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dc.contributor.authorLi, Sen
dc.contributor.authorGu, Hengyu
dc.contributor.authorShen, Jianfa
dc.date.accessioned2025-02-25T16:30:13Z
dc.date.available2025-02-25T16:30:13Z
dc.date.issued2023-04-13
dc.identifier309747977
dc.identifierfc0c5885-7b2d-476e-b9a8-5e492b12088f
dc.identifier85147503501
dc.identifier.citationLi , S , Gu , H & Shen , J 2023 , ' Detecting spatial heterogeneity in the determinants of intercity migration in China ' , Population, Space and Place , vol. 29 , no. 3 , e2649 . https://doi.org/10.1002/psp.2649en
dc.identifier.issn1544-8444
dc.identifier.otherORCID: /0000-0003-2953-5757/work/178181778
dc.identifier.urihttps://hdl.handle.net/10023/31502
dc.descriptionFunding: This work has received support from CUHK Vice-Chancellor's PhD Scholarship and CUHK Research Committee Research Fellowship Scheme.en
dc.description.abstractSpatial variations exist in migration patterns and the processes causing the observed patterns. Yet, far less attention has been given to the latter. Even if a few studies have engaged in spatial heterogeneity in the process of migration, the scale multiplicity is not emphasised. This research aims to address these gaps with evidence from Chinese cities. To facilitate international comparisons, we use data on intercity migration over a 5-year interval instead of the floating population. Following an elaboration of highly imbalanced migration patterns at the city scale, we detect spatial heterogeneity in the processes underlying these patterns based on 17 potential determinants in four domains (namely labour market conditions, site-specific amenities, agglomerative effects, and institutional dividends) by multiscale geographically weighted regression. The results indicate that cities' attractiveness to migrants depends on a broad spectrum of factors whose influences are location-dependent and exhibit specific patterns, including east–west, south–north, and southwest–northeast gradient patterns, as well as discrete clustered and concentric patterns. The diagnostic analysis has confirmed that the provenance of spatial-varying effects is irrelevant to the nonlinearity. These effects are also scale-sensitive, showing that the influencing scales of the labour market status and agglomeration factors tend to be larger (i.e., their effects are spatially stationary) than those relevant to amenities and policies, which vary considerably (i.e., the impacts of some factors change significantly over space). These findings regarding spatial heterogeneity deepen our understanding of migration in China and highlight the fact that there is no ‘one size fits all’ approach for government policies designed to attract migrants.
dc.format.extent16
dc.format.extent2256973
dc.language.isoeng
dc.relation.ispartofPopulation, Space and Placeen
dc.rights© 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.en
dc.subjectChinaen
dc.subjectIntercity migrationen
dc.subjectMigration patternen
dc.subjectMultiscale geographically weighted regressionen
dc.subjectScale multiplicityen
dc.subjectSpatial heterogeneityen
dc.subjectNSen
dc.subjectMCCen
dc.titleDetecting spatial heterogeneity in the determinants of intercity migration in Chinaen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews.School of Geography & Sustainable Developmenten
dc.contributor.institutionUniversity of St Andrews.Population and Health Researchen
dc.contributor.institutionUniversity of St Andrews.Bell-Edwards Geographic Data Instituteen
dc.identifier.doi10.1002/psp.2649
dc.description.statusPeer revieweden


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