Agus Sidiq Purnomo, Handaru Jati, Sri Kusumadewi
Along with increasing awareness of environmental sustainability and the demand for green technology, including electric vehicles. However, decision-making in the selection of electric vehicles involves a variety of complex aspects that require a systematic approach. This article provides a systematic review in the form of an analysis of 46 research articles related to the decision-making aspects of electric vehicle selection. The results show a significant increase in publications from 2015-2025 with a focus on economic factors (25-30%), charging infrastructure (20-25%), government policies (15-20%), and environmental awareness. Bibliometric analysis revealed 38 key keywords with a total link strength of 117, showing the complexity of the relationship between factors. This research provides the foundation for the development of an artificial intelligence-based decision support system that integrates multi-criteria decision making methods (AHP, TOPSIS, PLS-SEM) for optimal electric vehicle selection. The findings emphasize the importance of government incentives and the availability of infrastructure, while also providing a framework for the integration of artificial intelligence in personalized recommendation systems. © 2025 IEEE.
Universitas Negeri Yogyakarta, Faculty of Engineering, Yogyakarta, Indonesia; Universitas Mercu Buana Yogyakarta, Faculty of Information Technology, Yogyakarta, Indonesia; Universitas Islam Indonesia, Faculty of Industrial Technology, Yogyakarta, Indonesia
