Unveiling Crucial Factors Shaping Ridesharing Usage Intention: Insights from Serbia

Abstract

The aim of our paper is to reveal crucial factors related to the intention towards adoption of ridesharing service. To determine the importance of the factors we employ machine learning technique. Employing a survey methodology and a total of 325 questions, we gathered data from students at the University of Belgrade – Faculty of Organizational Sciences. We then analysed responses using a Random Forest Classifier to predict ridesharing service usage intention. Our findings reveal that social influences, including word-of-mouth and perceived enjoyment, are paramount in shaping intentions to use ridesharing services. Negative perceptions about the complexity and safety of ridesharing also emerged as influential. Since our research was focused on first-time users of ridesharing concept the findings can be of great importance for the emerging sharing mobility providers. Outlined top preferences can dictate market operators’ penetration strategies that should be adjusted based on the potential consumers’ perceptions and motives.