独创性
领域(数学)
计算机科学
过程(计算)
知识管理
联动装置(软件)
钥匙(锁)
人工智能
引用
数据科学
管理科学
工程类
过程管理
定性研究
社会科学
生物化学
基因
操作系统
万维网
社会学
计算机安全
化学
纯数学
数学
作者
Jantanee Dumrak,Seyed Ashkan Zarghami
出处
期刊:Engineering, Construction and Architectural Management
[Emerald (MCB UP)]
日期:2023-07-01
被引量:10
标识
DOI:10.1108/ecam-02-2022-0153
摘要
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.
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