File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: The effects of green building on construction waste minimization: Triangulating ‘big data’ with ‘thick data’

TitleThe effects of green building on construction waste minimization: Triangulating ‘big data’ with ‘thick data’
Authors
KeywordsBEAM Plus
Big data
Construction waste management
Green building
Hong Kong
Issue Date2018
PublisherPergamon. The Journal's web site is located at https://www.journals.elsevier.com/waste-management/
Citation
Waste Management, 2018, v. 79, p. 142-152 How to Cite?
AbstractIn contrast with the prolific research examining the effects of green building (GB) on property value, energy saving, or indoor air quality, there has been minimal focus on GB’s effects on Construction Waste Minimization (CWM), which is also an important aspect of cultivating sustainability in the built environment. To address this significant knowledge gap, this study has two progressive objectives: (1) to ascertain the empirical effects of GB on CWM and; (2) to identify and understand the causes leading to the ascertained effects. This is achieved by triangulating quantitative ‘big data’ obtained from government agencies with qualitative ‘thick data’ derived from case studies and interviews. The study found that BEAM Plus, the latest version of the Building Environmental Assessment Method developed by the Hong Kong Green Building Council (HKGBC), gave rise to a 36.19% waste reduction by weight for demolition works, but no statistically significant waste reduction for foundation or building works. It is because CWM, the basis for a demolition project to obtain GB credits, makes up only one of many ways for foundation or building works to earn credits, e.g., site aspects, lighting. In any case, CWM measures typically prove costlier means of acquiring credit, further causing developers to pay less attention to CWM in their GB tactics. The study’s results, i.e., CWM in GB significantly influences demolition, but only marginally for foundation and building works, provide useful scientific evidence to inform GB councils and other responsible bodies and encourage continuous improvement in GB practices. While the study in general sheds light on how the triangulation of big, empirical data with conventional, qualitative data, e.g., interviews with GB professionals, helps to better understand the subject of the investigation, i.e., the effects of GB on CWM.
Persistent Identifierhttp://hdl.handle.net/10722/261145
ISSN
2021 Impact Factor: 8.816
2020 SCImago Journal Rankings: 1.807
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLu, W-
dc.contributor.authorChen, X-
dc.contributor.authorPeng, Y-
dc.contributor.authorLiu, X-
dc.date.accessioned2018-09-14T08:53:14Z-
dc.date.available2018-09-14T08:53:14Z-
dc.date.issued2018-
dc.identifier.citationWaste Management, 2018, v. 79, p. 142-152-
dc.identifier.issn0956-053X-
dc.identifier.urihttp://hdl.handle.net/10722/261145-
dc.description.abstractIn contrast with the prolific research examining the effects of green building (GB) on property value, energy saving, or indoor air quality, there has been minimal focus on GB’s effects on Construction Waste Minimization (CWM), which is also an important aspect of cultivating sustainability in the built environment. To address this significant knowledge gap, this study has two progressive objectives: (1) to ascertain the empirical effects of GB on CWM and; (2) to identify and understand the causes leading to the ascertained effects. This is achieved by triangulating quantitative ‘big data’ obtained from government agencies with qualitative ‘thick data’ derived from case studies and interviews. The study found that BEAM Plus, the latest version of the Building Environmental Assessment Method developed by the Hong Kong Green Building Council (HKGBC), gave rise to a 36.19% waste reduction by weight for demolition works, but no statistically significant waste reduction for foundation or building works. It is because CWM, the basis for a demolition project to obtain GB credits, makes up only one of many ways for foundation or building works to earn credits, e.g., site aspects, lighting. In any case, CWM measures typically prove costlier means of acquiring credit, further causing developers to pay less attention to CWM in their GB tactics. The study’s results, i.e., CWM in GB significantly influences demolition, but only marginally for foundation and building works, provide useful scientific evidence to inform GB councils and other responsible bodies and encourage continuous improvement in GB practices. While the study in general sheds light on how the triangulation of big, empirical data with conventional, qualitative data, e.g., interviews with GB professionals, helps to better understand the subject of the investigation, i.e., the effects of GB on CWM.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at https://www.journals.elsevier.com/waste-management/-
dc.relation.ispartofWaste Management-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBEAM Plus-
dc.subjectBig data-
dc.subjectConstruction waste management-
dc.subjectGreen building-
dc.subjectHong Kong-
dc.titleThe effects of green building on construction waste minimization: Triangulating ‘big data’ with ‘thick data’-
dc.typeArticle-
dc.identifier.emailLu, W: wilsonlu@hku.hk-
dc.identifier.emailLiu, X: xliu6@hku.hk-
dc.identifier.authorityLu, W=rp01362-
dc.identifier.authorityLiu, X=rp01999-
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.wasman.2018.07.030-
dc.identifier.pmid30343740-
dc.identifier.scopuseid_2-s2.0-85050286318-
dc.identifier.hkuros290412-
dc.identifier.volume79-
dc.identifier.spage142-
dc.identifier.epage152-
dc.identifier.isiWOS:000449133500015-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0956-053X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats