Keywords: urban sustainable mobility; electric cars; charging infrastructures; KPIs; clusters; robustness; K-Means clustering method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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