TY - JOUR
T1 - The role of artificial intelligence in lean construction management
AU - Dumrak, Jantanee
AU - Zarghami, Seyed Ashkan
N1 - Publisher Copyright:
© 2023, Emerald Publishing Limited.
PY - 2023
Y1 - 2023
N2 - Purpose: The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers a classification scheme that specifies different categories of AI tools, as applied to the field of LCM to support various principles of LCM. Design/methodology/approach: This research adopts the systematic literature review (SLR) process, which consists of five consecutive steps: planning, searching, screening, extraction and synthesis and reporting. As a supplement to SLR, a bibliometric analysis is performed to examine the quantity and citation impact of the reviewed papers. Findings: In this paper, seven key areas related to the principles of LCM for which AI tools have been used are identified. The findings of this research clarify how AI can assist in bolstering the practice of LCM. Further, this article presents directions for the future evolution of AI tools in LCM based on the current emerging trends. Practical implications: This paper advances the LCM systems by offering a lens through which construction managers can better understand key concepts in the linkage of AI to LCM. Originality/value: This research offers a new classification scheme that allows researchers to properly recall, identify and group various applications of AI categories in the construction industry based on various principles of LCM. In addition, this study provides a source of references for researchers in the LCM discipline, which advances knowledge and facilitates theory development in the field.
AB - Purpose: The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers a classification scheme that specifies different categories of AI tools, as applied to the field of LCM to support various principles of LCM. Design/methodology/approach: This research adopts the systematic literature review (SLR) process, which consists of five consecutive steps: planning, searching, screening, extraction and synthesis and reporting. As a supplement to SLR, a bibliometric analysis is performed to examine the quantity and citation impact of the reviewed papers. Findings: In this paper, seven key areas related to the principles of LCM for which AI tools have been used are identified. The findings of this research clarify how AI can assist in bolstering the practice of LCM. Further, this article presents directions for the future evolution of AI tools in LCM based on the current emerging trends. Practical implications: This paper advances the LCM systems by offering a lens through which construction managers can better understand key concepts in the linkage of AI to LCM. Originality/value: This research offers a new classification scheme that allows researchers to properly recall, identify and group various applications of AI categories in the construction industry based on various principles of LCM. In addition, this study provides a source of references for researchers in the LCM discipline, which advances knowledge and facilitates theory development in the field.
KW - Artificial intelligence
KW - Bibliometric analysis
KW - Lean construction management
KW - Systematic literature review
UR - http://www.scopus.com/inward/record.url?scp=85164163032&partnerID=8YFLogxK
U2 - 10.1108/ECAM-02-2022-0153
DO - 10.1108/ECAM-02-2022-0153
M3 - Review article
AN - SCOPUS:85164163032
SN - 0969-9988
JO - Engineering, Construction and Architectural Management
JF - Engineering, Construction and Architectural Management
ER -