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Article: The mobility pattern of dockless bike sharing: A four-month study in Singapore
Title | The mobility pattern of dockless bike sharing: A four-month study in Singapore |
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Authors | |
Keywords | Built environment Dockless bike sharing Spatiotemporal analysis Poisson Regression |
Issue Date | 2021 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/trd |
Citation | Transportation Research Part D: Transport and Environment, 2021, v. 98, p. article no. 102961 How to Cite? |
Abstract | Many cities around the world have adopted dockless bike-sharing programs with the hope that this new service could enhance last-mile public transit connections. However, our understanding of the travel patterns using dockless bike sharing is still limited. To advance the knowledge on the new service, this study investigates mobility patterns of dockless bike sharing in Singapore using a four-month dataset. An exploratory spatiotemporal analysis is conducted to show daily travel patterns, while community detection of networks is used to explore the spatial clusters emerged from cycling behaviors. A series of Poisson regression models are then estimated to characterize the generation, attraction and resistance factors of bike trips in different periods of a day. The proposed regression model, which considers built environment factors of origin and destination simultaneously, is proved to be effective in deciphering mobility. The empirical findings shed light on policy implications in sustainable transportation planning. |
Description | Hybrid open access |
Persistent Identifier | http://hdl.handle.net/10722/304849 |
ISSN | 2023 Impact Factor: 7.3 2023 SCImago Journal Rankings: 2.328 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhang, X | - |
dc.contributor.author | Shen, Y | - |
dc.contributor.author | Zhao, J | - |
dc.date.accessioned | 2021-10-05T02:36:05Z | - |
dc.date.available | 2021-10-05T02:36:05Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Transportation Research Part D: Transport and Environment, 2021, v. 98, p. article no. 102961 | - |
dc.identifier.issn | 1361-9209 | - |
dc.identifier.uri | http://hdl.handle.net/10722/304849 | - |
dc.description | Hybrid open access | - |
dc.description.abstract | Many cities around the world have adopted dockless bike-sharing programs with the hope that this new service could enhance last-mile public transit connections. However, our understanding of the travel patterns using dockless bike sharing is still limited. To advance the knowledge on the new service, this study investigates mobility patterns of dockless bike sharing in Singapore using a four-month dataset. An exploratory spatiotemporal analysis is conducted to show daily travel patterns, while community detection of networks is used to explore the spatial clusters emerged from cycling behaviors. A series of Poisson regression models are then estimated to characterize the generation, attraction and resistance factors of bike trips in different periods of a day. The proposed regression model, which considers built environment factors of origin and destination simultaneously, is proved to be effective in deciphering mobility. The empirical findings shed light on policy implications in sustainable transportation planning. | - |
dc.language | eng | - |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/trd | - |
dc.relation.ispartof | Transportation Research Part D: Transport and Environment | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Built environment | - |
dc.subject | Dockless bike sharing | - |
dc.subject | Spatiotemporal analysis | - |
dc.subject | Poisson Regression | - |
dc.title | The mobility pattern of dockless bike sharing: A four-month study in Singapore | - |
dc.type | Article | - |
dc.identifier.email | Zhang, X: zhangxh@hku.hk | - |
dc.identifier.authority | Zhang, X=rp02816 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1016/j.trd.2021.102961 | - |
dc.identifier.scopus | eid_2-s2.0-85110004231 | - |
dc.identifier.hkuros | 326209 | - |
dc.identifier.volume | 98 | - |
dc.identifier.spage | article no. 102961 | - |
dc.identifier.epage | article no. 102961 | - |
dc.identifier.isi | WOS:000692248400014 | - |
dc.publisher.place | United Kingdom | - |