Citation

Ji S, Heinen E, Wang Y. Transp. Res. D Trans. Environ. 2023; 116: e103630.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.trd.2023.103630

PMID

unavailable

Abstract

Few studies have examined the influence of street configurations, and the built environment may have a more complex effect on bike-share usage than the linear associations typically modeled. Given the spatio-temporal correlation and nested data effect in the data from Xi'an, we applied generalized additive mixed modeling (GAMM) to address the effects of street configurations and land use on the number of bike-share trips and the number of trips stratified by districts. Street configuration is measured by average geodesic distance, network betweenness, and intersection density. The models suggest that a higher average geodesic distance was linked to the reduced number of arriving and departing bike-share trips (although it needs noting that land-use mix was excluded given the correlation with average geodesic distance). Moreover, land use density showed an inverted u-shape association with departures and arrivals.

Language: en

Keywords

Bike-sharing; Road network configuration; Spatial and temporal analysis