This paper investigates the rank reversal issue in the selection of new energy vehicle types,focusing on consumers aged 20 to 30.It employs both the AHP and the PCbHA methods to rank four types of the new energy vehic...This paper investigates the rank reversal issue in the selection of new energy vehicle types,focusing on consumers aged 20 to 30.It employs both the AHP and the PCbHA methods to rank four types of the new energy vehicles-pure electric vehicles,plug-in hybrid electric vehicles,range-extended electric vehicles,and fuel cell vehicles,based on ten influential factors:purchase cost,maintenance cost,fuel and electricity cost,safety,passability,endurance,appearance,brand power,power,and space.To verify the effectiveness of the PCbHA method in addressing the rank reversal problem,one alternative option is removed,and the ranking is recalculated with subsequent analysis of the results.The study finds that rank reversals often stem from the closeness of alternative weights.Through sensitivity analysis,this research reveals the impact of endurance attribute weight on decision outcomes,indicating that when the endurance weight reaches 0.35,the ranking of pure electric vehicles and range-extended electric vehicles reverses.展开更多
基金Supported by The Ministry of Education’s Humanities and Social Science Research Planning Fund Project(23YJA860004,24YJA860023)Major Project of Basic Research in Philosophy and Social Sciences at Colleges and Universities in Henan Province(2024-JCZD-27)2024 Henan Province Philosophy and Social Science Planning Project.
文摘This paper investigates the rank reversal issue in the selection of new energy vehicle types,focusing on consumers aged 20 to 30.It employs both the AHP and the PCbHA methods to rank four types of the new energy vehicles-pure electric vehicles,plug-in hybrid electric vehicles,range-extended electric vehicles,and fuel cell vehicles,based on ten influential factors:purchase cost,maintenance cost,fuel and electricity cost,safety,passability,endurance,appearance,brand power,power,and space.To verify the effectiveness of the PCbHA method in addressing the rank reversal problem,one alternative option is removed,and the ranking is recalculated with subsequent analysis of the results.The study finds that rank reversals often stem from the closeness of alternative weights.Through sensitivity analysis,this research reveals the impact of endurance attribute weight on decision outcomes,indicating that when the endurance weight reaches 0.35,the ranking of pure electric vehicles and range-extended electric vehicles reverses.
