Shared e-bikes interact with public transportation through connection and substitution, enhancing urban transportation services and user experience. However, the flexibility and speed advantages of shared e-bikes cause a significant substitution with public transit, thereby impacting public transit ridership and revenue. This study uses multinomial logit model to characterize connection and substitution behaviors between shared electric bikes and public transportation based on transactions data from Shenyang, China. Then, spatiotemporal analysis techniques and a generalized additive model are employed to explore characteristics and factors influencing connection and substitution interactions. Results show that connection and substitution behaviors respectively represent 12 % and 19 % of the total demand, with a concentration of substitution for commuting trips. Metro lines' layout and metro stations' proximity to the city center significantly affect connection demand, while business' density, bus stop density, trip locations, time savings, and travel distance significantly affect substitution demand. These findings can help city governments plan and maintain shared e-bike systems while avoiding negative impacts on public transit systems.

Spatiotemporal characteristics and influencing factors of connection and substitution relationships between shared E-bikes and public transit: A case study in Shenyang, China / Bai, Jiahao; Ye, Jianhong; Diana, Marco. - In: JOURNAL OF TRANSPORT GEOGRAPHY. - ISSN 0966-6923. - ELETTRONICO. - 129:(2025), pp. 1-15. [10.1016/j.jtrangeo.2025.104446]

Spatiotemporal characteristics and influencing factors of connection and substitution relationships between shared E-bikes and public transit: A case study in Shenyang, China

Diana, Marco
2025

Abstract

Shared e-bikes interact with public transportation through connection and substitution, enhancing urban transportation services and user experience. However, the flexibility and speed advantages of shared e-bikes cause a significant substitution with public transit, thereby impacting public transit ridership and revenue. This study uses multinomial logit model to characterize connection and substitution behaviors between shared electric bikes and public transportation based on transactions data from Shenyang, China. Then, spatiotemporal analysis techniques and a generalized additive model are employed to explore characteristics and factors influencing connection and substitution interactions. Results show that connection and substitution behaviors respectively represent 12 % and 19 % of the total demand, with a concentration of substitution for commuting trips. Metro lines' layout and metro stations' proximity to the city center significantly affect connection demand, while business' density, bus stop density, trip locations, time savings, and travel distance significantly affect substitution demand. These findings can help city governments plan and maintain shared e-bike systems while avoiding negative impacts on public transit systems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3006575