1
Member of the Traffic Operations Management Department, Faculty of Traffic Police Sciences and Technologies, Amin University of Law Enforcement Sciences, Tehran-Iran
2
professor, department of communication, university of applied science and technology: Tehran- Iran.
3
Assistant professor, department of Foreign Languages, Amin police university : Tehran- Iran.
Background: As urban traffic becomes increasingly dense, the use of motorcycles has increased in metropolitan areas. Given the multifaceted nature of traffic accidents, there is a pressing need for constructive interaction among the various institutions involved in managing motorcycle traffic safety. Methods: This applied research used mixed-methods approach, combining qualitative content analysis and quantitative descriptive-survey methods. In qualitative phase, the statistical population consisted of experts and managers from organizations related to motorcycle traffic safety. Participants were selected using non-probability purposive sampling until theoretical saturation was achieved. In the quantitative phase, the statistical population included 9,223 individuals selected via convenience sampling. The statistical population in the quantitative section consisted of Judicial Experts, Traffic Accident Experts from the Iran Highway and Traffic Police Department, Traffic Police Headquarters of Iranian National Police, the Ministry of Roads and Urban Development, and the Civil Affairs Department of the Ministry of Interior, who were selected based on their availability. Sampling in the qualitative section was conducted purposefully based on criteria, while in the quantitative section, it was done using stratified random sampling proportional to the size of each stratum in the total population, resulting in a sample size of 384 individuals according to the Morgan table. Findings: The multi-institutional prevention model includes the following dimensions: organizational structure (t = 26.894), inter-institutional communication (t = 25.251), multifaceted cultural development (t = 25.392), technical factors (t = 12.436), and comprehensive education (t = 10.281). All factor loadings were above 0.50 and statistically significant at the 95% confidence level.
ehsanpoor,S. , Ashab,H. and Javid,M. (2025). Preventing Motorcycle Accidents: A Multi-Institutional Model. (e236024). International Journal of Transportation Engineering, (), e236024 doi: 10.22119/ijte.2025.532957.1702
MLA
ehsanpoor,S. , , Ashab,H. , and Javid,M. . "Preventing Motorcycle Accidents: A Multi-Institutional Model" .e236024 , International Journal of Transportation Engineering, , , 2025, e236024. doi: 10.22119/ijte.2025.532957.1702
HARVARD
ehsanpoor S., Ashab H., Javid M. (2025). 'Preventing Motorcycle Accidents: A Multi-Institutional Model', International Journal of Transportation Engineering, (), e236024. doi: 10.22119/ijte.2025.532957.1702
CHICAGO
S. ehsanpoor, H. Ashab and M. Javid, "Preventing Motorcycle Accidents: A Multi-Institutional Model," International Journal of Transportation Engineering, (2025): e236024, doi: 10.22119/ijte.2025.532957.1702
VANCOUVER
ehsanpoor S., Ashab H., Javid M. Preventing Motorcycle Accidents: A Multi-Institutional Model. IJTE, 2025; (): e236024. doi: 10.22119/ijte.2025.532957.1702