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This study aims to explore the spatial and temporal dynamics of e-scooter usage and its association with the built and social environmental attributes in Minneapolis, Minnesota. Using a 4-month long trip data from 2019, this street-segment-level (N=13,367) study deployed negative binomial regression to build trip generation and destination models. The extent of the impact of built and social environment-related attributes varies at different temporal dimensions of e-scooting. Regarding spatial pattern, university areas and areas close to downtown generated substantially higher trips than other Minneapolis areas. In terms of temporal pattern, trips are more diffused at night and morning, and more concentrated in midday and evening. The high percentage of residential, commercial, and institutional land uses, a higher land use mix, high-valued parcels, and more food-related Points of Interest are strongly associated with e-scooter usage. E-scooter is heavily used in areas with more bike-dependent commuter, less car-dependent commuter, and young-aged people. Further, the presence of a sidewalk, bike-share station, bus stop, and transit shelter on a street segment positively affect scooter usage. These findings will assist e-scooter operators and city planners to formulate policies. Further, by strengthening the literature, this study can serve as a foundation for cities new in e-scooter mobility.
Tokey et al. (Sun,) studied this question.