The influence of individual characteristics and working environment on driving performance of truck drivers

Road freight transportation is a cornerstone of China’s economy, enabling efficient commodity circulation and network consumption. However, the high rate of truck-related accidents and fatalities is largely influenced by individual characteristics and company management practices. This study investigates the impact of these factors on driving safety using social cognitive theory as the framework. A questionnaire was designed to gather empirical data on truck drivers’ individual traits, work environments, and driving behaviors. Exploratory factor analysis confirmed the reliability and validity of the questionnaire. The association rule algorithm was then used to uncover correlations among drivers’ risk behaviors, personal attributes, and work environments. A structural equation model (SEM) was constructed, integrating findings from the association rule analysis and social cognitive theory to explore causal relationships and influence paths. This approach effectively addressed challenges in constructing optimal path models with multivariable relationships. The SEM results revealed that insomnia, negative affect, burnout, and safety climate significantly influence driving behavior. Mediation analysis further showed that well-being, weekly working days, and salary levels indirectly affect driving behavior through burnout and negative affect. These findings highlight critical targets for individual and organizational interventions. Freight companies can implement targeted education and training programs addressing risk factors and enhance safety management. This research offers practical insights for improving truck drivers’ behavior and promoting road freight safety.