Risky Riding Violations Among Motorcycle Riders Through an Integrated Model of Behavioral, Psychological and Workload Factors

Risky violation behavior among motorcycle riders engaged in goods-delivery and service activities poses a significant challenge to road safety, particularly amid the growing demand for platform-based commercial motorcycle services. This research developed a unified structural model to investigate how Theory of Planned Behavior (TPB) constructs, risk perception, personal traits and workload are associated with risky riding violations across behavioral, perceptual, individual and occupational dimensions. A survey of 1400 commercial riders working in food-delivery and ride-hailing services was conducted, with 1251 samples analyzed after screening. Thereafter, the hypothesized associations among the constructs were evaluated through structural equation modeling (SEM). The results suggested that perceived social pressure and personality characteristics were positively associated with risky violation behavior, whereas attitudes and workload demonstrated negative associations with risky violation behavior. Furthermore, when the structural model was examined separately according to work experience, differences in the patterns and strengths of the relationships among the factors were observed. Overall, risky riding violations appear to arise from a combination of behavioral, individual and occupational conditions with the strength and direction of these associations differing across levels of work experience. Therefore, road safety interventions should consider the specific characteristics and experience levels of commercial riders rather than applying a uniform approach to all riders. Tailored strategies addressing the distinct behavioral and contextual factors of different rider groups may contribute to more effective risk reduction and road safety promotion.

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Publication Details

Journal
Behavioral Sciences
Published
2026-10-09
DOI
https://doi.org/10.3390/bs16101860
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
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article

Risky Riding Violations Among Motorcycle Riders Through an Integrated Model of Behavioral, Psychological and Workload Factors

Pawinee Iamtrakul, Sararad Chayphong
Behavioral Sciences
Traffic and Road Safety
article

Risky Riding Violations Among Motorcycle Riders Through an Integrated Model of Behavioral, Psychological and Workload Factors

Pawinee Iamtrakul, Sararad Chayphong
article en

Abstract

Risky violation behavior among motorcycle riders engaged in goods-delivery and service activities poses a significant challenge to road safety, particularly amid the growing demand for platform-based commercial motorcycle services. This research developed a unified structural model to investigate how Theory of Planned Behavior (TPB) constructs, risk perception, personal traits and workload are associated with risky riding violations across behavioral, perceptual, individual and occupational dimensions. A survey of 1400 commercial riders working in food-delivery and ride-hailing services was conducted, with 1251 samples analyzed after screening. Thereafter, the hypothesized associations among the constructs were evaluated through structural equation modeling (SEM). The results suggested that perceived social pressure and personality characteristics were positively associated with risky violation behavior, whereas attitudes and workload demonstrated negative associations with risky violation behavior. Furthermore, when the structural model was examined separately according to work experience, differences in the patterns and strengths of the relationships among the factors were observed. Overall, risky riding violations appear to arise from a combination of behavioral, individual and occupational conditions with the strength and direction of these associations differing across levels of work experience. Therefore, road safety interventions should consider the specific characteristics and experience levels of commercial riders rather than applying a uniform approach to all riders. Tailored strategies addressing the distinct behavioral and contextual factors of different rider groups may contribute to more effective risk reduction and road safety promotion.

Behavioral SciencesVol. 16(10)
Thammasat University (TH)
Openalex Percentile: Top 11%
Traffic and Road Safety
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