During operation (especially in long-term service), the necessity arises to strengthen the reinforced concrete structures of hydraulic engineering facilities. In recent years, in industrial and civil construction, the strengthening of reinforced concrete structures using externally bonded reinforcement systems made of composite materials (for example, carbon-based) has been applied. However, in hydraulic engineering construction, such strengthening solutions are encountered only in isolated cases. The experimental studies of reinforced concrete structures of hydraulic engineering facilities strengthened with an external reinforcement system made of carbon materials, presented in the article, were carried out to substantiate the application of external reinforcement systems made of carbon-based materials (strips and laminates) for the purpose of strengthening reinforced concrete structures of this type of facilities. Keywords: composite materials, reinforced concrete models, carbon fiber strips, bending moment, external reinforcement system, carbon-based materials, strength, strengthening of structures.

This paper develops a practical framework for implementing circular business models (CBMs) in the design and planning phases of the construction industry. By synthesizing circular economy literature, industry case studies, and a survey of sector stakeholders, the study shows how modular construction, reclaimed materials, and service-based models can optimize resource efficiency and minimize waste throughout the built environment lifecycle. The framework features actionable tools such as material flow mapping and a circular economy model canvas to facilitate stakeholder collaboration and embed circularity at the earliest project stages. Results reveal substantial barriers to CBM adoption, including policy gaps, investment needs, and limited technical expertise, but highlight major potential for reducing environmental impacts, enhancing economic resilience, and aligning with global sustainability goals. The research concludes with recommendations for policy support, skill development, and future investigation into digital solutions, providing guidance for professionals aiming to drive sustainable transformation in construction.

Green procurement (GP) is increasingly recognized as a strategic mechanism for embedding sustainability within the construction industry (CI), yet its adoption in developing economies remains inconsistent and uneven. This study investigates the key drivers shaping GP adoption in Malaysia’s CI and uncovers the underlying factors that explain variations in stakeholder behaviour. Drawing on Institutional Theory (IT) and the Resource-Based View (RBV), twenty-one GP drivers were identified through a comprehensive literature review and evaluated using a structured questionnaire administered to developers, consultants, and contractors. Quantitative analyses—including descriptive statistics, Kruskal–Wallis tests, and exploratory factor analysis (EFA)—revealed four interrelated dimensions: Institutional and Strategic Support, Market and Business Competitiveness, Availability of Green Resources and Infrastructure, and Stakeholder Engagement and Social Responsibility. These dimensions form the basis of the Integrated Institutional–Capability Framework for Green Procurement (IICF-GP), which explains how external institutional pressures interact with internal organizational capabilities to influence both strategic intent and operational implementation of GP. The framework contributes theoretically by integrating IT and RBV within a single empirically grounded explanatory model, and practically by identifying targeted policy, capability-building, and supply-chain levers. Findings underscore that regulatory clarity, supplier readiness, technological capability, and stakeholder collaboration are critical to advancing GP in developing-country construction contexts.

The relevance of the work. In the 21st century, humanity has faced global challenges, among which the issues of environmental degradation, depletion of natural resources and climate change have become particularly acute. Against this background, the traditional linear economic model, which involves excessive use of resources and the generation of a large amount of waste, has exhausted its potential. This is especially critical in the construction industry ‒ one of the most resource-intensive sectors of the world economy. In response to the challenges of modernity, more and more attention is paid to the concept of a circular economy, which allows creating closed production cycles, reducing the burden on the environment. In the context of restoring Ukraine's infrastructure after the war, the relevance of the transition to a circular construction model is growing exponentially. Purpose. The purpose of the article is to comprehensively analyze the possibilities and limitations of implementing a circular economy in the construction industry as a tool for implementing the principles of sustainable development. The research is aimed at studying theoretical foundations, practical experience, international cases, innovative materials and technologies that can transform approaches to the design, construction and operation of facilities. Methodology. The article uses an interdisciplinary approach that combines the concepts of ecological economics, urbanism, architecture, and systems analysis. A comparative analysis of linear and circular economic models is conducted, and examples of successful implementation of circular practices in construction in different countries, including Germany, Great Britain, the Scandinavian countries, and Japan, are studied. Statistical data on material consumption, energy costs, and waste generation in the construction sector are used. Special attention is paid to the analysis of regulatory, institutional, and behavioral barriers to circularity in Ukraine. The results. The author proves that the circular economy is not only an environmentally sound, but also an economically profitable strategy for construction. The use of secondary materials, organic insulation, energy-efficient technologies, and local raw materials allows for a reduction in carbon footprint, reduced waste disposal costs, and improved quality of the living environment. Key barriers to the implementation of a circular approach in Ukraine are identified – from the lack of a regulatory framework to the low level of environmental culture. At the same time, the country’s potential in implementing relevant solutions is highlighted, especially in the context of post-war reconstruction. The article calls for a revision of the paradigm of construction as a technical process and its transformation into a worldview model based on long-term responsibility to society, nature and future generations.

Abstract. In recent years, three-dimensional (3D) printing technology has emerged as a significant innovation in the construction industry, aligning with sustainability goals. As one of the key components of Industry 4.0, this technology offers advantages such as design flexibility, material efficiency, and reduced environmental impact. 3D printing (3DP) technology stands out as an innovative production method that supports sustainability goals within the context of smart cities. In order to evaluate the role of 3DP in sustainable construction practices, this study examines 100 publications in the Web of Science database through bibliometric analysis. 29% of the analyzed publications were published in 2024, which stands out as the year with the highest production in the literature. The majority of the publications are concentrated in the fields of engineering and building technologies. In addition, 72% of the 40 articles analyzed are research articles, and 75% are laboratory-based studies. The types of materials used in the studies show a significant diversity. In addition to traditional concrete, innovative and environmentally friendly alternatives such as recycled aggregates, fly ash, geopolymers, biobased fibres, salt-sand mixtures, high-density polymers and self-healing materials are used. This diversity demonstrates the potential that 3DP offers in terms of reducing environmental impacts, limiting waste generation and utilizing local resources. The study identifies trends in the literature and future research areas to strengthen the use of this technology in sustainable construction.

Abstract Clinker-reduced cements are gaining in popularity as part of efforts to lower the construction industry’s CO 2 footprint. Past studies showed that utilization of these cements negatively influences the fire-induced spalling behavior of concrete, which is highly influenced by thermohydraulic damage mechanisms. Therefore, thermally induced moisture transport in normal strength concretes made with different types of blended cements (CEM I, CEM II/A-LL, CEM III/A and CEM II/B-Q) was investigated by means of 1 H-NMR relaxometry in combination with supportive side investigations concerning permeability and porosity. In addition, a numerical model was used to analyze in-situ moisture development during high temperature exposure. The results show that the cement type influences both initial moisture content and pore size-specific moisture distribution. This was primarily reflected in an increased water content in CEM III/A and CEM II/B-Q concretes as well as a comparable high gel pore water fraction in CEM II/B-Q concrete before heating. After heating, a similar degree of pore coarsening from gel to capillary pore was observed in all samples. Although the measurements were only conducted after, not during, high temperature exposure, the depth of the drying front and the extent of the moisture clog could be determined. With the additional numerical analysis, it can be assumed that during high temperature load, the drying front is less advanced and the moisture clog even more pronounced. In conclusion, it can be stated that the increased spalling susceptibility in blended cement concrete is caused by the lower initial permeability and increased moisture content.

Abstract:From the perspective of engineering economic benefits and BIM technology application, this paper studies the application effect of intelligent engineering concept, constructs a coupling and coordination model of industrial engineering construction quality control, and conducts an empirical study on the application data of industrial engineering. According to the research and analysis, the concept of smart engineering has a promoting effect on the application of BIM technology in the quality control of industrial engineering buildings, and the balance of promotion is significantly improved, with an increase of 20~40%. At the same time, the construction quality control rate is always above 90%, and the reduction rate of engineering construction costs is about 15%. Therefore, the role of the smart engineering concept allows BIM to maintain a positive relationship between BIM and industrial engineering construction quality control, improve the wisdom of the construction process, construction plan application and construction result evaluation, and realize the purpose of green and low-carbon construction, energy conservation and environmental protection construction, and strengthen project quality. Keywords: smart engineering concept; BIM technology; industrial engineering; architecture; Quality control

Identifying Factors Influencing Mental Health Issues among Female Practitioners in the Construction Industry: Systematic Literature Review

This research examines external environmental factors and risk management practices to explore how they affect resilience and success in construction projects in Ethiopia's fast-developing construction industry, using quantitative surveys of 192 professionals and modelling techniques. The research adopted an integrated research methodology of Partial Least Squares Structural Equation Modelling (PLS-SEM), Importance-Performance Map Analysis (IPMA), and descriptive statistics to systematically analyse/assess the complexities between the external environment, risk management practices, resilience, and project success. It is found that external risks, as exemplified by low inflation, economic stability and legal certainty, favour resilience and then project success. Similarly, in line with effective risk management practices such as communication, knowledge and integration of risk management and resource allocation help increase resilience. The research provides a contribution by identifying the significance and relevance of best practices to buffer the effects of external shocks and improve risk management practices, as well as be resilient to develop sustainably in the construction industry in Ethiopia.

The predictors of turnover intention among construction managers in the U.S. are examined. This article uses a quantitative correlational multiple linear regression to examine the relationships among construction managers’ job uncertainty, complexity, variety, interdependence, job satisfaction, and turnover intent in the United States. Previous studies have shown that turnover intent rates continue to reach new highs, with no signs of slowing in the U.S. and many other countries. Although researchers have recognized the importance of turnover intent, job uncertainty, complexity, variety, interdependence, and job satisfaction individually, their combined effects remain under-investigated. Therefore, this quantitative study aims to identify predictors of potential turnover intent among managers in the United States construction industry. The empirical findings highlight the moderate predictive relationship between job satisfaction and turnover intent, suggesting that improving job satisfaction may help reduce turnover intentions. However, the factors of job uncertainty, complexity, variety, and interdependence were not statistically significant predictors of turnover intent. These findings align with the push-pull-mooring theory, which explains most migration behaviors, and, alternatively, the two-factor theory, which explains that executive managers must establish a link between essential hygiene and motivator factors. This study contributes to understanding the importance of construction companies’ specific needs and perceptions. Finally, the study invests in measures to promote job satisfaction and retention to mitigate the challenges posed by high turnover rates in the industry

Competency Expectations for Sensing Technologies in the Construction Industry: A Comparative Study of Academia and Industry Perceptions

Construction case-relevant article-level law identification using fine-tuned large language models: A study in China’s construction industry

The synergy benefits and drivers of pollution and carbon reductions from solid waste resource utilization in China.

The construction industry worldwide is experiencing a paradigm shift due to the impact of digitalisation, BIM, AI, IoT, automation, cloud computing, etc. This revolutionises the planning, coordination, and construction approaches currently employed across projects. Nevertheless, India faces challenges, such as fragmented workflows, that may hinder the workforce's ability to fully adapt to the digital revolution. This paper provides an overview of the competencies required in project management in India, in the context of Digitalisation, as opposed to those of the construction industry, and across sectors such as IT, manufacturing, and logistics, which are among the most digitally advanced. A systematic analysis of the available data has identified five distinct areas. These areas are Digital technical competency, Governance competency, digitally enabled project management competency, Behavioural interpersonal competency, and Strategic leadership competency. This study presents a Competency Framework and an Implementation Plan to address the project management industry in India. These findings are significant given the notable shift in the construction industry in India, which is dependent on workforce competency and the establishment of necessary leadership.

The construction industry has a high level of occupational accident risk, making the implementation of an Occupational Safety and Health Management System (OSHMS) essential in construction projects. This study aims to evaluate the implementation of OSHMS in the construction project of the Pamulang University Campus Building and to identify potential hazards, risk levels, and risk control measures applied on site. This research employed a quantitative descriptive method, collecting data through field observations, interviews, and questionnaires distributed to 55 respondents directly involved in the project. Data analysis was conducted using SPSS to test the validity and reliability of the questionnaire, while the HIRARC method was used for hazard identification, risk assessment, and risk control. The results indicate that all questionnaire items were valid and reliable, with Cronbach’s Alpha values of 0.842 for the likelihood variable and 0.818 for the severity variable. The evaluation of OSHMS implementation achieved an average score of 4.07, categorized as good. The highest risk was identified in upper structural work, particularly the hazard of falling from height. It can be concluded that the implementation of OSHMS in the project has been carried out effectively; however, improvements in supervision and worker compliance are still required to further reduce occupational accident risks

This paper explores the role of blockchain technology in reducing information asymmetry and improving trust in the context of circular construction. In the construction industry, especially when applying circular economy principles, many stakeholders suffer from lack of transparency and poor data sharing. This often causes mistrust and inefficient collaboration. Blockchain, as a decentralized and secure technology, can solve this problem by creating transparent, traceable, and immutable records of material flows, contracts, and processes. However, there is a lack of scientific evidence in understanding the blockchain’s role in building trust and reducing information asymmetry in circular construction. This study reviews recent literature where the blockchain is applied to circular construction, finds the current gaps, and proposes future directions for research on this topic. It identifies critical technical, organizational, and legal barriers while outlining a clear pathway for overcoming them. By addressing these challenges, the blockchain can evolve into a central enabler of circular, sustainable, and trustworthy construction, offering a decisive reference point for guiding adoption, standardization, and industry-wide implementation.

To solve the problem of conflicting objectives in project management in the construction industry and comply with China’s energy-saving and carbon reduction policies in the construction industry, this study introduces carbon emission conditions into a multi-objective model and designs an optimization model for project duration cost quality resources. On the basis of the mixed shuffled frog leaping algorithm, this study applies an improved encoding method, a target anchoring mixed initialization operator based on heuristic information, a design constraint handling operator, discrete jumping optimization rules, and local mining of individuals in external memory for mixing and optimization, to obtain the final multi-objective optimization solution method. The research results indicated that after the performance dimension was improved, the research method could still maintain stable and superior performance. The average fitness values of the f1 function and f2 function correspond to 1.81 · 101 and 1.81 · 101, respectively. In practical engineering project management applications, compared with the mainstream mixed frog leaping algorithm based on multi-population improved firefly algorithm, the research method obtained a total project duration that was 20 days less and a total cost that was $13125 less. Only the quality level and resource balance index were slightly inferior, with decibels of 0.93% and 49. The results indicate that the research method can quickly and effectively solve multiple solutions, enhance the competitiveness of enterprises in the construction industry, and promote the green development of the construction industry.

The construction industry is increasingly exploring alternatives to natural aggregates, driven by sustainability concerns and landfill waste reduction. Blast furnace slag, a byproduct of steel manufacturing, exemplifies this shift, serving as a substitute aggregate or concrete additive. This transition supports the circular economy principle, where yesterday’s waste transforms into today’s resources. Key to this practice is the precise determination of material parameters, which vary depending on their origin. Among these, the filtration coefficient is critical, affecting the performance of anthropogenic aggregates in construction and infrastructure. It indicates how well materials transmit water, a factor vital for structural integrity. Machine Learning (ML) presents a promising tool for estimating such parameters efficiently. This paper explores various ML techniques for predicting the filtration coefficient, comparing their effectiveness and examining the impact of the physical properties of aggregates on model accuracy. Through this approach, the paper aims to identify the most suitable methods for parameter estimation, which could enhance the durability and stability of constructions that utilize recycled materials. This research not only contributes to the field of civil engineering but also advances sustainable practices within the industry.

Cost overrun is a major challenge in the construction industry. However, there is a notable lack of data from imperial studies that exhaustively identify and analyze risk factors contributing to overruns. This study aims to address this gap by systematically identifying and analyzing these risk factors. A hybrid methodology was employed. It combined a systematic literature review, a three-round Delphi process, and fuzzy set techniques. Insights from the literature review informed the first-round Delphi questionnaire. Subsequent rounds were refined based on earlier results. In the third round, experts’ opinions on the likelihood and impact of the cost risk factors were collected using a 5-point Likert scale. Finally, a fuzzy approach was employed to assess the severity of cost risk factors based on the combined effects of their likelihood and impact. The results revealed that the primary cost risk factors include escalation and fluctuation in material prices, inflation, material shortages, the country’s political instability, the country’s economic instability, delays in payment to the contractor, and delays in material procurement and delivery. Notably, the significant cost risk factors are largely beyond the contractor’s control and are closely tied to the broader political and economic conditions of the country.

The assessment of Industrialized Building System (IBS) adoption in construction projects—a critical metric for evaluating prefabrication levels and construction modernization—remains largely manual, time-intensive, and prone to inconsistencies, with practitioners typically requiring 4–8 h to evaluate a single building using spreadsheet-based frameworks and visual documentation review. This paper presents a novel AI-enhanced workflow architecture that automates IBS scoring through systematic processing of Industry Foundation Classes (IFC) building information models—the first documented integration of web-based IFC processing, visual workflow automation (n8n), and large language model (LLM) reasoning specifically for construction industrialization assessment. The proposed system integrates a web-based frontend for IFC file upload and configuration, an n8n workflow automation backend orchestrating data transformation pipelines, and an Azure OpenAI-powered scoring engine (GPT-4o-mini and GPT-5-0-mini) that applies Construction Industry Standard (CIS) 18:2023 rules to extracted building data. Experimental validation across 136 diverse IFC building models (ranging from 0.01 MB to 136.26 MB) achieved a 100% processing success rate with a median processing duration of 61.62 s per model, representing approximately 99% time reduction compared to conventional manual assessment requiring 4–8 h of expert practitioner effort. The system demonstrated consistent scoring performance with IBS scores ranging from 31.24 to 100.00 points (mean 37.14, SD 8.84), while GPT-5-0-mini exhibited 71% faster inference (mean 23.4 s) compared to GPT-4o-mini (mean 80.2 s) with no significant scoring divergence, validating prompt engineering robustness across model generations. Processing efficiency scales approximately linearly with file size (0.67 s per megabyte), enabling real-time design feedback and portfolio-scale batch processing previously infeasible with manual methods. Unlike prior rule-based compliance checking systems requiring extensive manual programming, this approach leverages LLM semantic reasoning to interpret ambiguous construction classifications while maintaining deterministic scoring through structured prompt engineering. The system addresses key interoperability challenges in IFC data heterogeneity while maintaining traceability and compliance with established scoring methodologies. This research establishes a replicable architectural pattern for BIM-AI integration in construction analytics and positions LLM-enhanced IFC processing as a practical, accessible approach for industrialization evaluation that democratizes advanced assessment capabilities through open-source workflow automation technologies.