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Article: Jobs-housing relationships before and amid COVID-19: An excess-commuting approach

TitleJobs-housing relationships before and amid COVID-19: An excess-commuting approach
Authors
KeywordsBig data
Change
China
COVID-19
Jobs-housing relationship
Issue Date4-Dec-2022
PublisherElsevier
Citation
Journal of Transport Geography, 2023, v. 106 How to Cite?
Abstract

The outbreak of COVID-19 and subsequent pandemic containment measures have significantly affected our daily life, which has been extensively examined in the existing scholarship. However, the existing scholarship has done little on the jobs/housing relationship impacts of COVID-19. We attempted to fill this gap by using an excess-commuting approach. The approach allows us to analyse a series of jobs-housing matrices based on the location-based service big data of around fifty million individuals in the Pearl River Delta (PRD), China before and amid COVID-19. In the PRD, a zero-COVID policy was implemented, which presents a distinct and interesting context for our study. We found that after the COVID-19 outbreak: (1) residences and employment became more centrally located in downtowns, which is opposite to the suburbanization trend elsewhere; (2) in the whole PRD, the minimum and maximum commutes became smaller while the actual commute became larger, indicating the simultaneous presences of some paradoxical phenomena: a better spatial juxtaposition of jobs and housing, more compressed distribution of jobs and housing, and longer average actual commutes; (3) inter-city commutes between large cities were significantly refrained and decreased, while new inter-city commuters between smaller cities emerged; (4) it was more likely for the less-educated and female workers to see smaller minimum commutes amid COVID-19. This paper illustrates the potential of big data in the longitudinal study on jobs-housing relationships and excess commuting. It also produces new insights into such relationships in a unique context where stringent anti-COVID-19 policies have been continuously in place.

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Persistent Identifierhttp://hdl.handle.net/10722/340488
ISSN
2023 Impact Factor: 5.7
2023 SCImago Journal Rankings: 1.791
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, Ruoyu-
dc.contributor.authorZhang, Min-
dc.contributor.authorZhou, Jiangping-
dc.date.accessioned2024-03-11T10:45:00Z-
dc.date.available2024-03-11T10:45:00Z-
dc.date.issued2022-12-04-
dc.identifier.citationJournal of Transport Geography, 2023, v. 106-
dc.identifier.issn0966-6923-
dc.identifier.urihttp://hdl.handle.net/10722/340488-
dc.description.abstract<p>The outbreak of COVID-19 and subsequent pandemic containment measures have significantly affected our daily life, which has been extensively examined in the existing scholarship. However, the existing scholarship has done little on the jobs/housing relationship impacts of COVID-19. We attempted to fill this gap by using an excess-commuting approach. The approach allows us to analyse a series of jobs-housing matrices based on the location-based service big data of around fifty million individuals in the Pearl River Delta (PRD), China before and amid COVID-19. In the PRD, a zero-COVID policy was implemented, which presents a distinct and interesting context for our study. We found that after the COVID-19 outbreak: (1) residences and employment became more centrally located in downtowns, which is opposite to the <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/suburbanization" title="Learn more about suburbanization from ScienceDirect's AI-generated Topic Pages">suburbanization</a> trend elsewhere; (2) in the whole PRD, the minimum and maximum commutes became smaller while the actual commute became larger, indicating the simultaneous presences of some paradoxical phenomena: a better spatial juxtaposition of jobs and housing, more compressed distribution of jobs and housing, and longer average actual commutes; (3) inter-city commutes between large cities were significantly refrained and decreased, while new inter-city commuters between smaller cities emerged; (4) it was more likely for the less-educated and female workers to see smaller minimum commutes amid COVID-19. This paper illustrates the potential of big data in the <a href="https://www.sciencedirect.com/topics/social-sciences/longitudinal-analysis" title="Learn more about longitudinal study from ScienceDirect's AI-generated Topic Pages">longitudinal study</a> on jobs-housing relationships and excess commuting. It also produces new insights into such relationships in a unique context where stringent anti-COVID-19 policies have been continuously in place.</p><ul>​​​​​​​</ul>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofJournal of Transport Geography-
dc.subjectBig data-
dc.subjectChange-
dc.subjectChina-
dc.subjectCOVID-19-
dc.subjectJobs-housing relationship-
dc.titleJobs-housing relationships before and amid COVID-19: An excess-commuting approach-
dc.typeArticle-
dc.identifier.doi10.1016/j.jtrangeo.2022.103507-
dc.identifier.scopuseid_2-s2.0-85145267852-
dc.identifier.volume106-
dc.identifier.eissn1873-1236-
dc.identifier.isiWOS:000913769500001-
dc.identifier.issnl0966-6923-

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