Key Levers for Modeling Traffic Violations: Lifestyle, Citizenship Belonging, Social Capital, and Individual Attitudes

Document Type : Research Paper


Department of Industrial Engineering, College of Engineering, Islamic Azad University, Tehran North Branch, Tehran, Iran


Identifying the most important human factors affecting driving violations and the occurrence of high-risk behaviours in driving will help to develop effective and deterrent programs. The aim and contribution of this study was to identify individual, social and environmental factors affecting the incidence of traffic violations by drivers and measure their effectiveness. Through the review of literature, these factors have been identified under variables including cultural capital, demographic variables, individual attitudes (social responsibility and rule of law), lifestyle, environmental factors and citizenship. Studying the effects of variables such as lifestyle, citizenship belonging, social capital distinguishes this paper from others. To measure the effect of variables, a questionnaire was used in which a number of appropriate observed variables were designed for each identified factor. The questionnaires were randomly distributed in the drivers' community of Tehran (248 samples) and after examining the validity and reliability of the research tool, descriptive and inferential statistical analyses including structural equation analysis (partial least squares method) were used to test the research hypotheses. The results of the analysis show that citizenship, attitude, environmental factors and cultural capital have the greatest impact on the rate of traffic violations. Also, the rate of traffic violations in different groups of drivers with different demographic characteristics is different. Planning to improve the attitude and culture of drivers by emphasizing the citizenship factor is one of the ways to reduce the number of violations. The results of this study can help policymakers to design training and tests for reducing traffic violations.


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