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Article: Multilevel effects of urban form and urban functional zones on housing prices: evidence from open-source big data

TitleMultilevel effects of urban form and urban functional zones on housing prices: evidence from open-source big data
Authors
KeywordsHousing prices
Multilevel effect
Natural semantical language process
Open-source big data
Urban form
Urban functional zone
Issue Date14-Feb-2024
PublisherSpringer
Citation
Journal of Housing and the Built Environment, 2024, v. 39, n. 2, p. 987-1011 How to Cite?
AbstractWhile the relationship between local housing prices and the urban form and distribution of urban functional zones in a single city is well-discussed, the conclusion is usually sensitive to a particular city context, and cross-city comparative study is limited. This study attempts to examine the influences of urban form and urban functional zone distribution on housing prices within and between cities after controlling the city-wide socio-economic and demographic differences. Based on multiple open-source big data, such as points-of-interest (POI) and historical housing transaction data, the hierarchical linear model is utilized to compare the housing market of 10 extra-large cities in China. Results indicate that the urban form and the urban functional zone distribution significantly influence housing prices after the socio-economic and demographic differences are controlled. For inter-city comparison, an urban form with high compactness, low centrality, low polycentricity, high density, and low dissimilarity in housing development is related to lower city-level housing prices. For intra-city, proximity to work centers, high-quality hospitals, and schools shows positive associations to housing prices.
Persistent Identifierhttp://hdl.handle.net/10722/348239
ISSN
2023 Impact Factor: 1.8
2023 SCImago Journal Rankings: 0.564

 

DC FieldValueLanguage
dc.contributor.authorHuang, Guan-
dc.contributor.authorQiao, Si-
dc.contributor.authorYeh, Anthony Gar On-
dc.date.accessioned2024-10-08T00:31:10Z-
dc.date.available2024-10-08T00:31:10Z-
dc.date.issued2024-02-14-
dc.identifier.citationJournal of Housing and the Built Environment, 2024, v. 39, n. 2, p. 987-1011-
dc.identifier.issn1566-4910-
dc.identifier.urihttp://hdl.handle.net/10722/348239-
dc.description.abstractWhile the relationship between local housing prices and the urban form and distribution of urban functional zones in a single city is well-discussed, the conclusion is usually sensitive to a particular city context, and cross-city comparative study is limited. This study attempts to examine the influences of urban form and urban functional zone distribution on housing prices within and between cities after controlling the city-wide socio-economic and demographic differences. Based on multiple open-source big data, such as points-of-interest (POI) and historical housing transaction data, the hierarchical linear model is utilized to compare the housing market of 10 extra-large cities in China. Results indicate that the urban form and the urban functional zone distribution significantly influence housing prices after the socio-economic and demographic differences are controlled. For inter-city comparison, an urban form with high compactness, low centrality, low polycentricity, high density, and low dissimilarity in housing development is related to lower city-level housing prices. For intra-city, proximity to work centers, high-quality hospitals, and schools shows positive associations to housing prices.-
dc.languageeng-
dc.publisherSpringer-
dc.relation.ispartofJournal of Housing and the Built Environment-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectHousing prices-
dc.subjectMultilevel effect-
dc.subjectNatural semantical language process-
dc.subjectOpen-source big data-
dc.subjectUrban form-
dc.subjectUrban functional zone-
dc.titleMultilevel effects of urban form and urban functional zones on housing prices: evidence from open-source big data-
dc.typeArticle-
dc.identifier.doi10.1007/s10901-023-10109-y-
dc.identifier.scopuseid_2-s2.0-85185120300-
dc.identifier.volume39-
dc.identifier.issue2-
dc.identifier.spage987-
dc.identifier.epage1011-
dc.identifier.eissn1573-7772-
dc.identifier.issnl1566-4910-

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