Influence of Built Environment on Bike Sharing Usage under COVID-19

Abstract

Bike sharing, as an important component of urban public transportation, has played a more important role during the COVID-19 pandemic because users could ride bikes in open space and avoid the risk of infection. Leveraging the trip data of the Divvy bike sharing system in Chicago, this study sets to explore the change of ridership that COVID-19 has brought and the built environment factors that influence the spatial variation of ridership under the pandemic. Results show that the ridership declines by xx% in total. To account for the spatially heterogeneous relationship between the built environment and the ridership, the geographically weighted regression (GWR) model and the semi-parametric GWR (S-GWR) model are constructed. By comparing the model results, we find that the S-GWR model outperforms the GWR and the multiple linear regression model. The results of the S-GWR model indicates that education employment density, distance to subway, COVID-19 cases and ridership before COVID-19 are global variables. The ridership between residential density, office employment density and the ridership vary across space. The results of this study could provide useful reference to transportation planners and bike sharing operators to determine the high bike sharing demand area under the pandemic and to make adjustment on the locations and capacity of the stations and the rebalancing schemes accordingly. Keywords: COVID-19, Public bike, Built environment, Spatial change, Geographically weighted regression