Data-Driven Decision Aids for Purchasing Battery Electric Vehicles Based on PROMETHEE-II Methodology - Xiuhong Niu; Yongming Song; Hongli Zhu (IEEE Access, 2024)
Considering the significant contribution of the transport sector to carbon emissions, the importance of battery electric vehicles (BEVs) as environmentally friendly vehicles is self-evident. Due to the rapid expansion of the BEV market in recent years, a comprehensive evaluation of BEV options from the consumer perspective has become an important issue. This paper proposes a data-driven decision aids for purchasing BEVs based on a multiple criteria decision-making methodology (i.e., PROMETHEE-II). A hierarchical evaluation criteria system of BEVs is constructed and correlation analysis between indicators is performed to eliminate duplicate indicators. Then, a comprehensive weighting method by integrating large-scale group decision making method and the Entropy-based method is proposed to identify the weights of criteria. Based on which, the ranking of candidate BEVs can be obtained based on the PROMETHEE-II with a hierarchical evaluative criteria, which can help consumers make BEV purchase choices. Furthermore, the robustness and reliability of the results are tested by applying the sensitivity analysis and contrastive analysis.