Determinants influencing students motorcycle travel among universitys and colleges : A hierarchical multiple regression analysis integrating MRBQ and T-LOC
Main Article Content
Abstract
Road accidents are influenced by multiple factors, including human behavior, vehicles, and environmental conditions.
Notably, human factors contribute to approximately 95% of all cases, with motorcycles being the most frequently
involved vehicle type. This study aimed to determine the factors influencing motorcycle travel behavior among students. The sample consisted of 650 student volunteers from universities and colleges in Kalasin Province, all of whom were capable of riding a motorcycle. Data were collected through a structured questionnaire incorporating the Motorcycle Rider Behavior Questionnaire (MRBQ), the Traffic Locus of Control Scale (T-LOC), and additional variables such as Mobile Phone use, Alcohol Consumption, use of Drowsiness-Inducing Medications, Motorcycle License Ownership, History of Traffic Violations, and Past Accident Involvement. Hierarchical Multiple Regression analysis was used to examine the relationships between these factors and Riding Behaviors. The results revealed that 75.7% of the students did not possess a motorcycle license, and all participants reported having violated traffic laws at least once. Further analysis showed that Mobile Phone use for Texting, Alcohol Consumption, and the Internal T-LOC factor (“Self”) significantly influenced the MRBQ. These included increases in “Traffic Errors”, “Speed Violations”, “Control Errors”, and “Stunts”, as well as a decrease in the use of “Safety Equipment”. These findings have significant implications for road safety policy and practice. Recommendations include stricter enforcement of motorcycle licensing requirements, banning mobile phone use while riding, promoting “don’t drink and ride” initiatives, and implementing expert-led road safety education programs. Educational institutions can integrate these findings into their strategic safety plans to
improve motorcycle safety among students.
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References
กรมควบคุมโรค, กระทรวงสาธารณะสุข. (2568). ข้อมูลผู้เสียชีวิตจากอุบัติเหตุทางถนน จากระบบบูรณาการข้อมูลการตายจากอุบัติเหตุทางถนน (3 ฐาน). Retrieved 15/02/2568 from https://data.go.th/th/dataset/rtddi
กลุ่มสถิติการขนส่ง. (2568). รายงานการวิเคราะห์ผู้เสียชีวิตจากอุบัติเหตุทางถนน และอัตราผู้เสียชีวิตฯ ปีงบประมาณ 2566. Retrieved 14/02/2568 from https://web.dlt.go.th/statistics/
วัยวุฑฒ์ อยู่ในศิล. (2556). การถดถอยแบบขั้นตอนระดับลดหลั่น. Journal of Research and Curriculum Development, 3(1), 28-38. https://so03.tci-thaijo.org/index.php/jrcd/article/view/93142
อนัญญา หาบุญมี, ชนัญญา จิระพรกุล, และ เนาวรัตน์ มณีนิล. (2024). ความชุกและปัจจัยที่มีความสัมพันธ์กับการเกิดอุบัติเหตุทางถนนจากรถจักรยานยนต์ ของนักศึกษาสถาบันอาชีวศึกษา จังหวัดหนองคาย. วารสารวิชาการสาธารณสุขชุมชน, 10(1). https://he02.tci-thaijo.org/index.php/ajcph/article/view/264640
Aceves-González, C., Cook, S., & May, A. (2015). Bus use in a developing world city: Implications for the health and well-being of older passengers. Journal of Transport & Health, 2(2), 308–316. https://doi.org/10.1016/j.jth.2015.04.001
Agusdinata, D. B., van der Pas, J. W. G. M., Walker, W. E., & Marchau, V. A. W. J. (2009). Multi-criteria analysis for evaluating the impacts of intelligent speed adaptation. Journal of Advanced Transportation, 43(4), 413–454. https://doi.org/10.1002/atr.5670430402
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Cerny, B. A., & Kaiser, H. F. (1977). A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivariate Behavioral Research, 12(1), 43–47. https://doi.org/10.1207/s15327906mbr1201_3
Dimitriou, L., Stylianou, K., & Yannis, G. (2018). Capturing the effects of texting on young drivers behaviour based on copula and Gaussian Mixture Models. Transportation Research Part F: Traffic Psychology and Behaviour, 58, 930–943. https://doi.org/10.1016/j.
trf.2018.07.022
Elliott, M. A., Baughan, C. J., & Sexton, B. F. (2007). Errors and violations in relation to motorcyclists’ crash risk. Accident Analysis & Prevention, 39(3), 491–499. https://doi.org/10.1016/j.aap.2006.08.012
Evans, L. (2012). Human behavior and traffic safety. Springer US.
Kline, R. B. (2011). Principles and practice of structural equation modeling. Guilford Press.
Loehlin, J. C. (1998). Latent variable models: An introduction to factor, path, and structural analysis (3rd ed.). Lawrence Erlbaum Associates Publishers.
Luu, L. V., Minh, C. C., & Long, N. X. (2021). The development of safe riding guidelines for young riders– A case study of Phu Yen, Vietnam. IATSS Research, 45(2), 226–233. https://doi.org/10.1016/j.iatssr.2020.11.001
Mardia, K. V., Kent, J. T., & Taylor, C. C. (2024). Multivariate analysis. John Wiley & Sons.
Maskey, R., Fei, J., & Nguyen, H.-O. (2018). Use of exploratory factor analysis in maritime research. The Asian Journal of Shipping and Logistics, 34(2), 91–111. https://doi.org/10.1016/j.ajsl.2018.06.006
Michalaki, P., Quddus, M., Pitfield, D., & Huetson, A. (2016). A time-series analysis of motorway collisions in England considering road infrastructure, sociodemographics, traffic and weather characteristics. Journal of Transport & Health, 3(1), 9–20. https://doi.
org/10.1016/j.jth.2015.10.005
Montag, I., & Comrey, A. L. (1987). Internality and externality as correlates of involvement in fatal driving accidents. Journal of Applied Psychology, 72(3), 339–343. https://doi.org/10.1037/0021-9010.72.3.339
Moskal, A., Martin, J.-L., & Laumon, B. (2012). Risk factors for injury accidents among moped and motorcycle riders. Accident Analysis & Prevention, 49, 5–11. https://doi.org/10.1016/j.aap.2010.08.021
Özkan, T., & Lajunen, T. (2005). Multidimensional Traffic Locus of Control Scale (T-LOC): Factor structure and relationship to risky driving. Personality and Individual Differences, 38(3), 533–545. https://doi.org/10.1016/j.paid.2004.05.007
Özkan, T., Lajunen, T., Doğruyol, B., Yıldırım, Z., & Çoymak, A. (2012). Motorcycle accidents, rider behaviour, and psychological models. Accident Analysis & Prevention, 49, 124–132. https://doi.org/10.1016/j.aap.2011.03.009
Reason, J., Manstead, A., Stradling, S., Baxter, J., & Campbell, K. (1990). Errors and violations on the roads: A real distinction? Ergonomics, 33(10-11), 1315–1332. https://doi.org/10.1080/00140139008925335
Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs: General and Applied, 80(1), 1–28. https://doi.org/10.1037/h0092976
Rudisill, T. M., Zhu, M., Kelley, G. A., Pilkerton, C., & Rudisill, B. R. (2016). Medication use and the risk of motor vehicle collisions among licensed drivers: A systematic review. Accident Analysis & Prevention, 96, 255–270. https://doi.org/10.1016/j.aap.2016.08.001
Sakashita, C., Senserrick, T., Lo, S., Boufous, S., Rome, L. d., & Ivers, R. (2014). The Motorcycle Rider Behavior Questionnaire: Psychometric properties and application amongst novice riders in Australia. Transportation Research Part F: Traffic Psychology
and Behaviour, 22, 126–139. https://doi.org/10.1016/j.trf.2013.10.005
Satiennam, T., Akapin, N., Satiennam, W., Kumphong, J., Kronprasert, N., & Ratanavaraha, V. (2023). Wrong way driving intention and behavior of young motorcycle riders. Transportation Research Interdisciplinary Perspectives, 19, Article 100827. https://doi.
org/10.1016/j.trip.2023.100827
Shinar, D. (2007). Traffic safety and human behavior. Emerald Group Publishing Limited.
Stephan, K., Kelly, M., McClure, R., Seubsman, S.-a.,Yiengprugsawan, V., Bain, C., & Sleigh, A. (2011). Distribution of transport injury and related risk behaviours in a large national cohort of Thai adults.
Accident Analysis & Prevention, 43(3), 1062–1067. https://doi.org/10.1016/j.aap.2010.12.011
Sumit, K., Brijs, K., Ross, V., Wets, G., & Ruiter, R. A. C. (2022). A focus group study to explore risky ridership among young motorcyclists in Manipal, India. Safety, 8(2), Article 40. https://doi.org/10.3390/safety8020040
Sumit, K., Ross, V., Brijs, K., Wets, G., & Ruiter, R. A. C. (2021). Risky motorcycle riding behaviour among young riders in Manipal, India. BMC Public Health, 21(1), Article 1954. https://doi.org/10.1186/s12889-021-11899-y
Sunmud, S., Arreeras, T., Phonsitthangkun, S., Prommakhot, S., & Sititvangkul, K. (2024). Examining risky riding behaviors: Insights from a questionnaire survey with middle-aged and older motorcyclists in Thailand. Safety, 10(2), Article 48. https://doi.org/10.3390/
safety10020048
Tainio, M. (2015). Burden of disease caused by local transport in Warsaw, Poland. Journal of Transport & Health, 2(3), 423–433. https://doi.org/10.1016/j.jth.2015.06.005
Transport Statistics Sub-Division. (2025). Number of vehicle registered in Thailand as of 31 January 2025. Department of Land Transport. https://web.dlt.go.th/statistics/
Trung Bui, H., Saadi, I., & Cools, M. (2020). Investigating on-road crash risk and traffic offences in Vietnam using the motorcycle rider behaviour questionnaire (MRBQ). Safety Science, 130, Article 104868. https://doi.org/10.1016/j.ssci.2020.104868
Uttra, S., Jomnonkwao, S., Watthanaklang, D., & Ratanavaraha, V. (2020a). Development of self-assessment indicators for motorcycle riders in Thailand: Application of the Motorcycle Rider Behavior Questionnaire (MRBQ). Sustainability, 12(7), Article 2785.
https://doi.org/10.3390/su12072785
Uttra, S., Laddawan, N., Ratanavaraha, V., & Jomnonkwao, S. (2020b). Explaining sex differences in motorcyclist riding behavior: An application of multi-group structural equation modeling. International Journal of Environmental Research and Public Health, 17(23),
Article 8797. https://doi.org/10.3390/ijerph17238797
Warner, H. W., Özkan, T., & Lajunen, T. (2010). Can the traffic locus of control (T-LOC) scale be successfully used to predict Swedish drivers’ speeding behaviour? Accident Analysis & Prevention, 42(4), 1113–1117. https://doi.org/10.1016/j.aap.2009.12.025
WHO. (2018). Global status report on road safety 2018. World Health Organization.
Yu, Z., Weina, Q., & Ge, Y. (2023). Utilizing MRBQ to investigate risky rider behavior in Chinese young riders: Combining the effect of Big Five personality and sensation seeking. Journal of Risk Research, 26(11), 1263–1282. https://doi.org/10.1080/13669877.2023.2270669