Going green on wheels: what drives electric vehicle use among self-driving tourists

Engineering notes

Attitude, subjective norms, and perceived behavioral control significantly enhance adoption intention.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Introduction Electric vehicles (EVs) play an increasingly important role in supporting the tourism industry’s low-carbon transition. However, the factors and psychological mechanisms underlying tourists’ adoption of EVs for self-driving tourism remain insufficiently understood. Grounded in the Theory of Planned Behavior (TPB), this study develops and validates an extended TPB model to examine how tourist-related factors, EV attributes, and destination conditions jointly influence tourists’ intention to use EVs for self-driving tourism. Methods A questionnaire survey was conducted among 545 residents from six representative Chinese cities. Partial least squares structural equation modeling (PLS-SEM) was employed to test the proposed relationships, and PLS multigroup analysis (PLS-MGA) was used to examine gender differences. Results The findings indicate that tourists’ intention to use EVs for self-driving tourism is shaped by both individual and contextual factors. Attitude, subjective norms, and perceived behavioral control significantly enhance adoption intention. Price value influences intention indirectly through attitude, whereas limited driving range, charger availability, and policy incentives exert their effects through a perceived behavioral control–range anxiety mechanism. Low-carbon awareness indirectly affects intention through attitude and subjective norms, while range anxiety serves as a key mediator linking perceived behavioral control to intention. Furthermore, gender differences emerge, with male tourists being more strongly influenced by attitude and female tourists being more strongly influenced by subjective norms. Discussion This study advances understanding of EV adoption in tourism by revealing the multilevel drivers and psychological mechanisms underlying tourists’ behavioral intentions. It extends the application of TPB to the context of EV-based self-driving tourism and offers practical implications for destination managers, policymakers, and EV developers seeking to promote sustainable mobility in tourism.

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