Understanding micromobility equity with open big data

We develop an analytical framework to examine how dockless e-scooter and station-based bikesharing differ regarding a set of equity-related outcomes (i.e., availability, accessibility, usage, and idle time) across neighborhoods in different socioeconomic categories. An analysis of idle time is made possible by the availability of the GBFS data, a new source of open big data. The analysis of idle time can shed light on if improving spatial access to shared micromobility vechicles in low-income communities can effectively promote micromobility use in these areas.

Key words: E-scooter, bikeshare, micromobility equity

Su, L., Yan, X., Zhao, X. Micromobility equity: A comparison of shared e-scooters and station-based bikeshare in Washington DC. [Download Preprint].