Development, psychometric evaluation, and application of an eco-driving questionnaire based on the Health Belief Model

Engineering notes

SEM showed that self-efficacy, knowledge, perceived benefits, and perceived susceptibility significantly predicted eco-driving behavior.

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

This study aimed to develop and psychometrically evaluate a culturally adapted eco-driving questionnaire grounded in the Health Belief Model (HBM) among line taxi drivers in Tehran, Iran. Given the contribution of vehicular emissions to urban air pollution and the lack of theory-based tools for assessing eco-driving determinants, a multi-phase questionnaire development process was conducted. An initial pool of 96 items was generated through literature review and expert consultation, followed by content validation, pilot testing, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability assessment, and structural equation modeling (SEM). Data were collected from 401 line taxi drivers selected through stratified random sampling. The final 57-item questionnaire covered eight domains: knowledge, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, self-efficacy, and eco-driving behavior. EFA supported an eight-factor structure explaining 77% of cumulative variance. CFA using WLSMV estimation showed acceptable fit (CFI = 0.936, TLI = 0.942, RMSEA = 0.068), although SRMR was elevated (0.128). Reliability was acceptable to excellent for most Likert-based subscales, while lower reliability was observed for dichotomous and mixed-format subscales. SEM showed that self-efficacy, knowledge, perceived benefits, and perceived susceptibility significantly predicted eco-driving behavior. The questionnaire may support research, intervention design, and policy planning to reduce transport-related air pollution.

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