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author:

He, S. (He, S..) [1] | Wang, Y. (Wang, Y..) [2]

Indexed by:

Scopus

Abstract:

New energy vehicles (NEVs) have beneficial effects on the energy conservation and environmental protection in the transportation sector. The governments have issued many policies to promote their development and adoption. But, how to evaluate the NEVs is still a noteworthy topic. In this paper, we focus on the evaluation of NEVs through online reviews. First, the online reviews are obtained from the websites by data crawling technology. After obtaining the data, a data-driven based method is developed to extract the attributes about the NEVs and sentiment analysis is conducted to discriminate the sentiment orientation of each review to each alternative under each attribute. Then, we define a new information transformation mechanism to realize the transformation from unstructured data to picture fuzzy numbers. Next, a weight determination method based on the proposed picture fuzzy entropy measure is defined to determine the weight of attributes. Finally, considering the bounded rationality of consumers in purchasing, a picture fuzzy set-based regret theory is proposed to quantify their psychological behavior. A case study about the evaluation of NEVs are presented to show the implementation process of this research. Discussions consisting of comparative analysis and parameter analysis are also conducted to explore the superiority and robustness of the proposed evaluation method. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.

Keyword:

Evaluation analysis New energy vehicles Online reviews Regret theory Sentiment analysis Weight determination

Community:

  • [ 1 ] [He, S.]Decision Sciences Institute, Fuzhou University, Fujian, 350108, China
  • [ 2 ] [Wang, Y.]Decision Sciences Institute, Fuzhou University, Fujian, 350108, China
  • [ 3 ] [Wang, Y.]Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fujian, 350108, China

Reprint 's Address:

  • [Wang, Y.]Decision Sciences Institute, China

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Source :

Artificial Intelligence Review

ISSN: 0269-2821

Year: 2023

Issue: 3

Volume: 56

Page: 2171-2192

1 0 . 7

JCR@2023

1 0 . 7 0 0

JCR@2023

ESI HC Threshold:32

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 31

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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