Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116483
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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.contributorResearch Institute for Sustainable Urban Developmenten_US
dc.contributorMainland Development Officeen_US
dc.contributorOtto Poon Charitable Foundation Smart Cities Research Instituteen_US
dc.creatorYang, Xen_US
dc.creatorZhuge, Cen_US
dc.creatorShao, Cen_US
dc.creatorGuo, Ren_US
dc.creatorWong, ATCen_US
dc.creatorZhang, Xen_US
dc.creatorSun, Men_US
dc.creatorWang, Pen_US
dc.creatorWang, Sen_US
dc.date.accessioned2026-01-02T09:28:04Z-
dc.date.available2026-01-02T09:28:04Z-
dc.identifier.issn0049-4488en_US
dc.identifier.urihttp://hdl.handle.net/10397/116483-
dc.language.isoenen_US
dc.publisherSpringer New York LLCen_US
dc.rights© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11116-023-10427-8.en_US
dc.subjectCommutersen_US
dc.subjectDominant charging locationen_US
dc.subjectElectric vehicleen_US
dc.subjectMixed logistic regression modelen_US
dc.subjectTrajectory dataen_US
dc.titleDominant charging location choice of commuters and non-commuters : a big data approachen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage439en_US
dc.identifier.epage466en_US
dc.identifier.volume52en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1007/s11116-023-10427-8en_US
dcterms.abstractThis paper is focused on electric vehicle (EV) users’ dominant charging locations, where they get their EVs recharged more frequently. We particularly compared the dominant charging location choice of commuters and non-commuters using a unique one-month trajectory dataset collected from 76,774 actual private EVs in Beijing in January 2018. Specifically, we first grouped EV users for both commuters and non-commuters according to their dominant charging locations and then characterized and compared their charging patterns. Further, we associated the dominant charging location choice of EV users with their characteristics using a mixed logistic regression model. The results suggested that over 50% of the EV users were the Home Dominated users with most charging events occurring around home. Further, there were significant differences in charging patterns of EV users from different groups by dominant charging location, and also between commuters and non-commuters. Commuters tended to have a lower SOC than non-commuters when they got their EVs recharged. Moreover, the dominant charging location choice of EV users was significantly associated with their characteristics, including charging opportunities available and mobility patterns, and the association is different for commuters and non-commuters. The results are expected to be useful for deploying charging infrastructure.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation, Apr. 2025, v. 52, no. 2, p. 439-466en_US
dcterms.isPartOfTransportationen_US
dcterms.issued2025-04-
dc.identifier.scopus2-s2.0-105001076557-
dc.identifier.eissn1572-9435en_US
dc.description.validate202601 bcjzen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.SubFormIDG000603/2025-12-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis research was supported by the National Natural Science Foundation of China (52002345), and the RISUD Joint Research Fund (Project ID: P0042828), Funding Support to Small Projects (Project ID: P0038213) and SCRI IRF-SC (Project ID: P0041230) at the Hong Kong Polytechnic University.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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