Abstract

In contemporary times, regulations have been established to govern access and integration of electric vehicles, which hold immense potential in mitigating the adverse impacts of transportation arising from escalating mobility demands and rapid urbanization. Nevertheless, their implementation poses intricate challenges due to the multifaceted nature of sustainability and other complexities, as they are considered a prospective solution to address the pressing issue of climate change and achieve holistic sustainability. Moreover, this study elucidates the methodological approach employed for selecting a comprehensive set of criteria to be considered in energy planning initiatives involving the incorporation of electric vehicles, encompassing both renewable and conventional energy sources. The selection process was informed through a thorough review of existing literature and the insightful input from experts, utilizing the Likert scale and arithmetic mean as reference benchmarks. The outcomes of this research have yielded the identification of 27 sub-criteria, categorized into five distinct groups: technical, economic, social, environmental, and risk-related factors, thereby enabling a comprehensive evaluation of energy planning projects associated with the adoption of electric vehicles. The findings derived from employing the hierarchical analytical process with fuzzy logic FAHP highlight the considerable potential of most criteria and sub-criteria in devising effective measures. Notably, criteria related to policy-governance and environmental aspects emerged as the most influential, according to the collective expertise of the consulted group. This study significantly contributes to enhancing sustainable mobility and advancing progress towards attaining sustainable development goals. By delineating pertinent criteria and sub-criteria for the planning process, this research augments the literature dedicated to supporting informed decision-making in sustainable transportation, particularly through the potential application of a Multi-Criteria Decision Analysis (MCDA) method.

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