Print Email Facebook Twitter Comparison of usage regularity and its determinants between docked and dockless bike-sharing systems Title Comparison of usage regularity and its determinants between docked and dockless bike-sharing systems: A case study in Nanjing, China Author Ji, Yanjie (Southeast University) Ma, Xinwei (Southeast University) He, Mingjia (Southeast University) Jin, Yuchuan (KTH Royal Institute of Technology) Yuan, Y. (TU Delft Transport and Planning) Date 2020-05-10 Abstract Bike-sharing systems have rapidly expanded around the world. Previous studies found that docked and dockless bike-sharing systems are different in terms of user demand and travel characteristics. However, their usage regularity and its determinants have not been fully understood. This research aims to fill this gap by exploring smart card data of a docked bike-sharing scheme and GPS trajectory data of a dockless bike-sharing scheme in Nanjing, China, over the same period. Both docked and dockless bike-sharing users can be classified into regular users and occasional users according to their usage frequency. Two systems are cross-compared regarding their travel characteristics. Then, binary logistic models are applied to reveal the impacts of travel characteristics and built environment factors on the regularity of bike-sharing usage. Results show that for both bike-sharing systems, regular users and occasional users share similar riding time and distance, while significant differences in the spatio-temporal distribution between docked and dockless bike-sharing systems are observed. The regression model results show that the “Trips during morning and afternoon peak hours” are positively associated with the regularity of both docked and dockless bike-sharing usage. However, the “Riding distance” variable is negatively associated with the usage regularity of both systems. Built environment factors including working point of interest (POI), residential POI, and transit POI promote the usage regularity of both bike-sharing systems. Finally, policy implications are proposed, such as increasing the density of docking stations in suburban areas and developing high-quality parking area for dockless bike-sharing around public transport stations. This study can help operators or governments to launch or improve the service of bike-sharing systems. Subject Docked bike-sharingDockless bike-sharingGPS trajectory dataRegularitySmart card dataSpatio-temporal pattern To reference this document use: http://resolver.tudelft.nl/uuid:0adac6b7-25e0-4f0f-b4b6-3554f1047315 DOI https://doi.org/10.1016/j.jclepro.2020.120110 Embargo date 2022-01-30 ISSN 0959-6526 Source Journal of Cleaner Production, 255 Part of collection Institutional Repository Document type journal article Rights © 2020 Yanjie Ji, Xinwei Ma, Mingjia He, Yuchuan Jin, Y. Yuan Files PDF JCLP2020_AAM.pdf 18.46 MB Close viewer /islandora/object/uuid:0adac6b7-25e0-4f0f-b4b6-3554f1047315/datastream/OBJ/view