LAPSE:2023.25549
Published Article
LAPSE:2023.25549
Consumer Preferences for Electric Vehicle Charging Infrastructure Based on the Text Mining Method
Yuan-Yuan Wang, Yuan-Ying Chi, Jin-Hua Xu, Jia-Lin Li
March 28, 2023
The construction of charging infrastructure has a positive effect on promoting the diffusion of new energy vehicles (NEVs). This study uses natural language processing (NLP) technology to explore consumer preferences for charging infrastructure from consumer comments posted on public social media. The findings show that consumers in first-tier cities pay more attention to charging infrastructure, and the number of comments accounted for 36% of the total. In all comments, consumers are most concerned about charging issues, national policy support, driving range, and installation of private charging piles. Among the charging modes of charging piles, direct current (DC) fast charging is more popular with consumers. The inability to find public charging piles in time to replenish power during travel or high energy consumption caused by air conditioning is the main reason for consumers’ range anxiety. Increasing battery performance, improving charging convenience, and construction of battery swap station are the main ways consumers prefer to increase driving range. Consumers’ preference for charging at home is the main reason for their high attention to the installation of private charging piles. However, the lack of fixed parking spaces and community properties have become the main obstacles to the installation of private charging piles. In addition, consumers in cities with different development levels pay different amounts of attention to each topic of charging infrastructure. Consumers in second-tier and above cities are most concerned about charging issues. Consumers in third-tier and above cities pay significantly more attention to the installation of private charging piles than consumers in fourth-tier and fifth-tier cities. Consumers in each city have almost the same amount of attention to driving range.
Keywords
charging infrastructure, consumer preferences, natural language processing, public comment assessment, regional differences
Subject
Suggested Citation
Wang YY, Chi YY, Xu JH, Li JL. Consumer Preferences for Electric Vehicle Charging Infrastructure Based on the Text Mining Method. (2023). LAPSE:2023.25549
Author Affiliations
Wang YY: School of Economics and Management, Beijing University of Technology, Beijing 100124, China; Center for Energy and Environmental Policy Research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Chi YY: School of Economics and Management, Beijing University of Technology, Beijing 100124, China
Xu JH: Center for Energy and Environmental Policy Research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Li JL: China Datang Group New Energy Science and Technology Research Institute, Beijing 100124, China
Journal Name
Energies
Volume
14
Issue
15
First Page
4598
Year
2021
Publication Date
2021-07-29
Published Version
ISSN
1996-1073
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Original Submission
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PII: en14154598, Publication Type: Journal Article
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LAPSE:2023.25549
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doi:10.3390/en14154598
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Mar 28, 2023
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