Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103222
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dc.contributorDepartment of Building and Real Estateen_US
dc.creatorHong, Jen_US
dc.creatorGu, Jen_US
dc.creatorHe, Ren_US
dc.creatorWang, Xen_US
dc.creatorShen, Qen_US
dc.date.accessioned2023-12-11T00:32:26Z-
dc.date.available2023-12-11T00:32:26Z-
dc.identifier.issn0360-5442en_US
dc.identifier.urihttp://hdl.handle.net/10397/103222-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2020 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Hong, J., Gu, J., He, R., Wang, X., & Shen, Q. (2020). Unfolding the spatial spillover effects of urbanization on interregional energy connectivity: Evidence from province-level data. Energy, 196, 116990 is available at https://doi.org/10.1016/j.energy.2020.116990.en_US
dc.subjectChinaen_US
dc.subjectDurbin modelen_US
dc.subjectEnergy connectivityen_US
dc.subjectSpatialityen_US
dc.subjectSpillover effectsen_US
dc.subjectUrbanizationen_US
dc.titleUnfolding the spatial spillover effects of urbanization on interregional energy connectivity : evidence from province-level dataen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume196en_US
dc.identifier.doi10.1016/j.energy.2020.116990en_US
dcterms.abstractChina has exhibited an active attitude with regard to abating global climate change. To analyze the effect of economy development and urbanization quality on interregional energy transmissions against a backdrop of new-type urbanization, this study integrated MRIO model, complex network method, and spatial autocorrelation analysis to systematically analyze the spatiality and spillover effects of interregional energy connections. The results show that the interregional energy connectivity was spatially dependent whilst urban-rural income ratios and population structures were statistically significant in the national-level spatial econometric analysis. Specifically, a regional-level spatial regression analysis demonstrated that population structure, education level, the energy connectivity of other regions, and the income-expenditure ratios of other regions were four determinants that were significant in eastern, central, and western areas. Structural optimization is a key direction for future energy reduction nationwide. This study shed light on the current spillover effects of energy connective intensity, which is beneficial for making stratified and fair energy reduction policies at the regional level.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEnergy, 1 Apr. 2020, v. 196, 116990en_US
dcterms.isPartOfEnergyen_US
dcterms.issued2020-04-01-
dc.identifier.scopus2-s2.0-85079015503-
dc.identifier.eissn1873-6785en_US
dc.identifier.artn116990en_US
dc.description.validate202312 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBRE-0341-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextFundamental Research Funds for the Central Universities; Natural Science Foundation of China; Chongqing Science & Technology Commission; Project of Humanities and Social Sciences; Chongqing Social Science Planning Programen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24251844-
dc.description.oaCategoryGreen (AAM)en_US
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