Dockless E-scooter usage patterns and urban built Environments: A comparison study of Austin, TX, and Minneapolis, MN

• Published in: Travel, behaviour & society behaviour & society, 2020-07, Vol.20, p.264-272
• Main Authors: Bai, Shunhua, Jiao, Junfeng
• Format: Article
• Language: English
• Subjects: Built Environment; Dockless E-scooter; GIS; Travel Patterns
• ISSN: 2214-367X
• DOI: 10.1016/j.tbs.2020.04.005

•This study analyzed over 886,000 dockless e-scooter trips in two US cities.•It found that downtown and university campus areas were both high e-scooter usage clusters although the temporal patterns varied between the two cities.•It also found that besides common positive indicators for sustainable transportation, commercial land use and open space such as parks and green space only positively correlated with e-scooter usage in one of the cities.•This study raised the importance of the local uniqueness as well as intercity commonalities among different societies in terms of new micro-mobility modes like dockless e-scooters. In recent years, the popularization of dockless shared electric scooters (e-scooters) across many American cities has provided a great opportunity to reduce short-distance automobile trips. However, there is not enough research that examines e-scooter usage patterns and their association with the urban environment. Moreover, the question of whether this association would vary across different cities also remains unanswered. To bridge these gaps, this study investigated e-scooter ridership in Austin and Minneapolis using GIS hotspot spatial analysis and negative binomial regression models. The spatial analysis results showed that the densest e-scooter usage happened in downtown areas and university campuses in both cities. However, the temporal characteristics of the two cities’ e-scooter usage patterns turned out to be different: in Austin, afternoons, and weekends experienced greater e-scooter traffic, whereas Minneapolis showed larger evening ridership and stable daily vehicle miles traveled throughout the week. Finally, regression results showed that proximity to the city center, better access to transit, and greater land-use diversity positively correlated with higher e-scooter ridership in both cities. Compared to single-family residential areas, office and institutional land use were more likely to relate to higher ridership in both cities. Curiously, the statistically positive relationship with commercial areas and parks only existed in Austin. This study contributes to transportation literature and practice by providing empirical evidence on e-scooter trips in the U.S. cities and by highlighting the importance of local uniqueness by comparing two cities.