Understanding the usage of dockless bike sharing in Singapore
A new generation of bike-sharing services without docking stations is currently revolutionizing the traditional bike-sharing market as it dramatically expands around the world. This study aims at understanding the usage of new dockless bike-sharing services through the lens of Singapore's preva...
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| Format: | Article |
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Taylor & Francis
2019
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| Online Access: | http://hdl.handle.net/1721.1/120460 https://orcid.org/0000-0002-1929-7583 |
| _version_ | 1826202513411407872 |
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| author | Shen, Yu Zhang, Xiaohu Zhao, Jinhua |
| author2 | Massachusetts Institute of Technology. Department of Urban Studies and Planning |
| author_facet | Massachusetts Institute of Technology. Department of Urban Studies and Planning Shen, Yu Zhang, Xiaohu Zhao, Jinhua |
| author_sort | Shen, Yu |
| collection | MIT |
| description | A new generation of bike-sharing services without docking stations is currently revolutionizing the traditional bike-sharing market as it dramatically expands around the world. This study aims at understanding the usage of new dockless bike-sharing services through the lens of Singapore's prevalent service. We collected the GPS data of all dockless bikes from one of the largest bike sharing operators in Singapore for nine consecutive days, for a total of over 14 million records. We adopted spatial autoregressive models to analyze the spatiotemporal patterns of bike usage during the study period. The models explored the impact of bike fleet size, surrounding built environment, access to public transportation, bicycle infrastructure, and weather conditions on the usage of dockless bikes. Larger bike fleet is associated with higher usage but with diminishing marginal impact. In addition, high land use mixtures, easy access to public transportation, more supportive cycling facilities, and free-ride promotions positively impact the usage of dockless bikes. The negative influence of rainfall and high temperatures on bike utilization is also exhibited. The study also offered some guidance to urban planners, policy makers, and transportation practitioners who wish to promote bike-sharing service while ensuring its sustainability. Keywords: Built environment; data mining; dockless/stationless; bike sharing; GPS data; spatiotemporal analysis |
| first_indexed | 2024-09-23T12:08:41Z |
| format | Article |
| id | mit-1721.1/120460 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T12:08:41Z |
| publishDate | 2019 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | mit-1721.1/1204602022-09-28T00:29:13Z Understanding the usage of dockless bike sharing in Singapore Shen, Yu Zhang, Xiaohu Zhao, Jinhua Massachusetts Institute of Technology. Department of Urban Studies and Planning Zhao, Jinhua A new generation of bike-sharing services without docking stations is currently revolutionizing the traditional bike-sharing market as it dramatically expands around the world. This study aims at understanding the usage of new dockless bike-sharing services through the lens of Singapore's prevalent service. We collected the GPS data of all dockless bikes from one of the largest bike sharing operators in Singapore for nine consecutive days, for a total of over 14 million records. We adopted spatial autoregressive models to analyze the spatiotemporal patterns of bike usage during the study period. The models explored the impact of bike fleet size, surrounding built environment, access to public transportation, bicycle infrastructure, and weather conditions on the usage of dockless bikes. Larger bike fleet is associated with higher usage but with diminishing marginal impact. In addition, high land use mixtures, easy access to public transportation, more supportive cycling facilities, and free-ride promotions positively impact the usage of dockless bikes. The negative influence of rainfall and high temperatures on bike utilization is also exhibited. The study also offered some guidance to urban planners, policy makers, and transportation practitioners who wish to promote bike-sharing service while ensuring its sustainability. Keywords: Built environment; data mining; dockless/stationless; bike sharing; GPS data; spatiotemporal analysis 2019-02-14T19:32:37Z 2019-02-14T19:32:37Z 2018-01 2018-01 2019-01-24T14:00:06Z Article http://purl.org/eprint/type/JournalArticle 1556-8318 1556-8334 http://hdl.handle.net/1721.1/120460 Shen, Yu et al. “Understanding the Usage of Dockless Bike Sharing in Singapore.” International Journal of Sustainable Transportation 12, 9 (February 2018): 686–700 © 2018 Taylor & Francis Group, LLC https://orcid.org/0000-0002-1929-7583 http://dx.doi.org/10.1080/15568318.2018.1429696 International Journal of Sustainable Transportation Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Taylor & Francis Other repository |
| spellingShingle | Shen, Yu Zhang, Xiaohu Zhao, Jinhua Understanding the usage of dockless bike sharing in Singapore |
| title | Understanding the usage of dockless bike sharing in Singapore |
| title_full | Understanding the usage of dockless bike sharing in Singapore |
| title_fullStr | Understanding the usage of dockless bike sharing in Singapore |
| title_full_unstemmed | Understanding the usage of dockless bike sharing in Singapore |
| title_short | Understanding the usage of dockless bike sharing in Singapore |
| title_sort | understanding the usage of dockless bike sharing in singapore |
| url | http://hdl.handle.net/1721.1/120460 https://orcid.org/0000-0002-1929-7583 |
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