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Risk management in construction projects requires effective construction supply chain risk management (CSCRM). To gain insights into CSCRM research, this paper conducts a systematic literature review and bibliometric analysis covering the period from 1999 to 2023. The findings of this comprehensive analysis shed light on various aspects, including risk management phases, classification of micro or macrolevel risks, traditional approaches, and the emergence of artificial intelligence (AI) applications. Through an extensive database search, relevant articles on CSCRM were identified for analysis. The review reveals that while traditional techniques such as surveys, case studies, and statistical tools remain prominent, there is an increasing adoption of AI methods. Initially focused on risk identification, assessment, and analysis; the CSCRM phases have expanded over time to include risk allocation, prioritization, and recovery. Analysis of publication trends shows a rise in the use of AI techniques since 2016 alongside persistent utilization of traditional approaches. Moreover, influential authors, journals, and collaborative networks are highlighted to provide valuable insights into the field's development. Overall visualization contributes to advancing both research and practice in CSCRM by presenting a holistic overview of theories, methods, and emerging technologies within the field along with critical risk management approaches and publication trends. [Display omitted] • Systematic analysis of CSCRM research from 1999 to 2023. • Insights on risk management phases and risk classifications. • Traditional vs. AI approaches in CSCRM. • Identification of influential authors, journals, and networks. • Evolving trends: Increased AI adoption in CSCRM research. [ABSTRACT FROM AUTHOR]

The path to implementing successful, productive, and sustainable off-site 3D concrete printing building systems is unclear. To provide clarity, this paper aims to determine targeted actions for stakeholders in the construction industry. A systematic literature review and a bibliometric analysis are conducted to identify driver-barriers of Off-site Construction (OSC) and 3D Concrete Printing (3DCP). Thirty-four stakeholder-linked targeted actions are determined and divided into industry, organisational, project, and system levels. The findings indicate the success of off-site 3DCP building systems is not exclusively dependent on the system performance and a variety of actions are required from multiple stakeholders. This paper provides a theoretical foundation for practical actions and further research to implement off-site 3DCP building systems in local construction industries. • Drivers and barriers are identified with a systematic literature review on off-site construction and 3D concrete printing. • A bibliometric analysis using VOSviewer software is performed. • Stakeholders in off-site 3DCP are identified. • Stakeholder-linked targeted actions which aim to enable the development of off-site 3DCP building systems are derived [ABSTRACT FROM AUTHOR]

Blockchain has attracted great attention in the architecture, engineering, construction, and operation (AECO) industry. To capture its research trends, this study conducted a comprehensive review of blockchain development in the industry using a mixed approach of bibliometrics and content analyses. Ninety-four papers were filtered from the Scopus and Web of Science databases for this review. Bibliometric analysis revealed annual publication trends, journal distributions, country distributions, high-yielding authors, author cooperation networks, and keyword co-occurrence networks, whereas content analysis identified five key topics of contract management, supply chain management, information management, stakeholder management, and the integration of blockchain with other technologies. Research gaps and future research directions are articulated and explained within the research framework. This paper contributes to the body of knowledge by synthesizing the current state and development areas of blockchain research, which would promote the strategic adoption and use of blockchain to a greater extent in the AECO industry. [Display omitted] • Blockchain has many new applications that can improve and transform the AECO industry. • Bibliometrics and content analyses were adopted to review and analyze the blockchain development. • The research themes and future research directions are articulated in a research framework. • It contributes to the continued development and strategic adoption of blockchain in the industry. [ABSTRACT FROM AUTHOR]

In order to facilitate data analysis techniques for solving construction management (CM) problems, especially in a collaborative manner, it is essential to define the data schemas of various construction information as the common variables. However, one of the critical barriers is that there is no standard set of variables addressed for collaborative research and practice. Therefore, defining standard variable terms is essential to share, utilize, and analyze construction data systematically and efficiently. In this context, the purpose of this paper is to propose a structured set of standard CM variable terms to enable the global collective analyses of CM data, not only for human managers but also for automated machine inferences. To address this issue, firstly, bibliographic data was extracted from Scopus, focusing on CM research, and the VOSviewer was used to analyze the bibliographic information. Proposed standard variable terms were then organized into a hierarchical structure with two levels, including eight variables in the first level and fifty-seven variables in the second level. Additionally, examples of utilizing standard variable terms were presented to the traditional analytical techniques, ontology, and artificial intelligence (AI) techniques to illustrate the viability of the proposed variable terms in CM. The proposed standard variable terms can be used as the basis for further detailed taxonomy toward collective advanced analytics implementation in CM. This approach will significantly enhance automated knowledge sharing between different applications and machines, resulting in global collective intelligence among unspecified CM professionals. • Standard variable terminologies in CM were proposed. • A hypothesis for first-level variables was established and validated. • Standard variables were defined through keywords found from bibliographic data. • A comprehensive concept for collective data exchange was presented. [ABSTRACT FROM AUTHOR]

This paper reviews the state-of-the-art smart building research by a bibliometric analysis, a content analysis, and a qualitative review. The bibliometric analysis of 364 academic papers shows that smart building is a burgeoning, interdisciplinary field with a relatively high international collaboration level. Keyword's clustering identified two major themes: (1) IoT, WSN, and cloud computing for automation control and (2) the balance between energy efficiency and human comfort based on continuous monitoring and machine learning. The content analysis statistically detected a transition from the cyber-physical system (CPS) to the human-cyber-physical system (HCPS) in smart building research. We therefore proposed an HCPS framework with three dimensions—cyber-physical scale, human needs, and human roles—to summarize current research and discover potential gaps. Under this framework, five HCPS future research directions for occupants-centered smart buildings were proposed: adaptive building envelope, integrated building management system, enhanced building energy management, adaptive thermal comfort, and microgrid adoption. [Display omitted] • Conducted a bibliometric analysis of smart building research. • A statistical content analysis of 364 papers shows a transition from CPS to HCPS. • Proposed an HCPS framework to brainstorm potential research focus. • Proposed five HCPS future research directions for smart buildings. [ABSTRACT FROM AUTHOR]