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作者:

Wang, Yuan-Yuan (Wang, Yuan-Yuan.) | Chi, Yuan-Ying (Chi, Yuan-Ying.) (学者:迟远英) | Xu, Jin-Hua (Xu, Jin-Hua.) | Li, Jia-Lin (Li, Jia-Lin.)

收录:

SCIE

摘要:

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.

关键词:

charging infrastructure consumer preferences natural language processing public comment assessment regional differences

作者机构:

  • [ 1 ] [Wang, Yuan-Yuan]Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China
  • [ 2 ] [Chi, Yuan-Ying]Beijing Univ Technol, Sch Econ & Management, Beijing 100124, Peoples R China
  • [ 3 ] [Wang, Yuan-Yuan]Chinese Acad Sci, Ctr Energy & Environm Policy Res, Inst Sci & Dev, Beijing 100190, Peoples R China
  • [ 4 ] [Xu, Jin-Hua]Chinese Acad Sci, Ctr Energy & Environm Policy Res, Inst Sci & Dev, Beijing 100190, Peoples R China
  • [ 5 ] [Li, Jia-Lin]China Datang Grp New Energy Sci & Technol Res Ins, Beijing 100124, Peoples R China

通讯作者信息:

  • [Xu, Jin-Hua]Chinese Acad Sci, Ctr Energy & Environm Policy Res, Inst Sci & Dev, Beijing 100190, Peoples R China;;[Li, Jia-Lin]China Datang Grp New Energy Sci & Technol Res Ins, Beijing 100124, Peoples R China

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来源 :

ENERGIES

年份: 2021

期: 15

卷: 14

3 . 2 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:9

被引次数:

WoS核心集被引频次: 4

SCOPUS被引频次: 7

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 2

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