Mapping the global knowledge landscape of digital transformation in the AEC industry: a scientometric analysis

被引:0
|
作者
Wang, Kaiyang [1 ,2 ]
机构
[1] Nanjing Forestry Univ, Coll Civil Engn, Nanjing, Peoples R China
[2] Univ Liverpool, Fac Sci & Engn, Liverpool, England
关键词
Digital transformation; AEC industry; CiteSpace; Scientometric analysis; Knowledge map; Topic detection; Co-occurrence analysis; Co-citation analysis; BIM ADOPTION; CONSTRUCTION; TECHNOLOGY; BLOCKCHAIN; BUILDINGS;
D O I
10.1108/ECAM-11-2023-1174
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Purpose - In recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector. Design/methodology/approach - Employing a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990-2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords. Findings - The findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include "building information modeling", "design", "system", "framework", "adoption", "model", "safety", "internet of things", and "innovation". Emerging areas of interest are "deep learning", "embodied energy", and "machine learning". A cluster analysis of keywords reveals key research themes such as "deep learning", "smart buildings", "virtual reality", "augmented reality", "smart contracts", "sustainable development", "building information modeling", "big data", and "3D printing". Originality/value - This study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.
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页数:35
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