Seefong Manlika, Wisutwattanasak Panuwat, Se Chamroeun, Theerathitichaipa Kestsirin, Jomnonkwao Sajjakaj, Champahom Thanapong, Ratanavaraha Vatanavongs, Kasemsri Rattanaporn
School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.
Institute of Research and Development, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.
Sci Rep. 2024 Dec 2;14(1):29889. doi: 10.1038/s41598-024-81793-1.
Despite the considerable efforts to address traffic crashes, overspeeding in industrial zones remains a primary cause in Thailand. In order to effectively against this challenge (overspeeding), the deep-rooted factors influencing speeding behaviors, particularly drivers' risky behaviors, must be understood. Thus, this study employs the theory of planned behavior (TPB) and the framework comprising three basic Es (Education, Engineering, and Enforcement) and additional Es (Emergency response), i.e., the 3Es + Es framework, to examine these deep-rooted factors while considering the riders' sociodemographic data. Additionally, we performed structural equation modeling to investigate the factors influencing speeding behaviors, with key findings revealing that Engineering factors significantly account for overspeeding. Conversely, we revealed that attitude, subjective norm, and perceived behavioral control (which are essential TPB components) significantly influence riders' intentions to exhibit safe behavior, resulting in reduced speeding. Additionally, our examination of latent factors based on riders' sociodemographic data revealed that age, marital status, income, riding experience, crash history, and traffic tickets are significant factors that determine speeding habits. Specifically, we observed that single riders and those with less than five years of riding experience were less likely to exhibit safe riding behaviors. Overall, our findings would benefit Thailand's road-safety authorities, as we specifically proposed appropriate policies and empirical guidelines for Thailand's industrial zones, which are prone to high crash rates. This could effectively reduce speeding among motorcycle riders and mitigate traffic crashes.
尽管在应对交通事故方面付出了巨大努力,但在泰国,工业区的超速行驶仍然是主要原因。为了有效应对这一挑战(超速行驶),必须了解影响超速行为的深层次因素,特别是驾驶员的危险行为。因此,本研究采用计划行为理论(TPB)以及由三个基本要素(教育、工程和执法)和额外要素(应急响应)组成的框架,即3Es + Es框架,在考虑骑手社会人口统计学数据的同时,研究这些深层次因素。此外,我们进行了结构方程建模,以调查影响超速行为的因素,主要研究结果表明工程因素是超速的重要原因。相反,我们发现态度、主观规范和感知行为控制(计划行为理论的重要组成部分)显著影响骑手表现出安全行为的意图,从而减少超速。此外,我们根据骑手的社会人口统计学数据对潜在因素进行的研究表明,年龄、婚姻状况、收入、骑行经验、事故历史和交通罚单是决定超速习惯的重要因素。具体而言,我们观察到单身骑手和骑行经验少于五年的骑手表现出安全骑行行为的可能性较小。总体而言,我们的研究结果将使泰国道路安全当局受益,因为我们特别为泰国事故率较高的工业区提出了适当的政策和实证指南。这可以有效减少摩托车骑手的超速行为,减轻交通事故。