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The adoption rate of new technologies is still relatively low in the construction industry, particularly for mitigating occupational safety and health (OSH) risks, which is traditionally a largely labor-intensive activity in developing countries, occupying ill-afforded non-productive management resources. However, understanding why this is the case is a relatively unresearched area in developing countries such as Malaysia. In aiming to help redress this situation, this study explored the major barriers involved, firstly by a detailed literature review to identify the main barriers hampering the adoption of new technologies for safety science and management in construction. Then, a questionnaire survey of Malaysian construction practitioners was used to prioritize these barriers. A factor analysis further identified six major dimensions underlying the barriers, relating to the lack of OSH regulations and legislation, technological limitations, lack of genuine organizational commitment, prohibitive costs, poor safety culture within the construction industry, and privacy and data security concerns. Taken together, the findings provide a valuable reference to assist industry practitioners and researchers regarding the critical barriers to the adoption of new technologies for construction safety management in Malaysia and other similar developing countries, and bridge the identified knowledge gap concerning the dimensionality of the barriers.

This paper presents the first inclusive scientometric review of the economic areas of green building (GBE). The aim is to methodically examine and summarize the state-of-the-art of the GBE body of knowledge. To this end, this study analyses 1713 GBE-related bibliographic records retrieved from the Web of Science by using the quantitative method of knowledge mapping. The knowledge base, knowledge domain, and knowledge evolution of how they interacted with each other are explored using document co-citation analysis and keywords co-citation analysis of the existing body of literature. The research findings are informative in recognizing and interpreting the underlying structure and trends in GBE. A knowledge map provides a valuable and instructive understanding of the evolution and status quo of the GBE knowledge body, as well as assisting in recognizing the gaps and deficiencies involved. The results will help in understanding how GBE knowledge is evolving and its role played in green building, and thus provide suggestions of how academic research can enhance sustainability practices in terms of economic area in the future.

Construction information technology (CIT), particularly building information modeling, is globally embraced in industry but relatively new to Japanese universities because of its unique interdisciplinary nature. This presents challenges for students and instructors. Promoting the widespread adoption of CIT in Japan necessitates the development of undergraduates’ proficiency in hard and soft engineering. The problem is that Japanese universities lack research and curricula concerning CIT education—a deficiency that raises the need to evaluate students’ perceptions and acceptance of such education. This study is an initial endeavor to fulfill this need, with a view to providing curriculum recommendations and insights into the issue of interest via the analysis of students’ awareness by developing a comprehensive technology acceptance model (TAM). The findings revealed that students’ exposure to and knowledge of CIT during their university education significantly influence their perception of its utility, thereby affecting their acceptance of CIT courses. Their perception of the usefulness of CIT in future employment is a more influential factor in their willingness or readiness to accept and participate in CIT courses than its perceived importance for industry development. To facilitate the advancement of the construction sector, stakeholders should develop an industry–university collaboration-based education program that bridges the gap between academic and industry needs, creates job opportunities for students, and nurtures talent.

This paper presents a systematic literature review of the impact of emerging technologies such as Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), and gamification on student engagement, learning outcomes, and employability in Built Environment (BE) education. This review covers studies conducted between 2013 and 2023, utilizing the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) framework. From an initial pool of 626 studies, 61 were identified and rigorously analyzed. The findings reveal that these technologies significantly enhance student engagement by providing immersive and interactive learning experiences that bridge the gap between theoretical knowledge and practical application. Furthermore, their use is shown to improve learning outcomes by facilitating a deeper understanding of complex concepts and increasing student motivation. In terms of employability, the integration of digital tools into BE education equips students with the requisite skills that are increasingly demanded in the modern workplace. However, the study also identifies several challenges, including high costs, limited resources, and the need for extensive faculty training, which act as barriers to the effective implementation of these technologies. Despite these challenges, this review underscores the transformative potential of digital technologies in BE education. This study is significant as it synthesizes recent evidence to highlight the critical role of digital technologies in reshaping BE education. It offers practical recommendations for educators and policymakers to enhance teaching and learning practices. Providing pathways for integrating these technologies into BE curricula, this study aims to inform future research and pedagogical strategies, ultimately contributing to the development of a highly skilled and adaptable workforce.

Efficient measurement of labor input is a critical aspect of on-site control and management in construction projects, as labor input serves as the primary and direct determinant of project outcomes. However, conventional manual inspection methods are off-line, tedious, and fail to capture their effectiveness. To address this issue, this research presents a novel method that leverages Inertial Measurement Unit (IMU) sensors attached to hand tools during construction activities to measure labor input in a timely and precise manner. This approach encompasses three steps: temporal–spatial feature extraction, self-similarity matrix calculation, and local specific structure identification. The underlying principle is based on the hypothesis that repetitive use data from hand tools can be systematically collected, analyzed, and converted into quantitative measures of labor input by the automatic recognition of repetition patterns. To validate this concept and assess its feasibility for general construction activities, we developed a preliminary prototype and conducted a pilot study focusing on rotation counting for a screw-connection task. A comparative analysis between the ground truth and the predicted results obtained from the experiments demonstrates the effectiveness and efficiency of measuring labor input using IMU sensors on hand tools, with a relative error of less than 5%. To minimize the measurement error, further work is currently underway for accurate activity segmentation and fast feature extraction, enabling deeper insights into on-site construction behaviors.

This paper examines major railroad projects’ emergency response decision-making process, focusing on timeliness, cost-effectiveness, and public involvement. It explores the optimal collaborative strategies of local governments, enterprises, and the public during the construction phase. A novel tripartite decision-making framework is proposed, based on an asymmetric evolutionary game model and dynamic simulation methods. The results show a stable equilibrium in emergency response strategies emerges when public engagement is prioritized. Government subsidy policies are found to significantly influence the strategic choices of all agents, emphasizing the critical role of coordinated collaboration. The study highlights the importance of public participation and multi-agent cooperation in addressing complex emergency challenges. These findings provide valuable guidance for improving localized emergency response strategies, enhancing collaborative decision-making, optimizing resource allocation, increasing response efficiency, and supporting policy formulation in major railroad projects.

To explore the law of megaproject social responsibility behavior (MSRB) among internal organizations under institutional pressure, this paper presents a theoretical and empirical study to investigate how institutional pressure affects MSRB through the mediating role of organizational social responsibility cognition and the mediating roles of the communication mechanism and relationship strength based on new institutional sociology. Based on a total of 147 responses from a broad questionnaire survey, structural equation modelling (SEM) was used to test the proposed hypotheses. The research results show that institutional pressure has a promoting effect on MSRB, and organizational social responsibility cognition mediates the relationship between institutional pressure and MSRB. Additionally, the communication mechanism and relationship strength have no effect on the relationship between institutional pressures and MSRB. The research results provide a new theoretical foundation for the analysis of MSRB and practical suggestions for policymakers on the governance of MSRB.

Real estate developers typically assess potential projects using feasibility analyses and industry-standard heuristics, which include capital costs, return on costs, and a subjective risk measure. This study explores real estate developers’ decision-making practices in selecting hurdle rates and common feasibility analysis techniques, surveying 225 Australian and New Zealand developers. The main findings are that most developers use specific ‘go/no-go’ hurdle rate mechanisms irrespective of primary real estate type, with the majority using margin on development cost (MDC) or internal rate of return (IRR); the boundaries between traditional speculative development and real estate investment through the use of securitization methods have become blurred; many developers use both quantitative metrics, with qualitative methods and specific structural checks to manage the risks involved; and the two most frequent methods of determining site value prior to acquisition are the residual land value and discounted cash flow methods. Most place a heavy reliance on industry-accepted heuristics and do not have a predetermined process and method for altering or adapting the chosen hurdle rates and benchmarks. This research provides a contribution to property development practice from the Antipodean perspective which until now has been more focused on the UK view, enabling more generalized application internationally.

Cost overruns are a ubiquitous feature of construction projects, and realistic budgeting at the development stage plays a significant role in their control. However, the application of existing models to budgeting for power plant projects is restricted by the limited amount of project-specific cost data available. This study overcomes this by using a Classification and Regression Tree (CART) approach involving mixed methods of website visits, document study, and expert opinion to predict the amount of project cost (PC) and cost contingency (CC) needed to cover probable cost increases by the use of models containing readily available project attributes and national economic parameters at the project development stage. The modeling process is demonstrated and tested with a case study involving 58 Bangladeshi power plant projects – producing average absolute errors ranging from 0.7% to 1.7% and enabling project cost, inflation rate, and GDP to be identified as significant factors affecting PC and CC modeling. The approach can be applied to predict the PC during preliminary budgeting and selecting a project type and location aligned to the country’s economic status and policy-making strategies, thus facilitating further investment decisions.

The construction industry, a major global employer, increasingly relies on migrant construction workers (MCWs) to mitigate labor shortages and enhance cost efficiency. Despite their vital role, MCWs face numerous challenges, including exploitation during recruitment, safety risks, health issues, and difficulties with social integration. Current research into MCWs is dispersed across various disciplines—such as occupational safety, health, and social issues—and lacks a cohesive review of achievements and gaps. To address this, the present study employs bibliometric and qualitative content analysis to evaluate research progress, domains, hotspots, and trends from 2004 to 2024. The dataset, sourced from the Web of Science (WoS), includes 112 publications. The analysis reveals a steady growth in MCWs research, divided into two distinct phases, with significant contributions from 307 authors across 30 countries. The study also examines robust international collaboration and the prominent role of influential research institutions. The research identified ten key areas of focus and engaged in discussion. This comprehensive overview of MCWs research provides valuable insights for future studies and policy development, aiming to enhance conditions for MCWs and inform effective intervention strategies for this vulnerable workforce.