Preliminary Modelling of Accident and Near Miss Risk Factors Among Gig Delivery Workers in Malaysia

Abstract

This study explores the risk factors of accidents and near misses among gig delivery motorcyclists in Klang Valley, Malaysia. Using a customized questionnaire, this cross-sectional study collected 235 responses through closed Facebook groups. Sociotechnical aspects such as Rider Behaviour (RB), Rider Safety Awareness (RA), Work Conditions (WC), Environmental Factors (EF), Motorcycle Design and Safety (MDS), and Platform Safety Management (PSM) have been evaluated using an initial 74-item questionnaire. The Partial Least Squares Structural Equation Modelling (PLS-SEM) was utilized resulting a final model with 56 items. The study outcomes have good validity and reliability with Cronbach’s alpha between 0.67 and 0.95, Average Variance Extracted (AVE) > 0.50, and Composite Reliability (CR) > 0.80. Path analysis identified WC (β = -0.337, p < 0.001) and ORU (β = 0.198, p = 0.003) as critical predictors for accident. MDS (β = 0.177, p = 0.026), EF (β = 0.175, p = 0.009), and PSM (β = -0.207, p = 0.001) were significant predictors of near misses. By combining Sociotechnical System Theory and Multiple Causation Theory, the findings showed the complex relationship of various factors in gig delivery workers’ safety. Immediate reforms in platform policies, better road infrastructure, improved motorcycle safety design, and enhancing road users’ safety awareness are much needed. This research contributes to the limited literature on gig worker safety in Malaysia and provides a foundation for future studies and policy recommendations.