Extension of MEREC-CRADIS methods with double normalization-case study selection of electric cars

Abstract

Climate changes and the number of people in the world are increasingly affecting the environment. In order to reduce this impact, there are more and more alternatives to cars with internal combustion. Currently, the most used alternative is electric cars. This research aimed to rank electric cars according to their characteristics. It was selected 13 criteria according to which 20 alternatives were ranked. For this purpose, it was used two methods, DNMEREC (Double normalization Method based on the Removal Effects of Criteria) used to determine criterion weights objectively and DNCRADIS (Double normalization Compromise Ranking of Alternatives from Distance to Ideal Solution) method used to rank alternatives. Here, classical methods for multi-criteria decision-making (MCDM) are extended to contribute to a more stable ranking of alternatives. Unlike similar approaches, the same normalization has been used here, but in two ways, which represents an innovative approach in MCDM. The results of this approach have shown that the best-ranked alternative is A6 (Sono Sion), while the worst-ranked alternative is A2 (Smart EQ forfour). These results were confirmed with a comparative analysis of the results obtained using other MCDM methods and sensitivity analysis. The validation of the results and the application of the Spearman correlation coefficient have shown that the ranking of the alternatives is uniform and more stable when double normalization is applied than when classical methods with their normalization are used. In addition, this decision-making provides support to potential buyers for choosing electric cars.