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Unveiling consumer satisfaction and its driving factors of EVs in China using an explainable artificial intelligence approach

Author

Listed:
  • Chaoxi Liang

    (Peking University Shenzhen Graduate School)

  • Qingtao Yang

    (Peking University Shenzhen Graduate School)

  • Hongyuan Sun

    (Peking University Shenzhen Graduate School)

  • Xiaoming Ma

    (Peking University Shenzhen Graduate School)

Abstract

As China’s electric vehicle (EV) industry shifts from policy-driven to market-oriented development, understanding post-purchase satisfaction and its driving factors becomes imperative. This study compiled objective product attributes and consumer online reviews for 1321 EV models from China’s largest automotive website, Autohome, covering the period between 2014 and 2022. By employing data mining and sentiment analysis (SA) techniques, this research extracted consumers’ overall satisfaction with EVs and identified the subjective product attributes that garnered the most attention in consumer online comments. Utilizing a machine learning (ML)—SHapley Additive exPlanations (SHAP) framework, the research pinpointed the most impactful objective and subjective product attributes on consumer satisfaction and ranked their impact intensity both statically and dynamically. The findings reveal that Chinese consumers are generally satisfied or very satisfied with their EVs. From a static perspective, distinctive objective product attributes of EVs, such as total motor power and range, play a crucial role in influencing consumer satisfaction. In terms of subjective product attributes, aspects like space, design, handling, and comfort are the most captivating to consumers and significantly shape their satisfaction. However, the dynamic analysis indicates that range anxiety persists, despite gradually increasing consumer satisfaction as the EV market matures. Additionally, price remains a crucial factor, particularly following the widespread implementation of subsidy withdrawal policies, making it the most sensitive factor for EV consumers. This study represents the first application of an explainable artificial intelligence framework to quantify the marginal impacts of various automotive product attributes on consumer satisfaction.

Suggested Citation

  • Chaoxi Liang & Qingtao Yang & Hongyuan Sun & Xiaoming Ma, 2024. "Unveiling consumer satisfaction and its driving factors of EVs in China using an explainable artificial intelligence approach," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-04120-z
    DOI: 10.1057/s41599-024-04120-z
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    1. Tao Shu & Zhiyi Wang & Ling Lin & Huading Jia & Jixian Zhou, 2022. "Customer Perceived Risk Measurement with NLP Method in Electric Vehicles Consumption Market: Empirical Study from China," Energies, MDPI, vol. 15(5), pages 1-23, February.
    2. Li, Jingjing & Jiao, Jianling & Tang, Yunshu, 2019. "An evolutionary analysis on the effect of government policies on electric vehicle diffusion in complex network," Energy Policy, Elsevier, vol. 129(C), pages 1-12.
    3. Wang, Ning & Tang, Linhao & Zhang, Wenjian & Guo, Jiahui, 2019. "How to face the challenges caused by the abolishment of subsidies for electric vehicles in China?," Energy, Elsevier, vol. 166(C), pages 359-372.
    4. Ma, Shao-Chao & Fan, Ying & Feng, Lianyong, 2017. "An evaluation of government incentives for new energy vehicles in China focusing on vehicle purchasing restrictions," Energy Policy, Elsevier, vol. 110(C), pages 609-618.
    5. Sun, Lishan & Huang, Yuchen & Liu, Shuli & Chen, Yanyan & Yao, Liya & Kashyap, Anil, 2017. "A completive survey study on the feasibility and adaptation of EVs in Beijing, China," Applied Energy, Elsevier, vol. 187(C), pages 128-139.
    6. Li, Wenbo & Long, Ruyin & Chen, Hong, 2016. "Consumers’ evaluation of national new energy vehicle policy in China: An analysis based on a four paradigm model," Energy Policy, Elsevier, vol. 99(C), pages 33-41.
    7. Lin, Boqiang & Yang, Mengqi, 2024. "Changes in consumer satisfaction with electric vehicle charging infrastructure: Evidence from two cross-sectional surveys in 2019 and 2023," Energy Policy, Elsevier, vol. 185(C).
    8. Wang, Lei & Fu, Zhong-Lin & Guo, Wei & Liang, Ruo-Yu & Shao, Hong-Yu, 2020. "What influences sales market of new energy vehicles in China? Empirical study based on survey of consumers’ purchase reasons," Energy Policy, Elsevier, vol. 142(C).
    9. Abdullah Dik & Siddig Omer & Rabah Boukhanouf, 2022. "Electric Vehicles: V2G for Rapid, Safe, and Green EV Penetration," Energies, MDPI, vol. 15(3), pages 1-26, January.
    10. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    11. Ma, Shao-Chao & Xu, Jin-Hua & Fan, Ying, 2019. "Willingness to pay and preferences for alternative incentives to EV purchase subsidies: An empirical study in China," Energy Economics, Elsevier, vol. 81(C), pages 197-215.
    12. Liu, Jin-peng & Zhang, Teng-xi & Zhu, Jiang & Ma, Tian-nan, 2018. "Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration," Energy, Elsevier, vol. 164(C), pages 560-574.
    13. Wenbo Li & Ruyin Long & Hong Chen & Feiyu Chen & Xiao Zheng & Muyi Yang, 2019. "Effect of Policy Incentives on the Uptake of Electric Vehicles in China," Sustainability, MDPI, vol. 11(12), pages 1-20, June.
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