Effective corporate social responsibility (CSR) implementation is essential for construction enterprises to achieve sustainable development. However, existing reviews on CSR indicators and performance measures predominantly employ a single review method or focus on non-construction sectors, with limited exploration of their interrelationships. To address this gap, this state-of-the-art review synthesizes findings from 77 relevant papers published over the past two decades in Scopus, adopting a combined methodological approach that integrates science mapping and systematic review techniques. The scientometric analysis, conducted using VOSviewer, examines annual publication trends, key journals, prominent keywords, contributing countries, and influential documents. A subsequent systematic discussion utilizing content analysis identifies seven critical CSR indicators (e.g., environmental sustainability, corporate practices, and employee well-being) and eight performance dimensions (e.g., customer satisfaction and corporate reputation). A conceptual linkage framework is developed to elucidate the relationships between these indicators and performance dimensions, highlighting the most influential CSR factors. To enhance the robustness of the findings, a post-survey interview method is employed to validate and compare the systematic discussion results, revealing several cognitive gaps between academic perspectives and industry practices. Finally, future research directions and study limitations are discussed. By integrating the mixed-review results with voices of the construction industry, this review provides an objective and holistic reference for CSR scholars in the construction sector and offers managerial and policy insights for industry stakeholders and policymakers.

Although the adoption of Internet of Things (IoTs) for green buildings (GBs) has attracted significant attention from researchers and practitioners in the construction sector, few studies have investigated the barriers to its implementation. To bridge this gap, this study aimed to identify and analyze the barriers to the adoption of IoTs in GBs through the lens of seasoned experts in the Hong Kong construction sector. A hybrid of systematic reviews, expert interviews, and social network analysis was used. The results revealed that 26 barriers impede the adoption of IoTs within GBs, and these barriers can be categorized into seven clusters. The most significant barriers include "political/regulatory" and "security" categories; and "cybersecurity and data risks," "concerns over the protection of intellectual property," "fewer GB codes/regulations available," "documentation requirements," and "uncertain government policies and absence of government support." These findings pave the way for relevant decision makers to adopt further productive measures to promote the adoption of IoT-based technologies in GBs, thereby expediting the application of the sustainability paradigm in the construction sector.

IntroductionWith rising urbanization and global climate change, sustainable city development has become an urgent challenge. Emerging mobility services provide innovative solutions for sustainable city governance, bridging the gap between transportation demand and supply, alleviating city travel and reducing carbon emissions. However, further investigation is needed to ascertain the specific roles and potential enhancements that emerging mobility services could contribute to reducing carbon emissions.MethodsIn this study, a systematic search of the Web of Science Core Collection using relevant keywords yielded 431 articles. After screening, 225 articles were deemed relevant, meeting the following criteria: (1) the articles focused on emerging mobility services, and (2) they explored the relationship between these services, carbon emissions, and environmental impacts. These articles were then synthesized using the Potential Dirichlet Allocation Model.ResultsThis study identifies four key research questions using the Potential Dirichlet Allocation Model: “Emerging Mobility’s Environmental Impacts,” “Policy-Led Sustainable Mobility Services,” “User-Centric Mobility Services,” and “Cost-Benefit Analysis of Electrification.” Assessments of the theme strengths track their evolution over time, highlighting the increasing importance of policy-led development and user-centered optimization.DiscussionThe study has shown that emerging mobility services have the potential to reduce carbon emissions; however, the extent of this impact varies by region, service type, and other factors. Policy strategies play a crucial role in promoting the development of new and emerging transport services. These findings contribute to the sustainable development of these services, the reduction of carbon emissions, and the improvement of urban living conditions.

The roofs of heritage buildings are subject to long-term degradation, resulting in poor heat insulation, heat regulation, and water leakage prevention. Researchers have predominantly employed feature-based traditional machine learning methods or individual deep learning techniques for the detection of natural deterioration and human-made damage on the surfaces of heritage building roofs for preservation. Despite their success, balancing accuracy, efficiency, timeliness, and cost remains a challenge, hindering practical application. The paper proposes an integrated method that employs a convolutional autoencoder, thresholding techniques, and a residual network to automatically detect anomalies on heritage roof surfaces. Firstly, unmanned aerial vehicles (UAVs) were employed to collect the image data of the heritage building roofs. Subsequently, an artificial intelligence (AI)-based system was developed to detect, extract, and classify anomalies on heritage roof surfaces by integrating a convolutional autoencoder, threshold techniques, and residual networks (ResNets). A heritage building project was selected as a case study. The experiments demonstrate that the proposed approach improved the detection accuracy and efficiency when compared with a single detection method. The proposed method addresses certain limitations of existing approaches, especially the reliance on extensive data labeling. It is anticipated that this approach will provide a basis for the formulation of repair schemes and timely maintenance for preventive conservation, enhancing the actual benefits of heritage building restoration.

The integration and impact of artificial intelligence (AI) and cloud computing (CC) technology in the construction industry (CI) would support their implementation process and adoption. However, there is a lack of research in the extant literature, and recent advances in this field have not been explored. As such, the key research question focuses on the extent of existing literature, main research hotspots, and recent advances (i.e., research gaps and future directions) in AI in CC in the CI. To address this research question, this study aims to conduct a state-of-the-art review of AI in CC in the CI by providing a qualitative discussion of the main research hotspots, research gaps, and future research directions. This review study used a four-step bibliometric-systematic review approach consisting of literature search, literature screening, science mapping analysis, and qualitative dis-cussion. The results found four main research hotspots, namely (1) construction project performance indicators, (2) data analysis and visualization, (3) construction quality control and safety, and (4) construction energy efficiency. These findings would provide valuable insights for scholars and practitioners seeking to understand and integrate AI and CC technology applications in the CI. This review study will lay a better foundation for future developments in construction project management processes, data-sharing protocols, real-time safety monitoring, and ethical implications of AI and CC technologies.

Introduction: Prolonged operation of construction equipment could lead to mental fatigue, which can increase the chances of human error-related accidents as well as operators’ ill-health. The objective detection of operators' mental fatigue is crucial for reducing accident risk and ensuring operator health. Electroencephalography, photoplethysmography, electrodermal activity, and eye-tracking technology have been used to mitigate this issue. These technologies are invasive and wearable sensors that can cause irritation and discomfort. Geometric measurements of facial features can serve as a noninvasive alternative approach. Its application in detecting mental fatigue of construction equipment operators has not been reported in the literature. Although the application of facial features has been widespread in other domains, such as drivers and other occupation scenarios, their ecological validity for construction excavator operators remains a knowledge gap. Method: This study proposed employing geometric measurements of facial features to detect mental fatigue in construction equipment operators' facial features. In this study, seventeen operators performed excavation operations. Mental fatigue was labeled subjectively and objectively using NASA-TLX scores and EDA values. Based on geometric measurements, facial features (eyebrow, mouth outer, mouth corners, head motion, eye area, and face area) were extracted. Results: The results showed that there was significant difference in the measured metrics for high fatigue compared to low fatigue. Specifically, the most noteworthy variation was for the eye and face area metrics, with mean differences of 45.88% and 26.9%, respectively. Conclusions: The findings showed that geometrical measurements of facial features are a useful, noninvasive approach for detecting the mental fatigue of construction equipment operators.

Polyimide foams (PIFs), renowned as some of the best materials for excellent performance in harsh temperature environments, have been developed to meet the increasing demands of high-tech industries. A state-of-the-art review of advanced PIFs research was conducted, covering the general research profiles and trends, institutions and scholars, major journals, research categories, and application fields through a bibliometric analysis of publications.Research on polyimide-based foam has increased approximately 30-fold over the past 40 years. One hundred forty-two research institutions from 20 countries have conducted research related to PIFs. Literature co-citation analysis reveals that the knowledge base of the PIFs research field primarily focuses on chemical synthesis foaming. This spotlight on engineering applications systematically describes the synthesis mechanisms, various typical fabrication methods, and the microstructure of PIFs. The advantages and disadvantages of this methods have been compared. Representative functions and corresponding mechanism models, which include thermal, mechanical, sensing, electromagnetic, flame retardant, oil-water separation, and other fields, have been outlined. This review offers insights into the technological development prospects and opportunities. Finally, the arduous tasks and challenges of PIFs research are summarized, providing valuable guidance for researchers interested in this field.

Purpose Design for safety (DfS), also known as prevention through design (PtD), is a concept that mitigates accidents and hazards through considerations during the design stage of building projects. The literature provides much information on this concept, but such information is only limited to a few developed countries such as the UK, the USA and Australia. There is limited insight into DfS implementation in the construction industry of several countries, including countries in the Gulf Cooperation Council (GCC) such as Kuwait. Therefore, this study investigates DfS implementation among design professionals in the Kuwait construction industry. Design/methodology/approach The study used a questionnaire survey to obtain data from design professionals. The data were analysed using descriptive and inferential statistics (i.e. analysis of variance and t -test). Findings The results revealed that DfS awareness among design professionals is very high; there is a very high willingness among design professionals to apply the concept, and design professionals generally view DfS implementation as important. Despite these, the frequency of implementation of DfS practices is generally moderate. In addition, the results revealed that though there is a high interest in DfS training among the design professionals, their actual engagement in training is low. The results also suggest some association between the frequency of engagement in the DfS practices and designers' DfS awareness, training and education. DfS related regulations, industry guidance, formal education and training are considered by design professionals to have the greatest influence on DfS implementation in Kuwait. Originality/Value These emerging findings both mirror and contradict aspects of the outcomes of previous DfS studies in other countries. Furthermore, the findings from this study provide insights into a less investigated area regarding work-related health and safety in the GCC region. It offers new and additional information and insights into the current state-of-the-art DfS implementation in the construction industry in Kuwait. In view of the findings, joined-up efforts by government, industry and academia are needed to enhance DfS implementation by design professionals in Kuwait.

Purpose The impact of building information modeling (BIM) on various aspects of project management has attracted much attention in the past decade. However, previous studies have focused on a particular facet of project management (e.g., safety, quality, facility management) and within identified target journals. Despite numerous existing studies, there is limited research on the mainstream research topics, gaps and future research directions on BIM in project management. This study aims to conduct a bibliometric and science mapping review of published articles on BIM in project management and to identify mainstream research topics, research gaps and future research directions in this domain. Design/methodology/approach A science mapping approach consisting of bibliometric search, scientometric analysis and qualitative discussion was used to analyze 521 journal articles that were retrieved from the Scopus database and related to BIM in project management. In the scientometric analysis, keyword co-occurrence analysis and document analysis were performed. This was followed by a qualitative discussion that seeks to propose a framework summarizing the interconnection between the mainstream research topics, research gaps and future research directions. Findings Six mainstream research topics were found including (1) BIM-enabled advanced digital technologies, (2) BIM-based reinforcement and enhancement, (3) BIM and project composition, (4) BIM project elements and attributes, (5) BIM-based collaboration and communication and (6) BIM-based information and data. Moreover, this study discussed six research gaps, namely, (1) integration of BIM and other digital technologies, (2) future maturity of BIM applications in project management, (3) application of BIM in project components and processes, (4) role of BIM application in project elements and attributes, (5) impact of collaboration and communication in BIM application and (6) stability of information and data interaction. Furthermore, future research directions were discussed. Originality/value The findings and proposed framework contribute to providing a deeper understanding to researchers, policymakers and practitioners in the development of related research and practice in the domain of BIM in project management, thus, promoting digital transformation in project management. Overall, it adds to the global knowledge domain in BIM and promotes the need for digital and data integration, BIM maturity and BIM collaboration.

Building Information Modelling (BIM) has emerged as a transformative force in the construction industry, gaining traction within the hydropower sector. This study critically examines the adoption and application of BIM throughout the entire lifecycle of hydropower projects, addressing a notable gap in existing research, to encompass a holistic approach to the management and resilience of these critical infrastructures. The objective is to delineate the comprehensive range of BIM applications, use cases, and adoption, integrating technologies including Digital Twin, UAV, GIS, and simulation tools, across components of hydropower projects. Employing a systematic search paired with a critical review of the selected literature, this study meticulously evaluates significant contributions in this domain. Through thematic analysis, the multifaceted utility of BIM in hydropower structures, including an in-depth evaluation of its current adoption within the industry, is presented. This encompasses an analysis of both benefits and challenges inherent in BIM implementation for hydropower infrastructures. This study is a significant contribution to understanding how BIM can be leveraged to enhance the resilience of hydropower infrastructures. It provides a comprehensive view of BIM’s applications, challenges, and future potential, guiding stakeholders in adopting strategies that ensure these structures withstand, adapt, and recover from disruptions while maintaining sustainable and efficient operations.

China officially entered the aging society in 2000, witnessing a rapid surge in demand for senior care services. In response, the real estate industry introduced the concept of Continuing Care Retirement Communities (CCRCs). The relationship between this model and complex risks in urban security resilience encompasses various factors, including filial care, demand for senior care, and urban sustainable development. The strategic layout and planning of CCRC enhance the security resilience of urban operational systems in the face of intricate senior care risks. However, the development and operation of CCRCs have encountered the challenge of sluggish project progress, primarily due to a lack of robust purchase intention. This study investigates the factors influencing the purchase intention of CCRCs in mainland China, using the Theory of Planned Behavior (TPB) as the foundational theoretical model. Additionally, three contextual constructs (economic cost, product performance, and external stimuli) were introduced to form the initial model. Based on the initial model, six factors were identified and nine hypotheses were proposed. A questionnaire survey was conducted to collect data, and Structural Equation Modeling (SEM) analysis was employed to test the proposed hypotheses. The results indicate that consumers’ purchase intention of CCRCs is primarily influenced by product performance and subjective norms, followed by economic cost. At the same time, external stimuli have a significant indirect effect on it.

Purpose The relationships between transformational leadership (TL), organizational climate (OC) and project performance have been investigated by previous studies, but no review of existing studies has systematically analyzed the effects of TL and OC on project performance in the industrial revolution (IR) 5.0 era. Therefore, this study aims to conduct a systematic literature review on the effects of TL and OC on project performance in IR 5.0, and to identify mainstream research topics, research gaps and future research directions. Design/methodology/approach To do this, a total of 53 included journal articles were obtained after initially retrieving 648 documents from the Scopus database by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. It consists of four main steps, namely, identification of documents, screening, eligibility and included articles. In addition, science mapping analyses were conducted for keyword co-occurrence and document analyses, which aided in identifying the mainstream research topics, research gaps and future research directions. Findings The results report the annual publication trends, keywords and document analyses. Furthermore, a detailed qualitative discussion highlighted four mainstream research topics including TL in project management; the relationship between TL, OC and innovation; safety climate; and OC in project management. Moreover, this review study identified four research gaps and future research directions aligned with the mainstream research topics. They include: longitudinal investigations and multinational corporation surveys in TL; scope and longitudinal data in innovation; mono-method bias and universality of safety climate; and more comprehensive analyses of OC. Originality/value This review study would contribute to not only advancing the effects of TL and OC on project performance in IR 5.0, but also enabling project managers to understand TL or OC issues to improve project performance.

Wearable sensing devices (WSDs) have enormous promise for monitoring construction worker safety. They can track workers and send safety-related information in real time, allowing for more effective and preventative decision making. WSDs are particularly useful on construction sites since they can track workers' health, safety, and activity levels, among other metrics that could help optimize their daily tasks. WSDs may also assist workers in recognizing health-related safety risks (such as physical fatigue) and taking appropriate action to mitigate them. The data produced by these WSDs, however, is highly noisy and contaminated with artifacts that could have been introduced by the surroundings, the experimental apparatus, or the subject's physiological state. These artifacts are very strong and frequently found during field experiments. So, when there is a lot of artifacts, the signal quality drops. Recently, artifacts removal has been greatly enhanced by developments in signal processing, which has vastly enhanced the performance. Thus, the proposed review aimed to provide an in-depth analysis of the approaches currently used to analyze data and remove artifacts from physiological signals obtained via WSDs during construction-related tasks. First, this study provides an overview of the physiological signals that are likely to be recorded from construction workers to monitor their health and safety. Second, this review identifies the most prevalent artifacts that have the most detrimental effect on the utility of the signals. Third, a comprehensive review of existing artifact-removal approaches were presented. Fourth, each identified artifact detection and removal approach was analyzed for its strengths and weaknesses. Finally, in conclusion, this review provides a few suggestions for future research for improving the quality of captured physiological signals for monitoring the health and safety of construction workers using artifact removal approaches.

PurposeThis study underscores the critical importance of well-functioning sewer systems in achieving smart and sustainable urban drainage within cities. It specifically targets the pressing issue of sewer overflows (SO), widely recognized for their detrimental impact on the environment and public health. The primary purpose of this research is to bridge significant research gaps by investigating the root causes of SO incidents and comprehending their broader ecological consequences.Design/methodology/approachTo fill research gaps, the study introduces the Multi-Phase Causal Inference Fuzzy-Based Framework (MCIF). MCIF integrates the fuzzy Delphi technique, fuzzy DEMATEL method, fuzzy TOPSIS technique and expert interviews. Drawing on expertise from developed countries, MCIF systematically identifies and prioritizes SO causes, explores causal interrelationships, prioritizes environmental impacts and compiles mitigation strategies.FindingsThe study's findings are multifaceted and substantially contribute to addressing SO challenges. Utilizing the MCIF, the research effectively identifies and prioritizes causal factors behind SO incidents, highlighting their relative significance. Additionally, it unravels intricate causal relationships among key factors such as blockages, flow velocity, infiltration and inflow, under-designed pipe diameter and pipe deformation, holes or collapse, providing a profound insight into the intricate web of influences leading to SO.Originality/valueThis study introduces originality by presenting the innovative MCIF tailored for SO mitigation. The combination of fuzzy techniques, expert input and holistic analysis enriches the existing knowledge. These findings pave the way for informed decision-making and proactive measures to achieve sustainable urban drainage systems.

Natural organisms have superior material properties such as mechanical adaptability, impact protection, and self-healing to protect the body from complicated external environments, fascinating the development of functional supramolecular elastic materials with biomimetic protective features. Herein, a dual physically crosslinked supramolecular polyurethane (PU) network with strain-hardening effect is synthesized by incorporating hierarchical hydrogen bonds (H-bond) and metal coordination bonds into an elastomer matrix. A moderate content of quadruple H-bonds is critical for achieving a prominent toughness and a considerable strain-at-break owing to the strain hardening effect enabled by the hierarchical H-bonds. When the Zn-to-pyridine coordination bonds were introduced to the supramolecular PU, the strength, toughness, and energy dissipation properties were further enhanced attributing to the dual physical crosslinking networks. The dynamic dissociation and association of the sacrificial H-bonds and Zn-to-pyridine coordination bonds induced significant strain hardening effect and enabled tremendous energy absorption and self-healing properties. Besides, the supramolecular PU elastomers and their blends were foamed via scCO2 foaming to produce supramolecular foams containing dynamic bonds. The composite foam could effectively reduce the impact force from 6085 N to 373 N and achieve an outstanding energy absorption efficiency of 93.87% owing to the synergistic effect of porous structure and dual physically crosslinked networks. This work provides an innovative strategy for designing high-performance energy absorbing supramolecular elastomers and cushioning foams with reversible bonds.

Purpose - The impact of building information modeling (BIM) on various aspects of project management has attracted much attention in the past decade. However, previous studies have focused on a particular facet of project management (e.g., safety, quality, facility management) and within identified target journals. Despite numerous existing studies, there is limited research on the mainstream research topics, gaps and future research directions on BIM in project management. This study aims to conduct a bibliometric and science mapping review of published articles on BIM in project management and to identify mainstream research topics, research gaps and future research directions in this domain. Design/methodology/approach - A science mapping approach consisting of bibliometric search, scientometric analysis and qualitative discussion was used to analyze 521 journal articles that were retrieved from the Scopus database and related to BIM in project management. In the scientometric analysis, keyword co-occurrence analysis and document analysis were performed. This was followed by a qualitative discussion that seeks to propose a framework summarizing the interconnection between the mainstream research topics, research gaps and future research directions. Findings - Six mainstream research topics were found including (1) BIM-enabled advanced digital technologies, (2) BIM-based reinforcement and enhancement, (3) BIM and project composition, (4) BIM project elements and attributes, (5) BIM-based collaboration and communication and (6) BIM-based information and data. Moreover, this study discussed six research gaps, namely, (1) integration of BIM and other digital technologies, (2) future maturity of BIM applications in project management, (3) application of BIM in project components and processes, (4) role of BIM application in project elements and attributes, (5) impact of collaboration and communication in BIM application and (6) stability of information and data interaction. Furthermore, future research directions were discussed. Originality/value - The findings and proposed framework contribute to providing a deeper understanding to researchers, policymakers and practitioners in the development of related research and practice in the domain of BIM in project management, thus, promoting digital transformation in project management. Overall, it adds to the global knowledge domain in BIM and promotes the need for digital and data integration, BIM maturity and BIM collaboration.

Offline programming (OLP) is a mainstream approach for controlling assembly robots at construction sites. However, existing methods are tailored to specific assembly tasks and workflows, and thus lack flexibility. Additionally, the emerging large language model (LLM)-based OLP cannot effectively handle the code logic of robot programming. Thus, this paper addresses the question: How can robot control programs be generated effectively and accurately for diverse construction assembly tasks using LLM techniques? This paper describes a closed user-on-the-loop control framework for construction assembly robots based on LLM techniques. A hierarchical strategy to generate robot control programs is proposed to logically integrate code generation at high and low levels. Additionally, customized application programming interfaces and a chain of action are combined to enhance the LLM's understanding of assembly action logic. An assembly task set was designed to evaluate the feasibility and reliability of the proposed approach. The results show that the proposed approach (1) is widely applicable to diverse assembly tasks, and (2) can improve the quality of the generated code by decreasing the number of errors. Our approach facilitates the automation of construction assembly tasks by simplifying the robot control process.

By adopting a systematic literature and science mapping review, this paper aims to explore the impact of artificial intelligence (AI) on organizational justice and project performance. A total of 47 bibliographic records from the Scopus database were analyzed. The results revealed the annual publication trends of research articles and relevant peer-reviewed journals in the studied domain. It was found that while AI technology has made significant progress in several fields, its application areas in project management and organizational justice are still relatively low. Moreover, it objectively discussed the co-occurrence analysis of keywords, co-authors, countries/regions, and documents in the fields, revealing the current research topics. The main research topics include the (1) AI’s influence on organizational justice, decision analysis, and digital transformation, (2) fostering organizational justice and AI’s role in enhancing project performance, and (3) improving organizational performance approaches. Furthermore, this paper proposed research gaps and future research directions, including (1) advancing business intelligence strategies, (2) unlocking AI technology potential on organizational justice and project performance, (3) the adaption of cultural, diversity, environmental, and social factors, (4) the impact of AI on complex and challenging leadership styles, and (5) developing a comprehensive understanding of the agile framework. The findings of this paper could contribute to a better understanding of how AI shapes project/construction management and organizational justice, providing practical solutions for innovative development for researchers and policymakers.

The development of prefabricated construction in China started relatively late, and the high cost of prefabricated housing has resulted in generally low enthusiasm among stakeholders in the market. Compared to other developed countries, the market penetration rate of prefabricated housing in China is relatively low. The current trajectory of prefabricated housing development in China is primarily influenced by the initiatives and support from key market stakeholders, underscoring the need for a concerted effort to enhance the sector’s growth and sustainability. Existing research on the influencing factors of prefabricated housing promotion mainly focuses on macro perspectives, such as the market, economy, technology, and policies. However, there is a lack of scholarly studies that specifically examine the promotion factors from the stakeholders’ perspective. However, there is a notable scarcity of scholarly work that delves into the promotion of prefabricated housing from the vantage point of the stakeholders involved. This paper defines the core stakeholders in the prefabricated housing market, including the government, developers, design units, supply units, construction units, and consumers, based on literature research, project surveys, and expert interviews. Furthermore, a preliminary list of 20 factors that influence the adoption of prefabricated housing by stakeholders has been determined. Using social network analysis, the study identifies 17 key influencing factors, interaction relationships, and influence paths for promoting prefabricated housing. Based on these key influencing factors, the study proposes promotion measures from the perspectives of the government, developers, and collaborating enterprises. The study’s results reveal 17 key influencing factors, interaction relationships, and influence paths for the promotion of prefabricated housing. Among these factors, developer willingness, developer investment costs, industry chain completeness, developer strategic goals, and competitive pressures on participating units are identified as the most critical factors within the network of relationships. The research findings of this paper aim to provide theoretical support for promoting prefabricated housing from the perspective of stakeholders.