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Leveraging digital technologies for circular economy in construction industry: a way forward

Author(s): ORCID
ORCID

ORCID
Medium: journal article
Language(s): English
Published in: Smart and Sustainable Built Environment, , n. 1, v. 13
Page(s): 85-116
DOI: 10.1108/sasbe-05-2023-0111
Abstract:

Purpose

This study aims to investigate the literature related to the use of digital technologies for promoting circular economy (CE) in the construction industry.

Design/methodology/approach

A comprehensive approach was adopted, involving bibliometric analysis, text-mining analysis and content analysis to meet three objectives (1) to unveil the evolutionary progress of the field, (2) to identify the key research themes in the field and (3) to identify challenges hindering the implementation of digital technologies for CE.

Findings

A total of 365 publications was analysed. The results revealed eight key digital technologies categorised into two main clusters including “digitalisation and advanced technologies” and “sustainable construction technologies”. The former involved technologies, namely machine learning, artificial intelligence, deep learning, big data analytics and object detection and computer vision that were used for (1) forecasting construction and demolition (C&D) waste generation, (2) waste identification and classification and (3) computer vision for waste management. The latter included technologies such as Internet of Things (IoT), blockchain and building information modelling (BIM) that help optimise resource use, enhance transparency and sustainability practices in the industry. Overall, these technologies show great potential for improving waste management and enabling CE in construction.

Originality/value

This research employs a holistic approach to provide a status-quo understanding of the digital technologies that can be utilised to support the implementation of CE in construction. Further, this study underlines the key challenges associated with adopting digital technologies, whilst also offering opportunities for future improvement of the field.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1108/sasbe-05-2023-0111.
  • About this
    data sheet
  • Reference-ID
    10779622
  • Published on:
    12/05/2024
  • Last updated on:
    12/05/2024
 
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