New Energy Vehicle Decision-Making for Consumers: An IBULIQOWA Operator-Based DM Approach Considering Information Quality

Yi Yang, Xiangjun Wang, Jingyi Chen (), Jie Chen, Junfeng Yang and Chang Qi
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Yi Yang: School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China
Xiangjun Wang: School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China
Jingyi Chen: School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China
Jie Chen: School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China
Junfeng Yang: School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China
Chang Qi: School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China

Sustainability, 2025, vol. 17, issue 17, 1-28

Abstract: New energy vehicles (NEVs) have gained increasing favor among NEV consumers due to their dual advantages of “low cost” and “environmental friendliness.” In recent years, the share of NEVs in the global automotive market has been steadily rising. For instance, in the Chinese market, the sales of new energy vehicles in 2024 increased by 35.5% year-on-year, accounting for 70.5% of global NEV sales. However, as the diversity of NEV brands and models expands, selecting the most suitable model from a vast amount of information has become the primary challenge for NEV consumers. Although online service platforms offer extensive user reviews and rating data, the uncertainty, inconsistent quality, and sheer volume of this information pose significant challenges to decision-making for NEV consumers. Against this backdrop, leveraging the strengths of the quasi OWA (QOWA) operator in information aggregation and interval basic uncertain linguistic information (IBULI) information aggregation and two-dimensional information representation of “information + quality”, this study proposes a large-scale group data aggregation method for decision support based on the IBULIQOWA operator. This approach aims to assist consumers of new energy vehicles in making informed decisions from the perspective of information quality. Firstly, the quasi ordered weighted averaging (QOWA) operator on the unit interval is extended to the closed interval 0 , τ , and the extended basic uncertain information quasi ordered weighted averaging (EBUIQOWA) operator is defined. Secondly, in order to aggregate groups of IBULI, based on the EBUIQOWA operator, the basic uncertain linguistic information QOWA (BULIQOWA) operator and the IBULIQOWA operator are proposed, and the monotonicity and degeneracy of the proposed operators are discussed. Finally, for the problem of product decision making in online service platforms, considering the credibility of information, a product decision-making method based on the IBULIQOWA operator is proposed, and its effectiveness and applicability are verified through a case study of NEV product decision making in a car online service platform, providing a reference for decision support in product ranking of online service platforms.

Keywords: NEV consumer; decision making; new energy vehicle; information quality; interval basic uncertain linguistic information; quasi ordered weighted averaging operator (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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