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Article: An anatomy of waste generation flows in construction projects using passive bigger data

TitleAn anatomy of waste generation flows in construction projects using passive bigger data
Authors
KeywordsConstruction waste management
Waste generation flow
Building projects
Bigger data
Issue Date2020
PublisherElsevier Ltd. The Journal's web site is located at https://www.journals.elsevier.com/waste-management/
Citation
Waste Management, 2020, v. 106, p. 162-172 How to Cite?
AbstractUnderstanding waste generation flow is vital to any evidence-based effort by policy-makers and practitioners to successfully manage construction project waste. Previous research has found that accumulative waste generation in construction projects follows an S-curve, but improving our understanding of waste generation requires its investigation at a higher level of granularity. Such efforts, however, are often constrained by lack of quality “bigger” data, i.e. data that is bigger than normal small data. This research aims to provide an anatomy of waste generation flow in building projects by making use of a large set of data on waste generation in 19 demolition, 59 foundation, and 54 new building projects undertaken in Hong Kong between 2011 and 2019. We know that waste is generated in far from a steady stream as it is always impacted by contingent factors. However, we do find that peaks of waste generation in foundation projects appear when project duration is at 50–85%, and in new building projects at 40–70% of total project time. Our research provides useful information for waste managers in developing their waste management plans, arranging waste hauling logistics, and benchmarking waste management performance.
Persistent Identifierhttp://hdl.handle.net/10722/283318
ISSN
2021 Impact Factor: 8.816
2020 SCImago Journal Rankings: 1.807
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXU, J-
dc.contributor.authorLu, W-
dc.contributor.authorYe, M-
dc.contributor.authorWebster, C-
dc.contributor.authorXue, F-
dc.date.accessioned2020-06-22T02:54:57Z-
dc.date.available2020-06-22T02:54:57Z-
dc.date.issued2020-
dc.identifier.citationWaste Management, 2020, v. 106, p. 162-172-
dc.identifier.issn0956-053X-
dc.identifier.urihttp://hdl.handle.net/10722/283318-
dc.description.abstractUnderstanding waste generation flow is vital to any evidence-based effort by policy-makers and practitioners to successfully manage construction project waste. Previous research has found that accumulative waste generation in construction projects follows an S-curve, but improving our understanding of waste generation requires its investigation at a higher level of granularity. Such efforts, however, are often constrained by lack of quality “bigger” data, i.e. data that is bigger than normal small data. This research aims to provide an anatomy of waste generation flow in building projects by making use of a large set of data on waste generation in 19 demolition, 59 foundation, and 54 new building projects undertaken in Hong Kong between 2011 and 2019. We know that waste is generated in far from a steady stream as it is always impacted by contingent factors. However, we do find that peaks of waste generation in foundation projects appear when project duration is at 50–85%, and in new building projects at 40–70% of total project time. Our research provides useful information for waste managers in developing their waste management plans, arranging waste hauling logistics, and benchmarking waste management performance.-
dc.languageeng-
dc.publisherElsevier Ltd. 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.subjectConstruction waste management-
dc.subjectWaste generation flow-
dc.subjectBuilding projects-
dc.subjectBigger data-
dc.titleAn anatomy of waste generation flows in construction projects using passive bigger data-
dc.typeArticle-
dc.identifier.emailLu, W: wilsonlu@hku.hk-
dc.identifier.emailWebster, C: cwebster@hku.hk-
dc.identifier.emailXue, F: xuef@hku.hk-
dc.identifier.authorityLu, W=rp01362-
dc.identifier.authorityWebster, C=rp01747-
dc.identifier.authorityXue, F=rp02189-
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.wasman.2020.03.024-
dc.identifier.pmid32220824-
dc.identifier.scopuseid_2-s2.0-85082176562-
dc.identifier.hkuros310560-
dc.identifier.volume106-
dc.identifier.spage162-
dc.identifier.epage172-
dc.identifier.isiWOS:000525840000022-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0956-053X-

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