An artificial neural network analysis of rework in sustainable buildings

Abstract Sustainable buildings were introduced to lessen the negative impact of on their users, occupants, communities, and environment, increase contractors’ productivity profit margins. However, despite prospects benefits sustainable buildings, instances reworking in have been recorded by construction companies. This research developed a questionnaire instrument that included 20 determinants rework measured 5-point Likert scale. An artificial neural network model was used predict buildings. The data revealed are delayed more than 15% cost overrun 20%. Rework is about 15%. correlation results will project costs up 29% completion time 27%. lack performance specification; skilled workers with green materials components; poor application industrialised building systems; governance; absence managers; welfare; adoption information modelling main predictors reworks. provide references for all stakeholders involved procurement study foremost examine reworks as its findings hold critical theoretical practical implications future market.