Abstract
Integrating continuous improvement and circular economy principles can promote sustainable construction practices (SCPs) and deliver long-term environmental, social and economic benefits. This study demonstrated how text mining could be applied to explicate the linkage between continuous improvement and circular economy principles in enhancing sustainable construction practices. The research applied unsupervised machine learning using text mining analyses through collocations to identify thematic areas where the integration of continuous improvement and circular economy principles would foster sustainable construction. Eighty-nine (89) peer-reviewed publications were extracted from the Scopus database for text mining analysis. The findings from text mining presented seven cogent themes through which continuous improvement and circular economy can be integrated. The optimal integration of the linkages advocated in this research can facilitate improved SCPs such as design for disassembly, modular construction, adaptive reuse, eco-friendly materials, innovative technologies, industrial symbiosis, life cycle assessment, cradle-to-cradle design, and lean construction practices. This investigation elucidated the utility of machine learning text mining in thematising and advancing sustainable construction research.
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Divisions: | School of Built Environment, Engineering and Computing |
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Status: | Published |
Refereed: | Yes |
Uncontrolled Keywords: | sustainable construction, mprovement, circular economy, text mining, |
Depositing User (symplectic) | Deposited by Omotayo, Temitope |
Date Deposited: | 13 Sep 2024 15:17 |
Last Modified: | 13 Sep 2024 23:10 |
Event Title: | Association of Researchers in Construction Management (ARCOM) 2023 |
Event Dates: | 04 September 2023 - 06 September 2023 |
Item Type: | Conference or Workshop Item (Paper) |
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