Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102324
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorGuo, Zen_US
dc.creatorZhao, Pen_US
dc.creatorSenousi, AMen_US
dc.creatorLiu, Xen_US
dc.creatorMansourian, Aen_US
dc.date.accessioned2023-10-18T07:51:10Z-
dc.date.available2023-10-18T07:51:10Z-
dc.identifier.issn2214-367Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/102324-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2023 The Authors. Published by Elsevier Ltd on behalf of Hong Kong Society for Transportation Studies. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Guo, Z., Zhao, P., Senousi, A. M., Liu, X., & Mansourian, A. (2023). Exploring the structural characteristics of intra-urban shared freight network and their associations with socioeconomic status. Travel Behaviour and Society, 32, 100576 is availale at https://doi.org/10.1016/j.tbs.2023.100576.en_US
dc.subjectComplex networken_US
dc.subjectGeographically weighted regressionen_US
dc.subjectShared freight transportationen_US
dc.subjectSocioeconomic statusen_US
dc.titleExploring the structural characteristics of intra-urban shared freight network and their associations with socioeconomic statusen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume32en_US
dc.identifier.doi10.1016/j.tbs.2023.100576en_US
dcterms.abstractIn recent years, shared freight systems have emerged in many cities as a new modality of freight transportation. However, little attention has been paid to the impact of a city's socioeconomic status on the characteristics of a shared freight network. To fill this gap, in this study, the structural characteristics of an intra-urban shared freight network are measured from the perspective of complex networks, and the correlations between network structure and socioeconomic status are examined. A case study is conducted in Hong Kong using large amounts of GPS trajectory data for freight vehicles and socioeconomic data. The results show that socioeconomic variables such as population size, percentage of elderly residents, percentage of residents with a marital status classified as “other” (i.e., separated, widowed, or divorced), and percentage of residents employed in the tertiary sector have distinct correlations with the structural characteristics. These correlations display spatial non-stationarity. This research can potentially assist decision-makers in improving the operating efficiency of shared freight systems and the governance of digital freight transport.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTravel behaviour and society, July 2023, v. 32, 100576en_US
dcterms.isPartOfTravel behaviour and societyen_US
dcterms.issued2023-07-
dc.identifier.scopus2-s2.0-85149296145-
dc.identifier.artn100576en_US
dc.description.validate202310 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextResearch Institute for Land and Space); National Natural Science Foundation of China; Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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