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Article: A commuting spectrum analysis of the jobs–housing balance and self-containment of employment with mobile phone location big data

TitleA commuting spectrum analysis of the jobs–housing balance and self-containment of employment with mobile phone location big data
Authors
Keywordscommuting spectrum
jobs–housing balance
mobile phone location big data
self-containment of employment
work trips
Issue Date2018
PublisherSage Publications Ltd. The Journal's web site is located at http://journals.sagepub.com/home/epb
Citation
Environment and Planning B: Urban Analytics and City Science, 2018, v. 45 n. 3, p. 434-451 How to Cite?
AbstractStudies on the jobs–housing balance and self-containment of employment are mainly focused on observed journey-to-work trips using travel survey data. This study examines the relationship between the jobs–housing balance and the self-containment of employment through the use of mobile phone location data in Shenzhen, a megacity in southern China. Individual-level journey-to-work trips are explored based on mobile phone location big data. Self-containment of employment in the suburban districts is higher than that in the central districts. The effect of the jobs–housing balance on self-containment of employment is examined at a 2 km grid level. Jobs–housing balance policies positively affect the self-containment of employment in the suburban districts, but its effect is limited in the central districts. Two extreme commuting spectrum measures are used to analyze self-containment of employment in different journey-to-work scenarios with the same jobs–housing distribution. Workers are disaggregated into secondary and tertiary sector workers according to job types. The self-containment of employment is found to be mainly affected by the local jobs–housing balance for secondary-sector workers and the regional city level job distribution for tertiary-sector workers. The extreme scenarios of commuting behavior using the commuting spectrum method can provide benchmarks that can help to understand the observed self-containment of employment better. © 2017, © The Author(s) 2017.
Persistent Identifierhttp://hdl.handle.net/10722/248101
ISSN
2017 Impact Factor: 2.046
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhou, X-
dc.contributor.authorYeh, AGO-
dc.contributor.authorLi, W-
dc.contributor.authorYue, Y-
dc.date.accessioned2017-10-18T08:37:49Z-
dc.date.available2017-10-18T08:37:49Z-
dc.date.issued2018-
dc.identifier.citationEnvironment and Planning B: Urban Analytics and City Science, 2018, v. 45 n. 3, p. 434-451-
dc.identifier.issn2399-8083-
dc.identifier.urihttp://hdl.handle.net/10722/248101-
dc.description.abstractStudies on the jobs–housing balance and self-containment of employment are mainly focused on observed journey-to-work trips using travel survey data. This study examines the relationship between the jobs–housing balance and the self-containment of employment through the use of mobile phone location data in Shenzhen, a megacity in southern China. Individual-level journey-to-work trips are explored based on mobile phone location big data. Self-containment of employment in the suburban districts is higher than that in the central districts. The effect of the jobs–housing balance on self-containment of employment is examined at a 2 km grid level. Jobs–housing balance policies positively affect the self-containment of employment in the suburban districts, but its effect is limited in the central districts. Two extreme commuting spectrum measures are used to analyze self-containment of employment in different journey-to-work scenarios with the same jobs–housing distribution. Workers are disaggregated into secondary and tertiary sector workers according to job types. The self-containment of employment is found to be mainly affected by the local jobs–housing balance for secondary-sector workers and the regional city level job distribution for tertiary-sector workers. The extreme scenarios of commuting behavior using the commuting spectrum method can provide benchmarks that can help to understand the observed self-containment of employment better. © 2017, © The Author(s) 2017.-
dc.languageeng-
dc.publisherSage Publications Ltd. The Journal's web site is located at http://journals.sagepub.com/home/epb-
dc.relation.ispartofEnvironment and Planning B: Urban Analytics and City Science-
dc.rightsEnvironment and Planning B: Urban Analytics and City Science. Copyright © Sage Publications Ltd.-
dc.subjectcommuting spectrum-
dc.subjectjobs–housing balance-
dc.subjectmobile phone location big data-
dc.subjectself-containment of employment-
dc.subjectwork trips-
dc.titleA commuting spectrum analysis of the jobs–housing balance and self-containment of employment with mobile phone location big data-
dc.typeArticle-
dc.identifier.emailZhou, X: zhouxg@hku.hk-
dc.identifier.emailYeh, AGO: hdxugoy@hkucc.hku.hk-
dc.identifier.emailLi, W: wfli@hku.hk-
dc.identifier.authorityYeh, AGO=rp01033-
dc.identifier.authorityLi, W=rp01507-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1177/2399808317707967-
dc.identifier.scopuseid_2-s2.0-85041407711-
dc.identifier.hkuros280713-
dc.identifier.volume45-
dc.identifier.issue3-
dc.identifier.spage434-
dc.identifier.epage451-
dc.identifier.isiWOS:000432060800004-
dc.publisher.placeUnited Kingdom-

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