Prefabricated Construction Risks: A Holistic Exploration through Advanced Bibliometric Tool and Content Analysis

Prefabricated construction (PC) offers advantages to the architecture, engineering, and construction (AEC) industry such as quality production, fast project completion, low waste output, high environmental sensitivity, and high security. Although PC has several advantages, knowledge gaps persist, necessitating a comprehensive bibliometric study. This research adopts a holistic bibliometric approach, combining qualitative (systematic literature review) and quantitative (bibliometric analysis) methods to assess the current state of prefabricated construction risks (PCRs) research and identify the literature trends. Unlike previous PCRs studies, our research capitalizes on the quantitative analysis capabilities of the Bibliometrix R-tool. We introduce innovative measures, such as the h-index, thematic mapping, and trend topic analysis, to deepen the understanding of the PCRs research landscape. Moreover, this study explores the intellectual structure of PCR research through keyword analysis, cluster analysis, and thematic evaluation, providing valuable insights into scientific studies, collaborations, and knowledge dissemination. In our study, following a systematic literature review to understand the existing knowledge, the R-studio Bibliometrix package is used to map the field, identify gaps in the field, and analyze the trends. This study involves a comprehensive bibliometric analysis of 150 articles in the field of PCRs, with data obtained from the Web of Science spanning from 2000 to 2023. The findings from the analyses reveal that the studies were divided into four different clusters: management, programming, logistics, and supply chain. Additionally, themes such as the integration of PC with Building Information Management (BIM), barriers, and stakeholders were also explored. The analyses indicate a growing awareness of PCRs, particularly in specific areas such as management, performance, and supply chain. This study stands out for its unique methods, analytical approach, and the use of specialized software. It provides valuable insights and suggestions for future studies.