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Article: Estimation algorithm for predicting the performance of private apartment buildings in Hong Kong

TitleEstimation algorithm for predicting the performance of private apartment buildings in Hong Kong
Authors
KeywordsBuildings
Hong Kong
Quality
Issue Date2009
PublisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/ss.htm
Citation
Structural Survey, 2009, v. 27 n. 5, p. 372-389 How to Cite?
AbstractPurpose: For the sake of public health and safety, a territory-wide evaluation of the quality of buildings in Hong Kong is crucial. However, it is a lengthy process to assess the performance of the whole stock of buildings in the city. To get around this predicament, this paper aims to propose a statistical approach for a fast and reliable building evaluation algorithm using the Building Quality Index (BQI) developed by The University of Hong Kong. Design/methodology/approach: Using the BQI assessment framework, the condition of 133 and 160 private apartment buildings in Yau Tsim Mong and the Eastern District respectively are assessed and rated. The data of the Yau Tsim Mong buildings are used to estimate a regression model associating the relationships between building performance, measured by the BQI, and other exogenous factors. The resulting model is then employed to predict the performance of the surveyed buildings in the Eastern District. Findings: The regression analyses on the Yau Tsim Mong data indicate that building age, development scale and building management mode are significant determinants of the existing condition of the sampled buildings, echoing the findings of previous studies. BQI scores of buildings in the Eastern District are estimated using the resulting regression model, and there is a highly positive relationship between the predicted BQI and in-situ BQI scores. Originality/value: The study is the first in the literature to provide an algorithm for estimating building condition in a densely developed high-rise urban area. © Emerald Group Publishing Limited.
Persistent Identifierhttp://hdl.handle.net/10722/136317
ISSN
2015 SCImago Journal Rankings: 0.262
References

 

DC FieldValueLanguage
dc.contributor.authorYau, Yen_HK
dc.contributor.authorHo, DCWen_HK
dc.contributor.authorChau, KWen_HK
dc.contributor.authorLau, WYen_HK
dc.date.accessioned2011-07-27T02:13:05Z-
dc.date.available2011-07-27T02:13:05Z-
dc.date.issued2009en_HK
dc.identifier.citationStructural Survey, 2009, v. 27 n. 5, p. 372-389en_HK
dc.identifier.issn0263-080Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/136317-
dc.description.abstractPurpose: For the sake of public health and safety, a territory-wide evaluation of the quality of buildings in Hong Kong is crucial. However, it is a lengthy process to assess the performance of the whole stock of buildings in the city. To get around this predicament, this paper aims to propose a statistical approach for a fast and reliable building evaluation algorithm using the Building Quality Index (BQI) developed by The University of Hong Kong. Design/methodology/approach: Using the BQI assessment framework, the condition of 133 and 160 private apartment buildings in Yau Tsim Mong and the Eastern District respectively are assessed and rated. The data of the Yau Tsim Mong buildings are used to estimate a regression model associating the relationships between building performance, measured by the BQI, and other exogenous factors. The resulting model is then employed to predict the performance of the surveyed buildings in the Eastern District. Findings: The regression analyses on the Yau Tsim Mong data indicate that building age, development scale and building management mode are significant determinants of the existing condition of the sampled buildings, echoing the findings of previous studies. BQI scores of buildings in the Eastern District are estimated using the resulting regression model, and there is a highly positive relationship between the predicted BQI and in-situ BQI scores. Originality/value: The study is the first in the literature to provide an algorithm for estimating building condition in a densely developed high-rise urban area. © Emerald Group Publishing Limited.en_HK
dc.languageengen_US
dc.publisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/ss.htmen_HK
dc.relation.ispartofStructural Surveyen_HK
dc.subjectBuildingsen_HK
dc.subjectHong Kongen_HK
dc.subjectQualityen_HK
dc.titleEstimation algorithm for predicting the performance of private apartment buildings in Hong Kongen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0263-080X&volume=27&issue=5&spage=372&epage=389&date=2009&atitle=Estimation+algorithm+for+predicting+the+performance+of+private+apartment+buildings+in+Hong+Kongen_US
dc.identifier.emailHo, DCW:danielho@hku.hken_HK
dc.identifier.emailChau, KW:hrrbckw@hkucc.hku.hken_HK
dc.identifier.authorityHo, DCW=rp01001en_HK
dc.identifier.authorityChau, KW=rp00993en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1108/02630800911002639en_HK
dc.identifier.scopuseid_2-s2.0-72049092457en_HK
dc.identifier.hkuros188539en_US
dc.identifier.hkuros181873-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-72049092457&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume27en_HK
dc.identifier.issue5en_HK
dc.identifier.spage372en_HK
dc.identifier.epage389en_HK
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridYau, Y=12806101900en_HK
dc.identifier.scopusauthoridHo, DCW=12805583800en_HK
dc.identifier.scopusauthoridChau, KW=24830082500en_HK
dc.identifier.scopusauthoridLau, WY=13608386400en_HK
dc.identifier.citeulike6206328-

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