A process-oriented hesitant fuzzy linguistic decision field theory: Application to the selection of new energy vehicles

Abstract

The new energy vehicle industry is thriving with high energy efficiency and environment friendly characteristic and how to select them is a significant comprehensive assessment problem. In the new energy vehicle assessment, the decision makers often encounter some qualitative evaluations which contain several adjacent linguistic terms, that is the hesitant fuzzy linguistic term set, to express their opinions with indicators. The existing hesitant fuzzy linguistic decision-making methods are mainly result-oriented which neglect the dynamic process of information processing. Therefore, we propose a process-oriented hesitant fuzzy linguistic decision field theory to modify the process-oriented decision-making methods combining the decision makers’ preference evolution processes. First, we introduce the BoD method which highlights the advantage indicator and maximizes the comprehensive score of each alternative to endow the weight. Next, the decision field theory is expanded to the hesitant fuzzy linguistic environment combining the normalized carbon emissions. The carbon emission-based preference and time constraint are taken into account to make the decision-making process conform to human decision-making behavior. Finally, the process-oriented decision-making method is applied to select the optimal new energy vehicle. The sensitivity analysis and comparative analysis verify the effectiveness and robustness of the proposed method.