Three-way decision based on ITARA and public weights DEA under picture fuzzy environment and its application in new energy vehicles selection

Abstract

AbstractPetroleum is the main power of automobiles, yet the environmental pollution it brings has caused globally. The promotion of new energy vehicles (NEVs) is effective. Even though the governments have introduced various supports for the popularization of NEVs, many enterprises and individuals continue to drive gas vehicles as they are poorly informed about them and cannot choose the right products. This paper proposes a categorization and ranking model of NEVs over three-way decisions (TWD) to tackle the problem. Picture fuzzy sets serve as a valid tool to describe uncertainty and fuzziness information. At first, the attribute weights are ascertained with the indifference threshold-based attribute ratio analysis (ITARA) method improved by the picture fuzzy distance. Then, the public weight picture fuzzy data envelopment analysis (DEA) which is enhanced by the picture fuzzy aggregation operator is employed for the conditional probability of decision units. Third, updated picture fuzzy TWD is utilized for the categorization and ranking. Fourth, the enterprise NEVs selection case is tested for the model. Later, comparative analysis with the classical methods illustrates that the proposed method yields accurate and reliable decisions. Finally, the robustness of the model is demonstrated by sensitivity analysis.