Research on New Energy Vehicle Type Selection Method Based on Inversion
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Kai LAI1(), Songyuan DIAO1,*(), Yada HU1(), Quanyi LIU2(), Chunsheng CUI1()
Author information+
1 School of Data Science and E-commerce, Henan University of Economics and Law, Zhengzhou 450046, China
2 Sichuan University-Pittsburgh Institute, Chengdu 610065, China
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History+
Received
Accepted
Published
2024-08-17
2024-11-12
2025-04-28
Issue Date
2025-04-29
Abstract
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.
Kai LAI, Songyuan DIAO, Yada HU, Quanyi LIU, Chunsheng CUI.
Research on New Energy Vehicle Type Selection Method Based on Inversion. Journal of Systems Science and Information, 2025, 13(2): 313-324 https://doi.org/10.12012/JSSI-2024-0118