The Development of Motorcycle Accident Models Based on Riders’ Characters - Margareth Evelyn Bolla; Ludfi Djakfar; Achmad Wicaksono; Cleoputri Al Yusainy (Civil Engineering Journal, 2023)
Human errors have commonly been perceived as the dominant cause of accidents. Different individuals may behave differently towards certain situations, leading to accidents. This study aims to model the relationship between the riders’ personalities, riding performance, and the probability of being involved in an accident. Adding mindfulness as a mediating variable and demographic factors as moderating variables are also essential points to developing the model. The Big Five Inventory (BFI) and Mindful Attention Awareness Scale (MAAS) were used to measure the respondents' traits, while the Honda Riding Trainer (HRT) was used as a simulation tool. The Structural Equation Modelling (SEM) analysis shows that only the neuroticism variable significantly predicts mindfulness and riding performance. The openness and conscientiousness variables only significantly predicted mindfulness, while agreeableness is the only Big Five personality that significantly predicted riding performance. The results also show that although the mindfulness (M) variable in this study has not been able to become a mediating variable, it is strong enough as an exogenous variable for riding performance. The logistic regression analysis found that the worse the rider's performance, the greater the chance of an accident. Female riders are more than twice as likely to have an accident as male riders. These results indicate the need to research road safety that is differentiated by sex and its characteristics based on it. Doi: 10.28991/CEJ-SP2023-09-018 Full Text: PDF