Publication: Analysis on self-reported risky riding behaviour of motorcyclist using partial least square structural equation modelling
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Date
2021-10-01
Authors
Goh, Wins Cott
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Abstract
This study was conducted among Malaysian motorcyclists to address the high fatality rate of motorcycle traffic accidents. Research has shown that age, gender, likeness towards a risky riding behaviour (positive affect), and perception of risky riding behaviour significantly impact a rider’s judgement on the road. Thus, this study is initiated to better comprehend the behaviour of Malaysian motorcyclists. A study was conducted to obtain demographic information, risky behaviour engagement, positive affect, and risk perception among Malaysian motorcycle riders. The survey results were then analysed using the Structural Equation Modelling – Partial Least Squares approach to assess the survey's reliability and validity. Consequently, a statistical model was created based on the hypothesis model, where the relationship among each latent construct is evaluated. The statistical model in this study included age, gender, riding experience, trip distance, motorcycle type as the construct of personal characteristic. A total of four hypotheses are accepted from the initial six
hypotheses. Crucial evaluation from the model reveals that the positive affect construct has the strongest positive relationship with the construct of risky behaviour (t-value = 15.517). Findings in the model also show that the personal characteristics of rider has a direct effect on risky behaviour (t-value = 2.175). In addition to these findings, the
model has also revealed an indirect effect from personal characteristics towards risky behaviour through positive affect was also significant (t-value = 3.885). These results
concur with most studies conducted on motorist driving behaviour. Thus, with these findings, it can be concluded that risky behaviour engagement of Malaysian motorcyclist reduction should be approached from the perspective of encouragement and empowerment instead of enforcement and deterrence.