Personas-based e-scooter usage patterns analysis at a Greek research campus

Abstract

Micro-mobility, particularly e-scooters, is characterized as a promising solution to urban transportation challenges by reducing congestion and pollution. However, integrating e-scooters into urban environments has been challenging due to safety concerns and friction with other transport modes, leading to public opposition and potential bans. These challenges underscore the benefits of deploying e-scooters in controlled environments like university campuses, where their impact can be better managed. This study examines e-scooter implementation on a Greek campus, focusing on identifying hidden factors influencing usage levels through exploratory factor analysis (EFA). In addition, cluster analyses reveal different personality types that significantly affect usage levels. The Real-life Experiment was conducted in two phases, compared behaviors over time, and accounted for weather variations. The study innovatively integrates questionnaire and usage data to identify hidden factors affecting usage and segment users into personas. The analysis created four perception-based personas (Reluctant, Cautious, Practical, Interested but Unconvinced) and four trip-based personas (Young and Infrequent, Young and Frequent, Older and Infrequent, Older and Frequent). Chi-square analysis and Sankey diagrams visualized personas’ patterns, while ridgeline plots showed variable distributions across the two phases. Results highlighted the significant impact of safety concerns, transport challenges, perceived e-scooter benefits, and weather on utilization levels. The insights from this study provide valuable guidance for effectively implementing e-scooter systems to enhance sustainability and reduce unnecessary car trips. Recognizing the challenges and opportunities associated with adopting e-scooter sharing systems allows research institutions to better plan and promote sustainable practices.