Composite Indices for Adoption of Electric Vehicles (EVs)

This study focused on developing composite indices (CI) to determine the degree to which electric vehicles (EVs) may be adopted by consumers, manufacturers, and investors. These indices may be used as gauges of where resources should be allocated in the EV industry. The first step was to collect opinions from six experts who provided inputs as fuzzy numbers. They provided inputs on twelve different factors which were divided into three categories: Design and Manufacture, Performance and Efficiency, and Sustainability and Environment. The CIs were developed for each category. Using the fuzzy inputs, two different methods of aggregating the opinions were used: the first was the Agreement Matrix method (AM) which focused on the degree of agreement among the experts, and the second one was called the Normalized Defuzzification method (ND) that focused on the weights of various factors as well as a signal-to-noise ratio metric. In order to compare the CIs obtained from these methods, the idea of information loss was used. After performing the calculations, it was observed that the AM method had lower CI information losses for all three categories. A few extensions of this study are provided in the conclusion.