Journal
JOURNAL OF TRANSPORT GEOGRAPHY
Volume 107, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jtrangeo.2023.103545
Keywords
Shared micro-mobility; Bikeshare; Built environment; Non-linear effects; Generalised additive mixed models; Multimodal transport
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Shared micro-mobility has been growing rapidly, and the coordinated development of different modes can improve urban public transport connectivity. This study compared the spatial and temporal patterns of station-based bikeshare systems (SBBS) and free-floating bikeshare systems (FFBS) with the metro. The results showed that SBBS were mainly used as feeder mode in downtown metro stations, while FFBS-metro integration was more dispersed at peripheral stations and covered wider time periods.
Shared micro-mobility has been booming in recent years and the coordinated development of different modes can play an important role in improving the connectivity of the urban public transport system. While most previous studies have analysed the feeder trips of individual modes, few comparative studies of different modes have been conducted. To this end, we compared the spatial and temporal patterns in the integrated use of station -based bikeshare systems (SBBS) and free-floating bikeshare systems (FFBS) with the metro. This study used the smart card data of SBBS and transaction data of FFBS from 1st to 30th September 2017, in Nanjing, China. Generalised additive mixed models were applied to examine the nuanced effects of the built environment, weather factors and temporal variables, while taking into account spatio-temporal autocorrelations. The results show that SBBS are used more as a feeder mode at downtown metro stations and exhibit pronounced rush hour patterns. FFBS-metro integrated use is spatially more dispersed at peripheral stations and covers wider periods of the day. This suggests that SBBS use is more demand-driven, while FFBS use is more efficiency-driven. The built environment shows different forms of effects: variables that have a linear relationship with SBBS-metro inte-grated use show non-linear effects in the FFBS model, and vice versa. Certain variables also present variations in their non-linear patterns. For instance, the plateau effect of road density for SBBS occurs at 10.5 km/km2, while the optimal employment density for FFBS is 12,000 jobs/km2. Inadequate or excessive development can lead to a decrease in integration efficiency. These findings can inform how service providers optimise fleet reallocation and how transport planners tailor spatial interventions that promote the integration of bikeshare and the metro system.
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