Artificial Intelligence in Building Information Modeling Research: Country and Document-based Citation and Bibliographic Coupling Analysis

Abstract

The intense association of the architecture, engineering, construction, operation, and facility management(AECO/FM) industry with cognitive and behavioral technologies leads to the increase in productivity of industryactivities. In light of these thoughts, the building information modeling (BIM) platform is included in theAECO/FM industry to further increase efficiency and deliver construction projects economically, timely, andsafely. While the BIM platform can work integrated with many programs and systems, concepts that offerinnovative and fast solutions such as artificial intelligence (AI) benefit the AECO/FM industry. The main aim ofthis study is to establish an understanding of the tendency of AI in BIM research carried out in differentcountries and by various scholars. This study adopts a bibliometric search, and a scientometric analysis andmapping approach with applying document-based citation analysis, country-based citation analysis, and countrybased bibliographic coupling analysis of scientific research of AI and BIM integration. Data about AI in BIMresearch has been collected by reviewing and screening articles selected from the Scopus database. The resultsreveal that information management, decision support systems, genetic algorithms, neural networks, knowledgebased systems, machine learning, and deep learning effect AI in BIM research. This article contributes to theAECO/FM literature by analyzing and visualizing the current status and relationship between AI and BIM.Therefore, the findings highlight the gaps and trends in AI and BIM studies and provide new recommendationsfor future studies.