Generalised Linear Modelling for Construction Waste Estimation in Residential Projects: Case Study in New Zealand
Niluka Domingo (),
Heshani M. Edirisinghe,
Ravindu Kahandawa and
Gayan Wedawatta
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Niluka Domingo: School of Built Environment, Massey University, Auckland 0632, New Zealand
Heshani M. Edirisinghe: School of Built Environment, Massey University, Auckland 0632, New Zealand
Ravindu Kahandawa: School of Built Environment, Massey University, Auckland 0632, New Zealand
Gayan Wedawatta: Department of Civil Engineering, School of Infrastructure and Sustainable Engineering, Ashton University, Birmingham B4 7ET, UK
Sustainability, 2024, vol. 16, issue 5, 1-14
Abstract:
Construction waste is a global problem, including in New Zealand where it makes up 40–50% of landfill waste. Accurately measuring construction waste is crucial to reduce its impact on New Zealand’s landfills and meet carbon targets. Waste can be effectively managed if predicted correctly from the start of a project. Waste generation depends on factors such as geography, society, technology, and construction methods. This study focuses on developing a model specific to New Zealand to predict waste generation in residential buildings. By analysing data from 213 residential projects, the study identifies the design features that have the greatest influence on construction waste generation. A generalized linear model is constructed to correlate these design features with waste generation. The findings are valuable for construction stakeholders seeking to implement waste reduction strategies based on predicted waste quantities. This research serves as a starting point, and further investigation in this area is necessary.
Keywords: construction waste; waste prediction; construction waste modelling; waste quantification; waste management; generalised liner regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:5:p:1941-:d:1346802
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