Electric vehicle selection for industrial users using an interval-valued intuitionistic fuzzy COPRAS-based model

Abstract

According to reports from international bodies such as the World Health Organization and the United Nations, transportation is one of the leading contributors to environmental pollution and climate change. Electric vehicles present a practical solution to reducing emissions, particularly for industrial users. However, industrial users' selection of electric vehicles involves different dynamics than individual users, making it a more complex process for companies. This paper aims to evaluate the selection criteria for electric vehicle fleets among industrial users using a novel multi-criteria decision-making framework based on interval-valued intuitionistic fuzzy sets. The model assesses various factors influencing industrial users' decisions and ranks the available electric vehicle options accordingly. The results indicate that driving range, purchase price, and charging time are the most influential factors in the decision-making process. Furthermore, the findings confirm that the Tesla Model S P100D is the most suitable option for industrial users, given its superior performance in these critical criteria.