Identifying latent mobility as a service preference segments among college students

Abstract The penetration of shared mobility services is spreading worldwide, leading to the restructuring of the existing transportation system. Mobility as a Service (MaaS) is presumed to answer the challenge of utilizing several transport modes including emerging services, where travel planning, booking options, payment methods, and ticketing solutions are integrated into one single application. MaaS promises several benefits, but studies on motivational mechanism behind the technology adoption are still lacking and usually rely on structural equation modelling approach. In this study, we apply latent class cluster analysis using attitudinal variables as indicators to examine the motivational factors in adopting MaaS, revealing the heterogeneity in preferences among college students. Based on the results, five clusters are identified, namely MaaS neutral, MaaS enthusiast, MaaS opponent, MaaS avoider, MaaS lover. College students with high environmental consciousness and seeking variety are more enthusiastic about MaaS, while others coming from higher-income households are likely to adopt MaaS. The negative precautions regarding MaaS should be decreased by respecting data privacy and providing easy-to-use MaaS applications, while the perceived safety risks should be eliminated by providing emergency features. Finally, some policy recommendations are drawn based on the identified clusters of university students.