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

Chaoxi Liang, Qingtao Yang, Hongyuan Sun () and Xiaoming Ma
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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

Palgrave Communications, 2024, vol. 11, issue 1, 1-13

Abstract: 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.

Date: 2024
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DOI: 10.1057/s41599-024-04120-z

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