Analysis of strategies to enhance motorcycle courier safety through perceptions, attitudes, and driving behaviors in Bogor City, Indonesia

The rapid growth of e-commerce has increased the phenomenon of the gig economy where many workers are not employed full-time, but are paid based on the number of services they successfully provide. One of the main transportation modes for goods delivery is the motorcycle. Motorcycles play a very vital role because they are small and agile, allowing riders to navigate traffic congestion more efficiently. However, motorcycles are also the type of vehicle most prone to traffic accidents because they do not have a protective frame for the rider compared to other types of vehicles. Therefore, this study aims to determine the causal factors of traffic accidents and develop preventive strategies for motorcycle courier drivers based on perceptions, attitudes and driving behaviors. Questionnaires were distributed to motorcycle courier drivers in Bogor City. The Moderated Regression Analysis (MRA) method and a fishbone diagram were used to identify the internal and external factors contributing to traffic accidents. The results showed that more positive perceptions and driving attitudes were associated with safer driving behavior. Driving experience significantly moderated the relationship between perception and driving behavior but did not significantly moderate the relationship between driving attitude and driving behavior. Furthermore, fishbone analysis identified excessive cargo loads as the main external factor contributing to unsafe driving. Descriptive analysis also identified several unsafe practices, including smartphone use while riding, headset use, carrying loads between the handlebars and the motorcycle seat, and working for two courier companies simultaneously. Based on these findings, the recommendations focused on preventing excessive loads by using the RACI matrix to define stakeholder responsibilities for vehicle inspection, proper cargo placement, and safety monitoring before delivery operations.