Abstract
China’s new energy vehicle industry has gradually shifted from relying on policy support in the past to a state where enterprise survival is determined by the market, which has driven the industry to accelerate its move toward market orientation. This study aims to help potential consumers quickly locate and obtain valuable, high-quality reviews, while also assisting new energy vehicle companies in improving product quality and service levels to promote the healthy development of the industry. To achieve these goals, review data were first collected from online forums, and a corresponding corpus was subsequently constructed. Next, an evaluation system for review quality was established, with values assigned to review quality accordingly. Finally, a model of the influencing factors of review quality was developed; through multiple regression analysis, specific influencing factors were identified, facilitating an exploration of the impact exerted by relevant factors on review quality. The results indicate that the statistical features and semantic features of online reviews can serve as evaluation indicators for constructing a quality evaluation system. In the influencing factor model, the time interval, number of purposes, and reviewers’ expertise exert a positive impact on review quality; driving mileage has a negative impact on review quality; while the positive impact of certified users on review quality is not significant. The study results provide a simple criterion for consumers’ perception of review values and verify the influence of review quality on consumers’ purchase intention. Additionally, they can help automotive companies identify factors affecting the quality of online reviews and enhance the effectiveness of new energy vehicle companies in utilizing online reviews for marketing purposes.
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Supplementary information. The online version contains supplementary material available at https://doi.org/10.6084/m9.figshare.29166875.
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Acknowledgements
This study is funded by Lianyungang “521” Project [Grant No. 2023].
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Conceptualization: Xiaoguang Wang, Yijun Gao; Data curation: Lei Fan, Nan Li; Formal analysis: Xiaoguang Wang, Nan Li; Methodology: Yijun Gao, Nan Li; Software: Xiaoguang Wang, Lei Fan; Visualization: Yijun Gao, Lei Fan, Nan Li; Writing – original draft: Xiaoguang Wang, Nan Li; Writing – review & editing: Xiaoguang Wang, Yijun Gao, Nan Li.
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Wang, X., Gao, Y., Fan, L. et al. The factors that influence online review quality: the example of new energy vehicle reviews. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-06884-y
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DOI: https://doi.org/10.1057/s41599-026-06884-y
