Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118493
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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.contributorMainland Development Officeen_US
dc.contributorResearch Institute for Sustainable Urban Developmenten_US
dc.contributorOtto Poon Charitable Foundation Smart Cities Research Instituteen_US
dc.creatorZhou, Sen_US
dc.creatorLiu, Jen_US
dc.creatorZhang, Yen_US
dc.creatorBu, Yen_US
dc.creatorHuang, Xen_US
dc.creatorZhuge, Cen_US
dc.date.accessioned2026-04-20T03:16:11Z-
dc.date.available2026-04-20T03:16:11Z-
dc.identifier.issn1361-9209en_US
dc.identifier.urihttp://hdl.handle.net/10397/118493-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.subjectAgent-based modelingen_US
dc.subjectImpact assessmenten_US
dc.subjectLand use and transport Interactionen_US
dc.subjectUrban dynamicsen_US
dc.subjectWorking from homeen_US
dc.titleAssessing the dynamic impacts of remote work in New York cityen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume154en_US
dc.identifier.doi10.1016/j.trd.2026.105260en_US
dcterms.abstractWorking from Home (WFH) has stabilized above pre-pandemic levels, yet its long-term and multidimensional impacts remain unclear. This study explored different WFH arrangements within urban dynamics. Three scenarios in New York City—fully on-site, fully flexible, and structured hybrid—were designed to evaluate the long-term systematic impacts of WFH on population, economy, and environment from 2020 to 2035. An agent-based land use and transport interaction model incorporating a WFH module (i.e., SelfSim-WFH) was developed to capture the feedback of individuals’ WFH decisions and other associated urban elements. Results suggest that: (1) WFH induces a “donut effect,” with decentralization of residence and employment leading to longer home-work distance; (2) housing market growth slows, with rents responding more sensitively, while office rent declines; and (3) environmental gains from reduced commuting are partially offset by longer home-work distance and modal shifts, causing rebound effects in emissions and energy use under certain scenarios.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part D, Transport and environment, May 2026, v. 154, 105260en_US
dcterms.isPartOfTransportation research. Part D, Transport and environmenten_US
dcterms.issued2026-05-
dc.identifier.scopus2-s2.0-105029774962-
dc.identifier.eissn1879-2340en_US
dc.identifier.artn105260en_US
dc.description.validate202604 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG001496/2026-04-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextWe thank the Shenzhen Park of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone and this research has been supported by the \u201CTheories for Spatiotemporal Intelligence and Reliable Data Analysis\u201D (Project ID: HZQSWS-KCCYB-2024058), the MTR Research Funding Scheme (Grant No.: PTU-25012), the European Research Council (ERC) for the iDODDLE project (grant #101003083), the Shenzhen Municipal Science and Technology Innovation Commission (Grant No.: JCYJ20230807140401003), the Research Grants from the Smart Cities Research Institute (Grant No.: CDAR and CDA9) and Research Institute for Sustainable Urban Development (Grant No.: BBWR) at the Hong Kong Polytechnic University.en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2028-05-31en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2028-05-31
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