TY - JOUR
T1 - Automation in architecture, engineering and construction
T2 - a scientometric analysis and implications for management
AU - Klarin, Anton
AU - Xiao, Qijie
N1 - Publisher Copyright:
© 2023, Emerald Publishing Limited.
PY - 2024
Y1 - 2024
N2 - Purpose: Many economic, political and socio-cultural events in the 2020s have been strong headwinds for architecture, engineering and construction (AEC). Nevertheless, technological advancements (e.g. artificial intelligence (AI), big data and robotics) provide promising avenues for the development of AEC. This study aims to map the state of the literature on automation in AEC and thereby be of value not only to those researching automation and its composition of a variety of distinct technological and system classes within AEC, but also to practitioners and policymakers in shaping the future of AEC. Design/methodology/approach: This review adopts scientometric methods, which have been effective in the research of large intra and interdisciplinary domains in the past decades. The full dataset consists of 1,871 articles on automation in AEC. Findings: This overarching scientometric review offers three interdisciplinary streams of research: technological frontiers, project monitoring and applied research in AEC. To support the scientometric analysis, the authors offer a critical integrative review of the literature to proffer a multilevel, multistage framework of automation in AEC, which demonstrates an abundance of technological paradigm discussions and the inherent need for a holistic managerial approach to automation in AEC. Originality/value: The authors underline employee well-being, business sustainability and social growth outcomes of automation and provide several managerial implications, such as the strategic management approach, ethical management view and human resource management perspective. In doing so, the authors seek to respond to the Sustainable Development Goals proposed by the United Nations as this becomes more prevalent for the industry and all levels of society in general.
AB - Purpose: Many economic, political and socio-cultural events in the 2020s have been strong headwinds for architecture, engineering and construction (AEC). Nevertheless, technological advancements (e.g. artificial intelligence (AI), big data and robotics) provide promising avenues for the development of AEC. This study aims to map the state of the literature on automation in AEC and thereby be of value not only to those researching automation and its composition of a variety of distinct technological and system classes within AEC, but also to practitioners and policymakers in shaping the future of AEC. Design/methodology/approach: This review adopts scientometric methods, which have been effective in the research of large intra and interdisciplinary domains in the past decades. The full dataset consists of 1,871 articles on automation in AEC. Findings: This overarching scientometric review offers three interdisciplinary streams of research: technological frontiers, project monitoring and applied research in AEC. To support the scientometric analysis, the authors offer a critical integrative review of the literature to proffer a multilevel, multistage framework of automation in AEC, which demonstrates an abundance of technological paradigm discussions and the inherent need for a holistic managerial approach to automation in AEC. Originality/value: The authors underline employee well-being, business sustainability and social growth outcomes of automation and provide several managerial implications, such as the strategic management approach, ethical management view and human resource management perspective. In doing so, the authors seek to respond to the Sustainable Development Goals proposed by the United Nations as this becomes more prevalent for the industry and all levels of society in general.
KW - Artificial intelligence
KW - Automation
KW - Bibliometrics
KW - Construction engineering and management
KW - Managerial implications
KW - Scientometrics
KW - Systematic literature review
UR - http://www.scopus.com/inward/record.url?scp=85150906242&partnerID=8YFLogxK
U2 - 10.1108/ECAM-08-2022-0770
DO - 10.1108/ECAM-08-2022-0770
M3 - Review Article
AN - SCOPUS:85150906242
SN - 0969-9988
VL - 31
SP - 3308
EP - 3334
JO - Engineering, Construction and Architectural Management
JF - Engineering, Construction and Architectural Management
IS - 8
ER -