Empowering User-Centric Selection of Electric Vehicles Charging Stations: A Hybrid Approach Using the Best–Worst Method and Grey Relational Analysis

Abstract

The increasing adoption of electric vehicles offers a way to combat the harmful impacts of climate change and to improve city living standards. Yet limited access to and lack of consistency among electric vehicle charging stations present obstacles for electric vehicle owners. This study advocates for an approach that positions the preferences of electric vehicle drivers first when choosing an electric vehicle charging station. By considering relevant factors to electric vehicle drivers and treating the problem as a grey system where certain information is known while other aspects are unknown, this research aims to empower users to make decisions aligned with their needs. The best–worst method is employed to assign preferences allowing electric vehicle users to make informed choices based on their priorities. The grey relational analysis method is utilized to rank electric vehicle charging stations based on user preferences. The best–worst method-grey relational analysis approach, as shown by examples, efficiently assists electric vehicle users in choosing the optimal electric vehicle charging station. This study acknowledges and incorporates the often-overlooked perspectives of electric vehicle drivers into a user-centric solution in existing research models. The gained insights carry significance for managing transportation and energy systems and designing user-friendly applications pertaining to electric vehicle charging station selection.