Exploring the Spatially Heterogeneous Effects of the Built Environment on Bike-Sharing Usage during the COVID-19 Pandemic

Bike-sharing holds promise for available and healthy mobility services during COVID-19 where bike sharing users can make trips with lower health concerns due to social distancing compared the restricted transportation modes such as public transit ridesharing services. Leveraging trip data of Divvy bike-sharing system in Chicago, this study exploresspatially heterogeneous effects built environment on usage under pandemic. Results show that average weekly ridership declined by 52.04%. To account spatially relationship between ridership, geographically weighted regression (GWR) model semiparametric GWR (S-GWR) are constructed. We find S-GWR outperforms multiple linear models. The results indicate education employment density, distance subway, cases, before global variables. factros (i.e., household office ridership) vary across space. could provide a useful reference planners operators determine high demand area pandemic,thus adjusting station locations, capacity, rebalancing schemes accordingly.