View article

This study provides valuable insights into ride-hailing trip patterns among various income groups, including lower-income groups and those living below the poverty line, groups often overlooked in previous research. Using latent class cluster analysis (LCCA) based on a survey in Yogyakarta Province, Indonesia, we examine how variations in trip pattern characteristics are influenced by socio-demographics, household characteristics, and travel-related attitudes toward ride-hailing usage. Our results establish that six distinct clusters representing different ride-hailing travel patterns can be identified. We found dominant clusters for short and less expensive trips using motorcycle-based ride-hailing services (RH MC). In contrast, longer and more expensive trips are associated with car-based ride-hailing (RH CAR). Moreover, ride-hailing plays an important role in essential trips such as returning home, commuting, and …