iCCPMCE2024 Proceedings

Abstract: The construction industry has made significant improvement on health and safety performance, but construction workers still suffer from poor mental health and are susceptible to suicide ideation. Although useful, mental health improvement programmes, such as awareness campaigns and counselling, fail to address the stressors that are deeply rooted in the nature of the construction industry and its traditional ways of working. Prefabricated construction, which is the offsite assemblage of project components in a controlled environment before their installation on site, has the potential to reduce the impact of the stressor-inducing nature of the traditional construction. To assess the relevance of prefabrication to mental health improvement, traditional and prefabricated construction workers in Australia were surveyed to capture their stressors and poor mental health symptoms. Prefabricated construction participants reported significantly less exposure to stressors such as work-related criticisms, fatigue or tiredness, and poor working conditions, than the traditional construction workers. Furthermore, traditional construction workers exhibited significantly higher symptoms of burnout and depression such as loss of interest in life, feelings of unhappiness, and depression than their prefabricated construction counterparts. Therefore, the findings of this study show the stressor-reducing potential and mental health improvement quality of prefabrication, if properly planned, implemented, and managed.

Abstract: This paper presents the outcomes of an experimental investigation into modified graphite nanoengineered sustainable concrete, utilizing porous recycled concrete aggregates (RCA) as carriers for phase-change materials (PCM). The RCA-PCM composite was created through an immersion technique followed by carbonation using high-purity carbon dioxide. Test results reveal that the addition of 0.02% modified graphite significantly enhances the 28-day compressive strength of RCA-PCM concrete compared to standard RCA concrete. In terms of thermal performance, experimental tests demonstrate that RCA-PCM concrete has the potential to reduce indoor peak temperatures by 4.9 °C compared to RCA concrete. The modified graphite nanoengineered RCA-PCM concrete emerges as an innovative and sustainable building material suitable for thermal conditioning, offering the prospect of saving thermal energy consumption.

Abstract: Nowadays, every country produces a large amount of construction waste every year, which is not only difficult to handle but also a huge waste of resources (Naseri et al. 2022). Recycling construction waste and applying it as recycled aggregates (RA) in construction can bring huge economic and environmental benefits (Ma et al. 2022). Pervious concrete (PC) is also an environmentally friendly road construction material that can help cities quickly remove stagnant water and mitigate the heat island effect (Strokova et al. 2022). Applying RA to PC to form recycled aggregate pervious concrete (RAPC) can bring the above-mentioned comprehensive effects and has a good future for application. But the combination of PC and RA leads to worse mechanical properties of RAPC (Yang et al. 2022). Therefore, it is necessary to find a way to treat RA so as to increase the performance of RA and improve the mechanical properties of RAPC.
This study employs three different methods to treat RA: sodium silicate-silane composite modification (SS), volcanic ash slurry modification (VS), and a combination of volcanic ash slurry and sodium silicate-silane composite modification (VS-SS). Subsequently, PC is prepared using the treated RA to investigate the impact of these three treatment methods on the mechanical properties of RAPC.

Abstract: Accurate prediction of building energy consumption over time is pivotal for the effective development and implementation of energy conservation policies and strategies. A systematic and comprehensive life cycle perspective on energy consumption prediction is essential to ensure project sustainability. Despite this, there are no explicit summaries and contributions of different prediction stages, leading to ambiguous definitions and application of the LCA tool in the energy consumption prediction process. It was widely accepted that building energy consumption prediction is segmented into four stages: defining the prediction scope, selecting input features, collecting data, and choosing the prediction model. Given the complexity of the prediction process and limited space as required, this study focuses exclusively on the final stage—prediction models—to provide a holistic and latest review of energy consumption prediction models to explore their significant influence on accuracy. Bibliometric analysis was conducted to screen 49 of the most related articles on the Web of Science (WoS) from 2014 to 2024. In-depth qualitative discussions were subsequently conducted to further identify prediction modeling methods. Results show six main prediction models, along with their advantages and weaknesses: 1) Physical characteristics-based models, 2) Traditional statistical models, 3) Primary machine learning models, 4) Advanced deep learning models, 5) Hybrid methods, and 6) Scenario simulation models. Although this study concentrates on only one stage of the prediction process, the insights gained into building energy consumption prediction models help researchers select an accurate prediction model in line with specific research goals and requirements. The comparison among them drives the evolution of prediction modeling methods, leading to improving prediction accuracy. However, further validation through extensive case studies is needed in the future.

Abstract: Low carbon practice becomes a global appeal for addressing climate changes. As a major carbon emission sector, building industry has the liability to take all possible actions for reducing carbon emissions. This paper introduces a principal framework of total low carbon management (TLCM) paradigm in the context of building industry. It argues that building industry must engage an advanced management paradigm in order to make effective contributions to the goal of emission reductions. And this paradigm requests the participation of low carbon practice across the whole regulations, the whole industry, the whole building enterprise, the whole building staff, and the whole building process.

Abstract: Researching the phenomenon and answering research questions to generate an integrated management system to manage the post-disaster reconstruction phase calls for a well-created or structured framework for the research methodology plus a mixed method. Aim and Purpose: To produce an Integrated Management of Environmental, Occupational Health & Safety and Quality Management Systems, a Disaster Management framework for Post-Disaster Reconstruction Projects Management and Empirically Validate the Framework. Research methodology and mixed methods framework study activities are the following stages: Literature Review, Formulating Research Methodology and Mixed Methods, The Research Aim and Objectives, The Research Question Statements - Mixed Methods (Qualitative and Quantitative), Planning and Procedures for Participants and Service Users' Involvements, Designing of Questionnaires and Surveys Research Question, Using Mixed Method Design Data Collection and Analysis with NVIVO and Final Development of the Integrated Management System for Post-Disaster Construction Management Phase, Recommendation and Conclusion. OBJECTIVES: Explore the awareness and practice of environmental, occupational health, safety, and quality management systems, as well as disaster management practices for the post-disaster reconstruction phase and routine reconstruction. Furthermore, the mixed methods part addresses the research aim and objectives. Then, it facilitates the achievement of the research goals and contribution to the knowledge and development of an integrated management system for the postdisaster reconstruction management phase. The end addresses the significance of the research methodology and mixed methods framework developed.

Abstract: The construction industry is shifting from traditional methods to digital approaches. Point cloud technology, which offers precise geometric information, is increasingly used for 3D model reconstruction, quality inspection, and more. Existing reviews often fail to capture recent trends or focus narrowly. This paper reviews the latest advancements in point cloud applications in construction, covering literature from 2014 to 2023 and summarizing six major applications: 3D model reconstruction, geometry quality inspection, construction progress tracking, safety management, heritage management, and construction robot applications. This review underscores the significance of point cloud technology in driving the digital transformation of the construction industry.

Abstract: Amid the global effort to address climate change, architects and industry practitioners often grapple with a critical concern: how to select a building design that optimally manages energy and financial resources throughout its lifecycle. Researchers worldwide are advancing building optimization models to minimize energy consumption and greenhouse gas emissions. Vietnam's government employs rigorous enforcement of laws, clear green construction regulations, and diverse strategies to promote sustainable development.
The aim is to encourage construction firms to use environmentally friendly materials in current and future projects. This study identifies several influential factors, such as experience, credentials, and talent, in assessing green buildings. These factors encompass motivation for economic optimization, energy and water conservation, material management, and market strategy enhancement. Efficient energy management is crucial for evaluating sustainable construction approaches. It will also influence future assessments, including life cycle cost and environmental impact evaluations during project implementation. Prioritizing influential components in green building development is essential. This resource offers scholars, designers, and professionals precise methodologies for project development.

Abstract: The objective of this research is to develop an evaluation framework for technically appraising underground methodologies during the pre-construction phase. Initially, technical assessment criteria were derived through a combination of literature review and expert consultations.
A survey was subsequently administered to gather insights from individuals with practical experience in underground building. Factor analysis was conducted to uncover the underlying significance of each criterion. Next, a Fuzzy Analytic Hierarchy Process (Fuzzy AHP) model was constructed to determine the relative importance of each criterion. The assessment framework was then applied to evaluate the underground construction approach for a specific project, and the results were validated by projectinvolved experts.
The study yielded a Fuzzy AHP model comprising 8 categories of factors and 35 refined criteria, spanning various domains from documentation and resources to geological and hydrological considerations. These factor categories represent original contributions to the field and are pivotal for the technical evaluation of underground construction methods in the pre-construction phase. The findings underscore the efficacy of the model in aiding construction firms in making informed decisions for the successful and safe execution of chosen underground construction methodologies, particularly during the pre-construction phase.

Abstract: The construction of public residential projects in Kuwait started in the 1950s by the Public Authority of Housing welfare. Today, an approximate waiting period of 20 years is needed to obtain a house ready to live in. The major problem is that most of the owners of these public housing units are unsatisfied with the overall design and finishing. These public houses have one design and structure that does not fulfill the end users’ needs and aspirations. This leads to a long revamping process carried out by the units’ owners that provides end-users with all means of comfort and satisfactions. The repercussions that stem from this is a delay in moving time and the cost expenses that the end users have to suffer as the people in need of these homes have limited financial incomes and cannot afford these expenses. A survey assessing public housing design and cost are implemented for projects constructed by Housing Welfare. Additionally, personal interviews and questionnaires surveys for both public and private residential projects end users formed the data base for the study. The estimate of revamping expenses is determined along with identifying the reasons behind the changes. This paper presents the findings of a research project aiming to determine the cost comparison between private and public residential projects. The research shows that concrete costs are consistent across both types of housing, with the overall cost being primarily influenced by the quality of the finishing. Additionally, the paper investigates owner satisfaction with public housing to identify potential improvements in policies, plans, and procedures for future public residential projects. It is recommended that homeowners be given the option to either complete their own finishing or receive a house with finishing already done.

Abstract: Ferrochrome slag (FCS) is investigated as a partial replacement for fine aggregate (sand) in concrete production. The study aims at reducing environmental pollution that arises from the dumping of the slag. Both physical and mechanical properties of the FCS were studied. For the concrete mix, fine aggregates were replaced with FCS aggregates in proportions of 25, 50, 75, and 100%, while 0% replacement was used as the control (reference) sample. Aggregate properties investigated are grading, fineness modulus, compacted bulk density uncompacted bulk density, relative density, and water absorption. The investigated properties of fresh and hardened concrete are slump, compressive strength, tensile splitting strength, and flexural strength. The physical characterization results of FCS obtained indicate that it complies with the national standard specifications for natural aggregates. The performance of the hardened concrete improved as the rate of FCS substitution increased. The optimum percentage replacement of FCS based on this study is 100% as it gives increments of 19.76%, 5.4% and 20.68% for compressive strength, split tensile strength and flexural strength respectively when compared with the control sample at 28 days curing period. FCS shows positive indication of inclusion in concrete.

Abstract: This paper delves into the prevalent issue of pathological problems in concrete structures, with a specific focus on corrosion in steel reinforcement. It details an experimental investigation into the effects of chloride environments on prestressed concrete structures. Central to this study is the analysis of stress corrosion cracking (SCC) in 5 mm prestressing strands. The findings reveal that SCC predominantly manifests as pitting corrosion, which in turn initiates micro cracking on the wire surface. Intriguingly, the stress applied to the wires appears not to alter the composition of the corrosion products. This research offers comprehensive insights into the behavior of high-carbon steel wires under SCC conditions. A critical discovery is the significant influence of stress level on SCC progression, which markedly diminishes the ultimate strength of the corroded wires. This is particularly evident in the 48% reduction in ductility of wires at 95% of the tensile strength (fptk), a consequence of the formation of localized microcracks. These findings underscore the need for a deeper understanding of SCC in prestressed concrete structures, which is vital for enhancing their durability and longevity.

Abstract: Off-site construction has become a widely accepted method due to its advantages in time-saving, rapid erection, and low cost. The rapid growth in this area demands better and more refined construction scheduling methods. Construction scheduling is complicated by the nature of various constraints in different aspects, such as resources and labour. Traditional methods, such as the Critical Path Method (CPM), lack consideration of various constraints, making them less applicable in real-world projects. This study proposes a Deep Reinforcement Learning (DRL) method to generate optimal construction schedules under limited labour and resource constraints. The objective of this study is to minimize the duration of construction projects. The proposed method introduces an improved DRL framework that enables the DRL to handle the scheduling of all construction processes. A case study is conducted on a real-world prefabricated bridge with 9 spans to evaluate the proposed method's performance. The DRL method is compared with traditional methods and the Genetic Algorithm (GA). The results show that DRL outperformed other methods in generating optimal construction schedules and required less running time. Therefore, the proposed method in this study extends the construction scheduling method and can be used in real projects.

Abstract: This paper covers the collection and analysis of data through a survey conducted at Kuwait Ports Authority’s Ports Complex. Since quality is an important indicator for the selection of an optimum facility management operating model, the questionnaire evaluates the level of satisfaction of the end-users with the current services at the Ports Complex. End user satisfaction reports from a local facility management firm are collected to assess the quality of services provided. By evaluating the end-user satisfaction level of both KPA’s current traditional practices and local’s integrated facility management practices, conclusions will be drawn as to whether end-user satisfaction can be optimized.

Abstract: In an era of knowledge economy, most construction enterprises are adopting technology alliances to address increasingly serious environmental issues and severe market rivalry. Despite the rapid development of such alliances, there is a high failure rate, how to evaluate the sustainability of construction enterprises technology alliances (CETA) is relatively lacking. However, distinct from other alliances, technology alliances are dedicated to knowledge diffusion and innovation, it’s more insightful from a knowledge perspective to analysis sustainability. Thus, based on knowledge viewpoint, this study builds a Bayesian Belief Network (BBN) model for assessing the sustainability of CETA, aiming to construct a scientific evaluation framework encompassed four dimensions, focusing on environmental, economic, social, and relational. The results indicate that: (1) Integrating of various theories, the constructed evaluation framework provide a comprehensive measure of the overall sustainability for CETA; (2) Knowledge spreads through construction activities, socioeconomic events and alliance network building; (3) The environmental sustainability is most significant for CETA, and green innovation plays an effective transmission effect, driven by green motivation, to promote the growth of green benefits. Moreover, the shared vision and asset specificity are the most important in relational sustainability. Additionally, cost feasibility and health and safety play a crucial role in economic sustainability and social sustainability, respectively .

Abstract: Understanding the social performance of buildings is challenging due to the complexity of their value chains. Building specifications and material selections are based on performance criteria governed by construction codes, standards, and industry guidelines, yet they often overlook modern slavery considerations. Due to this oversight, practitioners and non-governmental organisations (NGOs) risk neglecting the social implications throughout the building's design and construction stages. To investigate how Australian building practitioners and NGOs perceive modern slavery risks in their material specifications, we conducted a bottom-up analysis of responses to analyse industry actors' experiences and identify factors that influence the respondents’ decision-making during material specifications. Employing a mixed methodology with 18 expert interviews and 230 surveys, our study used industry sub-domains of 1) education, 2) clients, 3) material procurement and 4) regulation. Our findings suggest that the risk of modern slavery in selections is generated due to inadequate regulation, limited product information, and constrained access to modern slavery information, compounded by a lack of knowledge, time constraints, and project costs. This could be addressed through improved education, increased client awareness, transparent procurement, and stronger regulations. Product and material specifications frequently lack human rights information due to opaque supply chains and restrictive legislation, fostering practitioner distrust in addressing modern slavery. The outcomes underscore that a comprehensive approach is required, targeting the industry sub-domains identified and further integrating circular economy principles within supply chains to overcome the trust deficit among practitioners and NGOs when specifying products with human rights considerations. This paper proposes an integrated approach to assist in fostering the commitment of NGOs and practitioners to address modern slavery risks within the building sector.

Abstract: This paper focuses on the application of deep learning algorithms in processing 3D point cloud data for intelligent detection of construction dimensional quality. It discusses thelimitations of traditional machine learning algorithms, such as ICP and RANSAC, inhandling complex or irregularly shaped components due to their narrow scope of application. The paper highlights the advantages of deep learning-based methods, which canautomatically identify components without being constrained by specific shapes or structures. The analysis includes the current state of research on intelligent detection of constructiondimensional quality and the status quo of component recognition from point clouds. Potential research plans and strategies are also proposed to address the current algorithmicdeficiencies in performance and requirements.

Abstract: The construction industry faces significant sustainability challenges due to high energy and material consumption. Modular integrated construction (MiC) is a more sustainable alternative to traditional in-situ construction. It involves the fabrication of integrated modules in off-site controlled conditions and their transportation to construction sites for installation. MiC offers various social, economic, and environmental benefits, such as enhanced safety, increased productivity, and reduced waste. The success of MiC projects depends on efficient cross-border logistics, with Just-in-Time (JIT) deliveries being crucial. However, persistent problems related to JIT implementation still exist, even with the adoption of advanced project management software such as enterprise resource planning systems, building information modeling (BIM), and geographic information system (GIS) technologies. In this context, this paper proposes an i-Core and smart contracts-enabled framework for JIT deliveries of MiC modules. By addressing persistent problems related to JIT implementation, the proposed framework is expected to improve the overall efficiency and sustainability of MiC.

Abstract: The swift evolution of digital technology has spurred numerous industries to enhance their innovation competencies. The construction industry, characterized by low levels of digitalization, is in dire need of incorporating digital technologies. Artificial intelligence (AI) technology is the preeminent technology in the field of digitalization, and its integration with construction technologies is expected to yield innovative achievements. However, the majority of extant research concerning the implementation of AI technologies in construction is based on analyses of scholarly papers and literature reviews. Only a limited number of studies employ quantitative patent data to explore the convergence degree of AI and construction technology. This paper measures the degree of technological convergence using patent data and graph convolutional neural networks (GCN) based on patents. The spatiotemporal evolution characteristics of technological convergence in the AI and construction fields are analyzed. Technology convergence degree is studied to identify key fields that promote the convergence of AI technology and construction technology. This study improves the relevant theoretical methods for identifying technological convergence and can help industry regulators focus on AI and construction technology convergence fields with potential and value, and formulate policies to promote digital development in the construction industry.

Abstract: The new quality productivity in the construction industry includes construction robots, HumanMachine/Computer Interfaces, new energy construction machinery, etc., which can promote the green and high-quality development of the construction industry. The process of technological innovation in the formation of new quality productivity is highly complex, requiring industrial innovation actors to dynamically respond to various factors in the industry and deeply integrated themselves into the regional innovation network. Based on patent data, this study constructs an innovation network of new quality productivity in the construction industry, using the dynamic capability theory to explain the linkage mechanisms of the innovation network. The negative binomial regression is used for empirical analysis. The results show that: (1) Geographical proximity and institutional proximity always promote cooperative innovation, and the significance of industrial proximity and technological proximity fluctuates. (2) The effect of policy support is relatively significant, while the effect of environmental policy is not significant. (3) The two regions with strong industrial innovation ability tend to collaborate. (4) Social and economic factors all have a certain influence in a certain period of time. This study has implications for regional construction innovation and the formation of new quality productivity.

Abstract: A comprehensive sustainability assessment is paramount for enhancing the sustainable outcomes of infrastructure projects. In New Zealand, all projects with a capital value of over $100 million are obliged to complete a sustainability assessment. However, the traditional human-intensive assessment process often proves to be time-consuming and costly, particularly when evaluating the sustainability of large-scale infrastructure projects. While emerging digital technologies have the potential to enhance sustainability outcomes, there is a lack of clarity on how digital technology can be effectively utilised to expedite the sustainability assessment process. This systematic study aims to address this gap by investigating the utilisation of digital technologies, including building information modelling, digital twins, drones, Internet of Things, or a combination thereof, in evaluating the sustainability performance of infrastructure projects. By conducting a thorough systematic review of academic literature, this research discusses the existing practice of integrating digital technology into infrastructure sustainability assessment. Additionally, through an in-depth scientometric analysis of global scientific research, this research provides insights into emerging trends and areas of focus in the fields of construction informatics and infrastructure sustainability assessment.

Abstract: With the increasing severity of pollution, environmental infrastructure (EI) has gained more attention as a means of environmental governance to achieve regional sustainability. However, the construction of EI is complex and systematic due to path dependence of cities on technology and traditional industries. This paper investigates the relationship between technology transfer, EI investment, and expressway construction using panel data collected 30 provinces in China from 2010 to 2019. A twoway fixed effects model is utilized to validate the hypothesis. The results show that regions with higher levels of technology transfer significantly promote EI investment; Expressway construction has a significant negative moderating effect on the relationship between EI investment and technology transfer. These findings indicate that regions that rely heavily on expressways may face challenges when transforming toward green development. Substitution variable method and time lag method were utilized to test the robustness of the results. This research not only reveals the micro mechanism of how technological transfer impacts EI investment, but also suggests the construction of EI should be region-specific by considering transport infrastructure.

Abstract: Almost 25% of the environmental impacts, based on the indicator of global greenhouse gas emissions, are caused by traffic. For designing new traffic routes and decision-making processes, it is thus essential, that integral life cycle assessments (LCA) are conducted to ensure sustainable solutions in long term and to achieve the UN Sustainable Development Goals (SDGs).
This basic study examines an ecological comparison between two fictitious traffic routes. Route A reflects a typical Austrian mountain pass road with an average gradient of approximately 3 %. Route B investigates a new route variant with a tunnel (length 1,000 m), which shortens the general route distance and minimises the inclines.
The LCA considers life cycle stages from raw material supply to the usage of the tunnel over an analysis period of 100 years. The results of route B are then compared with a traffic LCA, which considers the operational emissions of route A.
In assessing the tunnel, the LCA incorporates the New Austrian Tunnelling Method, Austrian materials as well as typical geological conditions. To study the traffic effects, the vehicles driven in Austria were included by the current vehicle stock and were analysed in accordance to EN 17472 and EN 15804. The results (Global Warming Potential) show that the environmental impacts caused due construction, maintenance and operation of route B are lower than the operational traffic emissions of the mountain pass road. Consequently, the tunnel variant leads to general environmental savings. Hence, constructing and maintaining the tunnel gets environmentally amortised in a short period of about 10 years. Ultimately, the traffic usage counts as main emitter over the life cycle.
This research illustrates the importance of integral LCAs of transport infrastructures. Within this context, integral LCA studies support decision-making processes and will provide optimal support for a future proof sustainable built environment.

Abstract: Research on gender disparities in the construction industry has traditionally overlooked the role of technology in empowering women. This study aims to fill this gap by setting two key objectives: firstly, to outline the job roles of women in construction and their associated challenges, and secondly, to pinpoint areas where technology can address the challenges to increase female participation within those job roles. Through a systematic literature review and a task-based taxonomy, the study identifies two primary job roles for women: on-site roles encompassing tradeswomen and on-site professionals/managers, and off-site roles comprising managers/CEOs, administrative/clerical staff, and office professionals. To address the second objective, the study identifies 29 construction 4.0 technologies from existing literature, presenting them within a framework that categorises these technologies into digital layers, digital tools, and physical layers. By doing so, the research highlights specific technologies that could alleviate the challenges faced by women in both on-site and off-site job roles. Practical implications of this research lie in its potential to inform future interventions aimed at narrowing gender disparities in the construction industry. By identifying specific technologies that can facilitate women's participation and advancement in the field, policymakers, industry stakeholders, and organisations can develop targeted strategies to enhance inclusivity and diversity within the sector. Theoretical implications of this study extend to the broader discourse on gender, technology, and employment. By shedding light on the synergies between technology adoption and gender equity in a traditionally male-dominated industry, this research contributes to theoretical frameworks exploring the intersection of gender, technology, and labour market dynamics. Moreover, it underscores the importance of considering gender perspectives in technology design and implementation to foster more inclusive work environments across industries.

Abstract: As one of the world's largest energy consumers and carbon emitters, the construction industry plays a pivotal role in advancing global sustainability. Promoting technological innovation is essential for the industry's green transformation while maintaining development goals. However, current research reveals a significant gap in identifying and assessing potential technological innovation opportunities within the green construction sector, resulting in a lack of decision-making guidance for governments and innovators during the research and development phase. Recognizing this, the study proposes a twostage technology opportunity prediction approach based on interpretable machine learning from the perspective of technology convergence. Unlike traditional methods, this approach estimates the likelihood of emerging technological opportunities and anticipates the impact of convergence events. By examining 600,442 patent documents related to green technologies and construction, the study forecasts potential technology convergence innovations and investigates the factors driving these trends. The findings provide critical decision support for policymakers and organizations to develop strategies for green technology innovation.

Abstract: To ensure a safe environment for occupants, analyzing the structural safety of existing buildings is essential. The main objective of this paper is to combine machine learning (ML) algorithms with the Synthetic Minority Over Sampling Technique (SMOTE) to establish a comprehensive condition assessment model for structural safety in existing buildings and provide an interpretation of results. Firstly, a raw dataset comprising 18,090 existing buildings in a region of Southwest China was assembled, containing fundamental information about each building. This dataset was then preprocessed and augmented using the SMOTE method. Subsequently, the analysis was performed using four different ML algorithms, including artificial neural network (ANN), decision tree (DT), random forests (RF), and Adaptive Boosting (AdaBoost). Hyperparameters for these models were optimized using a grid search method with 5-fold cross-validation. Finally, a feature importance analysis was conducted based on the best-performing algorithm. The SMOTE-based RF model demonstrated the highest performance, with the evaluation metric G-mean reaching 96.34%. Among all input features, Service Life, Function, and Location were identified as the three most important factors influencing the structural condition of existing buildings. This study represents a promising approach for assisting government regulators in making critical maintenance decisions more effectively and efficiently through a rapid screening model for identifying buildings with potential structural issues.

Abstract: To achieve the “dual carbon goals” in building sector, the paper presents a novel building energy consumption strategy model during the operational phase based on the emission trading system (ETS). In the context of distributed grid layout, the best energy consumption strategy obtained by building users using stochastic dynamic programming (SDP) based on real-time electricity prices and carbon trading prices and their own energy consumption preferences. This makes the whole problem of multiobjective optimization including carbon trading and the cost of building operation. In this paper, the model is used to analyze a Chongqing building, and the sensitivity analysis of carbon permits costs is made. The results show that, (1) the cost of building carbon emissions has a significant impact on the operation of the building; (2) the user's energy consumption strategy can also affect operating costs; (3) the ETS achieves near-zero emissions while increasing building operating costs. This shows the importance and effectiveness of the ETS in the realization of “dual carbon goals” in building sector, and the value of building users actively developing energy consumption strategy.

Abstract: Through the rapid growth of the construction market in past decades, the construction management industry in China is now facing the challenges of digital transformation with the extensive development and application of information technologies in construction engineering and management. This literature review explores the digital transformation of the construction management industry in China, focusing on its drivers, technological advancements, challenges, and implications. It highlights the role of government initiatives, labour shortages, and the demand for sustainable practices as key drivers of this transformation. The review discusses the impact of technological advancements such as Building Information Modelling (BIM), Internet of Things (IoT), and virtual reality (VR) on construction management practices. Furthermore, it explores the impact of digital transformation on project management and performance, emphasizing improvements in construction supervision, quality management, cost management, and schedule planning.

Abstract: The construction sector makes a significant contribution to the establishment of sustainable development. In the past few decades, the industry has shifted towards a more sustainable strategy by embracing advanced technology and renewable materials. The purpose of this study was to determine the influence of project management practises on sustainable building development in UK. A quantitative questionnaire survey was employed to collect the data to test the research framework. Snowball sampling was used to recruit 205 participants among professionals who have worked or currently work in construction organisations in UK. In order to establish the interrelationships among project management methodologies, green technology, and sustainable construction methods, the responses were tested using correlation, confirmatory factor analysis, and structural equation modelling. According to the data findings, good quality project management practices can pave the way for sustainable construction implantation in UK and this relationship can be strengthened by the combination of digital green technology. Instead, it may be controlled by providing training programmes and improving communication channels. Overall, this study provides significant data for industry professionals and governments interested in encouraging sustainable construction practises in UK.

Abstract: Megaproject is an important platform for technological innovation and value creation. However, the efficiency and effectiveness of collaborative innovation in such projects are disappointing. One of the main reasons is the neglect of the value motivations behind the innovators involved. Therefore, coordinating the value motivations of various innovators to enhance the efficiency and effectiveness of technological innovation collaboration in megaprojects becomes a significant issue. Therefore, this study from the perspective of value co-creation and using grounded theory methodology, develops a three-dimensional theoretical model (encompassing lifecycle, innovators, and collaborative innovation dimensions) for collaborative technological innovation in megaprojects. This model preliminarily reveals the process of collaborative innovation among various innovators throughout the entire lifecycle. It could enhance the mutually beneficial relationships among innovators in the context of megaprojects, and further achieve value co-creation.

Abstract: This study explored integrating Building Information Modelling (BIM) to optimise construction supply chain resilience in South Africa. Through bibliometric analysis embedded in the Scopus database, coupled with the use of keywords such as “construction,” AND “supply,” AND “chain,” AND “building,” AND “information,” AND “modelling,” and the use of Vosviewer to generate occurrence map, 290 papers were exported. The findings showed that integrating BIM from a South African perspective would improve operation. Recommendations emphasized stakeholders' need to invest in BIM technology tools, promote collaboration across the supply chain, and advocate standardized protocols. This study highlights the multifaceted impact of BIM, which includes enhancements in architectural and structural design, the integration of lean principles, and the incorporation of technological innovations such as radio frequency identifiers (RFID) and the Internet of Things (IoT). Furthermore, this research underscores the importance of effective information management, decision-making processes, and knowledge sharing within the construction industry. By embracing these recommendations, the South African construction industry can leverage BIM to enhance efficiency, resilience, and sustainability, thereby positioning itself for continual growth and development.

Abstract: Poor manpower operations are affecting the construction industry in Nigeria despite the importance of the industry for national development. This study aimed to examine the effect of manpower operations in construction firms using VUCA model. A quantitative research design was adopted using a sample size of 300 among the population of construction professionals (Architects, Builders, Civil Engineers, and Quantity Surveyors), by employing a questionnaire as an instrument for data collection. Statistical Package for Social Sciences (SPSS version 23) was used as a tool for descriptive and inferential analyses. The results showed that: The professionals are somewhat aware of VUCA model in the building construction industry. However, social and financial uncertainties are the factors hindering the adoption of VUCA Model in construction firms for effective manpower operation. However, Firm reputation, occupational education and training, material management, and supervision are the most relevant factors for effective manpower operations in construction firms. VUCA model affects manpower operations in construction firms; which ensures project success, and adequate resource allocation, efficiently and effectively affects time and cost management of construction project delivery, and also, ensures the quality of project out-put by manpower operations as parts of most effect of VUCA model. The study recommended that professionals must have new perspectives and create stronger ideas, be flexible to challenges, as well as to develop responsible professional leadership styles that are generous, and capable of developing constructive ideas and networking, this can curtail factors hindering the adoption of VUCA model.

Abstract: Efficient waste management practices in construction are pivotal for sustainable development, particularly in emerging economies like Nigeria. The construction industry significantly contributes to environmental degradation through waste generation. This study explores the effectiveness of Building Information Modelling (BIM) in pre-empting construction waste during the planning and design stages. Utilizing a quantitative research approach, data were collected from 340 construction professionals in African Nigeria. The analysis revealed that BIM enhances waste mitigation by improving information sharing among stakeholders, optimizing resource use, and facilitating better project coordination. Notably, factors such as improper project planning and poor workmanship were identified as primary contributors to waste generation. BIM's capabilities in automated waste analysis, improved design documentation, and the use of prefabrication were highlighted as key strategies for waste reduction. The findings underscore BIM's potential to foster sustainable construction practices by minimizing waste and promoting efficient resource management.

Abstract: Several construction sites in Nigeria face significant challenges related to theft and vandalism, leading to financial losses, project delays, and low quality. The study aims to evaluate the impact of technological security measures and its effectiveness in preventing theft and vandalism on construction sites in Nigeria. The study adopts a descriptive design and employs a questionnaire- to collect data from respondents. Descriptive and inferential statistics such as mean, frequency, and regression were used to analyze the data. Major findings reported significant incidents of theft and vandalism occurring in construction sites, with construction material theft as the most common incident. In addition, these incidents often result in substantial financial losses. Similarly, most of the contractors utilise technologies like smart locks and GPS tracking to prevent theft and vandalism, but there is still a significant portion that is not aware of or utilising these technologies on sites. Moreover, the regression shows a significant contribution of technologies in curbing the incidence of theft and vandalism. Additionally, the data suggests that factors such as lack of training and funding as the barriers to technology adoption, with a notable majority willing to invest in new technologies to improve security measures. The study recommends that increasing funding, awareness, and training, along with the installation of surveillance cameras, are key to promoting the effective utilisation of these technologies. This study contributed to the body of knowledge on construction site security and provided practical recommendations for improving security measures against theft and vandalism on sites.

Abstract: Trade-level productivity plays a major role in evaluating the overall performance of building projects. Thus, significant attention has been given by researchers and practitioners to identify the key trades of building projects. However, very few studies have comprehensively investigated this body of knowledge. Therefore, this study aims to analyse the literature on building trades and propose a framework to support trade-level labour productivity (LP) measurement for building projects. To achieve this aim, a systematic literature review is carried out and bibliometric and in-depth content analysis is used for the analysis. Data are retrieved from Scopus, Google Scholar and Government sources. In total 72 publications are shortlisted for detailed review after several levels of screening including duplication, title and abstract checking and skim reading. The results of the bibliometric analysis mapped the yearly publication trend and publications by country/region. In-depth content analysis of the selected papers summarised the building trades identified in the literature from different perspectives of the trades. The proposed framework contributes to a better understanding of building trades and LP and also guides practitioners to achieve effective and detailed trade-level LP measurement for building projects.

Abstract: The fundamental purpose of this research study is to examine the impact of poor maintenance in commercial buildings and the exponential risk during property acquisition. By leveraging innovative solutions, implementing proactive maintenance strategies, and fostering stakeholder collaboration, property stakeholders can navigate the complexities of maintenance challenges, ensure long-term sustainability, and reduce the risk when acquiring commercial real estate assets in Australia's dynamic market landscape. The research findings indicate that the Australian property market is not immune to similar globally experienced exponential risks when commercial buildings are exchanged or acquired, and a research gap remains to be addressed. Further research is required to evaluate the effect of maintenance deficiencies on property valuation as the research should involve exploring the role of emerging technologies such as maintenance systems, building automation and BIM, and how these emerging technologies mitigate risks during property acquisition as this area represents a promising field for future research in the commercial real estate market. The discussion regarding the identification of poor maintenance during the property acquisition phase highlights the repercussion risks, including decreased property value, increased due diligence costs, elevated transactional risks, tenant dissatisfaction, and long-term operational financial implications.

Abstract: Knowledge management (KM) is crucial for successful project completion in the construction industry, where tacit knowledge, embedded in individuals’ experiences, plays a critical role. However, capturing and transferring this knowledge across projects is challenging due to the temporary nature of construction teams and the reluctance of individuals to share their expertise. Traditional KM methods, such as interviews and videos, often fail to capture tacit knowledge due to various barriers, including organisational culture, limitations of technology, and individual factors like knowledge hoarding. This study investigates a novel approach to overcome these barriers and effectively capture tacit knowledge in construction. This study proposes a storytelling-based approach for capturing tacit knowledge within a Knowledge Management System (KMS). Participants contributed their knowledge directly through stories within the KMS, unlike previous studies that relied on interviews or videos. This method aims to address the reluctance to share tacit knowledge by empowering individuals to share their experiences in a comfortable and engaging format. The study’s validation methodology incorporates two elements: (1) extensive research was conducted on KM, storytelling, and existing methods for capturing tacit knowledge, and (2) issues concerning tacit knowledge capture were identified based on the research. This study contributes to the field of KM in construction by: (a) proposing a novel storytelling-based approach for capturing tacit knowledge, (b) addressing the limitations of traditional KM methods in construction, and (c) offering a framework for implementing storytelling-based KM within KMS. The proposed storytelling approach has the potential to overcome existing barriers and contribute to the effective capture and utilisation of tacit knowledge in construction projects. This can lead to improved project performance, reduced rework, and knowledge transfer across projects within the industry.

Abstract: Maintenance in factory buildings is becoming increasingly important as factories use it as a profitgenerating tool. Literature suggests that problems such as poor maintenance budget planning, lack of communication, lack of emergency response, and lack of skilled labour are associated with selecting the predominant maintenance approach for the construction-related factory building. As a result, these problems are prevalent in developing and developed countries, including South Africa. This study aims to identify the most predominantly used maintenance approach for construction-related factory buildings in the construction industry. The paper is based on previous literature on the maintenance of construction-related factory buildings and implementing a suitable maintenance approach. The literature review focused on both the internal and South African contexts. The study revealed that preventive, corrective, and predictive maintenance analyses were the most commonly used maintenance approaches in the sample literature. This paper contributes to a better understanding of maintenance management and the aspects that impact the practical use of the maintenance approach for construction-related factory buildings.

Abstract: The fire resistance of recycled concrete is a critical factor that influences its extensive utilization in structural engineering. This review-based study employs a science mapping approach to evaluate the research conducted in the past two decades on the effects of high temperatures or fire on recycled concrete. By analyzing 200 articles related to recycled concrete subjected to high temperature or fire, this study identifies influential journals and countries that have actively contributed to the field since 2006. Keyword analysis reveals emerging research topics, including the prediction of mechanical properties of recycled concrete under high temperatures and the exploration of innovative recycled concrete mixed with various fibers under high temperatures. The ensuing discussion summarizes the predominant research areas, highlights research gaps such as the limited focus on investigating the performance of recycled concrete at high temperatures, and proposes potential directions for future research, such as optimizing prediction models using deep learning algorithms to evaluate the mechanical properties of recycled concrete under high temperature. By presenting a comprehensive overview of the latest research on recycled concrete under high temperature or fire conditions since 2006, this paper serves as an essential reference for practitioners and researchers, connecting current research areas with future trends.

Abstract: The construction industry plays a vital role in the economy but is also a significant contributor to waste generation and resource depletion. Lean construction has emerged as a strategy to address these challenges by focusing on minimising waste, enhancing efficiency, and maximising value throughout the project lifecycle. Moreover, the lean concepts positively impact sustainability in construction projects. Therefore, this study aims to review the evolution, principles, and implementation of lean construction in the construction industry. Through review, the study concludes that the lean construction principles encompass Customer Value, Value Stream, Flow, Pull, and Perfection. Further, the most commonly cited lean tools utilised in the construction industry include Value Stream Mapping (VSM), Last planner system (LPS), visual management, Total Quality Management (TQM), Poka-Yoke, 5S, Takt Time Planning (TTP), first-run studies, JIT, material or component flow, work structuring, kanban, supply chain integration, cell production units, continuous improvement cells, prefabrication and modularisation, Jidoka (in-station quality), line of balance method (LOB), 5 Why's, Gemba walk, PDCA (Plan-Do-Check-Act) cycle, A3 report, Target value design (TVD) and other. Further research is needed to refine lean construction methodologies implementation and overcome implementation barriers, ensuring its widespread adoption and long-term success in the construction industry.

Abstract: Inadequate seismic design regulations have a substantial detrimental influence on the overall performance of a structure. The existing code-based prescriptive reinforced concert design method adopted from developed countries will lead to the failure of structures. Performance-based design (PBD) is a seismic design approach widely used to assess existing buildings and earthquakes for various tall buildings. In this paper, the seismic performance of 3D reinforced concrete models designed per Ethiopian ES8-15 complies with the standards of Eurocode 8-2004 (based on EN1998-1) earthquake code recommendations. This study used sample linear and nonlinear models of 44 stories. It is located In Ethiopia's capital city, Addis Ababa. RC properties are analysed with ETABS vs. 19 software. Response Spectrum Analysis (RSA), Linear Dynamic Time History Analysis (LDTHA) and Classical Modal Analysis with eleven ground accelerations selected from the PEER website. To scale the selected ground motions with target response spectrum as per ES8-15 elastic spectrum type I, both SeismoMatch and ETABS vs. 19.0.0 software were used. The comparison parameters include maximum story displacement, inter-story drift ratios, shear force, overturning moments, and the fundamental period of the buildings for 1st and higher modes. As per Classical Modal Analysis, RSA and LDTHA analysis results of the sample linear 44-story building were found. The result shows that the four global responses of the structure are higher for LDTHA than for the RSA analysis result. The static nonlinear analysis (pushover) methodologies of FEMA 356, ASCE 41-17, and ATC 40 requirements are used to assess their seismic performance. In addition, Nonlinear Time History Analysis (NLTHA) is used to verify the Static Pushover Analysis (SPO) results. The stiffness of the model, the performance levels LS, IO, CP, the target displacement, and the patterns of the plastic hinges are the areas of comparison. The results show that the structures' global and local performance is very similar. Despite this, there were a few notable inconsistencies with sheer force and overturning moment capacity results for future earthquake assessment. The study highlighted the benefits of all analysis types except ELF for future research. This comprehensive research process instils confidence in the validity and reliability of our findings

Abstract: Structural design is essential for minimizing environmental impacts by encouraging the reuse of resources, recycling materials, and reducing waste and pollution in construction projects. Compared to traditional approaches, sustainable design more effectively supports sustainability objectives. Nonetheless, the decision-making process can be complicated due to differing preferences among clients, architects, and engineers. This research aims to develop a decision-making framework to assess sustainability in the initial phases of structural design. Multi-Criteria Decision-Aiding (MCDA) techniques are utilized to facilitate regulatory choices, with the Fuzzy Analytic Hierarchy Process (FAHP) employed to identify the best solution. Three structural system alternatives—one innovative and two conventional—are evaluated based on economic, social, and environmental criteria. A literature review and expert feedback reveal nine sub-criteria for prioritizing sustainability factors. The FAHP findings indicate that the economic impact is the most significant criterion for assessing the sustainability of structural systems, followed by environmental concerns, while social aspects are the least important. This research emphasizes the potential of MCDA methods to assist engineers in enhancing the selection process for sustainable design, with the proposed framework validated for application in similar future projects.

Abstract: The COVID-19 pandemic represents the most significant global health emergency of the last several decades, resulting in the deaths of millions of people worldwide. The spread of COVID-19 among construction workers has been extremely high, with frequent clusters of COVID-19 cases related to construction sites. Workplace contact is considered the primary cause of these outbreaks. Many governments have suggested implementing staggered scheduling to maintain social distancing among construction workers, but specific staggered work-rest schedules for construction workers, in terms of start time, rest time, and rest duration, are still not available. Therefore, it is necessary to establish optimal staggered work-rest schedules to reduce the infection risk at construction sites. This study proposed a research framework to develop optimal work-rest schedules that can maximize the labor productivity of construction workers while minimizing contact between them. Two research tasks are proposed, including utilizing machine learning methods to estimate workers’ maximum working duration and rate of recovery, and generating optimal staggered work-rest schedules by establishing mathematical programming models. The preliminary results have proved the feasibility of this research framework and laid a foundation for further research. The staggered work-rest schedule model proposed by this research framework could reduce infection risks for construction workers during pandemics as well as enhance the labor productivity of construction projects.

Abstract: As urban populations grow, energy demands and environmental impacts in cities intensify, necessitating sustainable solutions such as building-integrated photovoltaics (BIPVs). This study investigates the integration of geospatial analysis and Building Information Modelling (BIM) to evaluate BIPV potential at an urban precinct level. The proposed framework utilizes GIS and BIM to address urban-scale solar potential and detailed building-level simulations. By utilizing geospatial data from Melbourne and advanced simulation tools, this framework assesses the energy generation, economic viability, and environmental benefits of BIPV systems. The evaluation considers factors such as shading, building orientation, and architectural features, providing a comprehensive analysis that supports urban planning and BIPV implementation. The results highlight the varying solar potential across different building heights and orientations, emphasizing the importance of both detailed architectural modelling for accurate simulations and geospatial analysis of the urban environment dynamics. Additionally, the economic analysis of BIPV systems demonstrates varying profitability based on system type and placement relative to shading. This integrated approach bridges the gap between macro-scale urban analysis and micro-scale building modelling, offering a scalable and automated solution for urban planners and architects.

Abstract: Undoubtably, artificial intelligence (AI) has come to stay in all life activities. The last decade has seen a considerable number of studies and policy implementation across sectors aimed at adopting AI tools. However, less studies have explored the barriers to adopting AI tools in project management (PM) in the construction industry in developing economies such as Ghana. Professionals in the construction industry in Ghana handle complex projects which new technologies like AI can assist in improving their performance. But the shift towards this new technology has been met with many obstacles in the PM within the country. Therefore, this study aims at analysing the key challenges confronted by PM professionals in adopting AI tools in project management within Ghana. This study utilised questionnaire survey solicited from seventy-one experienced PM professionals. The following tests were conducted on the data: normality, reliability, mean score and Kruskall-Wallis tests. Findings from the analysis include lack of commitment from the leadership of PM firms to accept and invest in AI gadgets, there is resistance to change among construction workers with the feeling of AI tools taking over their jobs, cultural barriers, and ethical concerns. Although, the study is limited to a handful of PM professionals in Ghana, it provides a checklist of obstacles that must be overcome to facilitate the practical use of AI in PM. The findings will be helpful and supportive to further research on AI in PM.

Abstract: The current organisational over-reliance on the use of metrics and indicators that are based only on tangible assets, and financial capital, for the measurement of construction performance has proven to be inadequate for the highly complex and dynamic construction industry environments. This paper, based on the critical review of selected construction performance measurement (CoPM) and competitive strategy literatures from 2015-2024, advocates the use of integration of Balanced Scorecard (BSC) and Construction Value Chain to create an in-depth understanding of the need to use a balanced tool in the measurement of performance of construction projects. Using a systematic literature review (SLR) based on the Context-Intervention-Mechanism-Outcome (CIMO) logic framework, the paper focuses on how continuous CoPM, that produces continuous performance improvement, can be used as a strategic tool that leverages on the balanced utilisation of tangible and intangible organisational assets in project implementation. This is done in order to drive the achievement of long-term financial goals and attain competitive advantage. BSC, based on Plan-DoCheck-Act (PDCA) framework, uses balanced strategic goals and KPIs for CoPM of projects. It is believed that the iterative use of BSC for CoPM across the value chain of each construction project will lead to continuous performance improvement for the organisation. This, in turn, will create strategic value for construction organisations with construction excellence at the centre; and ultimately lead to long-term profitability, and market competitiveness of construction organisations. The main outcome of this study is the development of a performance measurement tool that integrates BSC and construction value chain; and this tool supports CoPM at the project phase-level. This extended application of BSC developed by this research is recommended to be used by top-level managers and project managers for the continuous CoPM of construction projects and competitive advantage of the organisation.

Abstract: In the construction industry, construction safety management is primarily governed by a safetymanagement team that involves safety officers, supervisors, project manager, and owner'srepresentatives. Safety reporting plays a vital role in safety management, serving not only to document on-site activities but also to facilitate effective communication across various management levels. With digital-technology advancements, intelligent safety reporting systems based on electronic formshave emerged. However, these systems encounter challenges such as high learning costs, delays inreport submission and unstable report quality. This study presents an intelligent agent designed forsafety reporting utilizing large language model (LLM) technology. The agent is deployed on cloudserver, and safety personnel can connect with it through an instant messaging application to obtainreal-time information. The interaction between the agent and safety personnel is similar to dailyconversations, requiring minimal learning costs. Additionally, the agent seamlessly generates safetyreports, offering a concise summary and subsequent work plans, thereby improving the overall qualityof reports. Through its deployment on a construction site, the agent achieved an F1 score of 0.996 forhazard identification and an average score of 93.4 for generated reports. It has been recognized byconstruction safety personnel, proving its ability to improve the efficiency and quality of safetypersonnel's work and demonstrating its potential to enhance safety management capabilities.

Abstract: The advancement of 3D-printed wall technology represents a significant innovation in the construction industry, particularly in the housing sector. This technology is increasingly being discussed due to its potential to reduce construction project time and address the growing demand for affordable housing. Despite its benefits, the widespread adoption of 3D printed wall technology faces significant challenges, primarily due to the high initial costs associated with expensive 3D printing equipment and materials. This study aims to identify the main challenges and strategies for implementing 3D-printed walls in affordable housing projects. A quantitative approach was employed, involving 73 housing developers in Selangor. Data were collected through online questionnaires and physical meetings, achieving a response rate of 71.2%. Frequency and descriptive analyses were conducted to address the study's objectives. The analysis revealed that transportation is the primary challenge in implementing 3D-printed walls for affordable housing. Additionally, the main strategy for successful implementation identified was ensuring worker safety. These findings suggest that addressing transportation logistics and prioritizing worker safety are crucial for improving the adoption of 3D-printed wall technology in affordable housing projects. In short, the relationship to the construction sector is multifaceted, involving technological advancement, economic considerations, implementation challenges, safety concerns, and data-driven strategies. Integrating 3D-printed wall technology in the construction sector, particularly for affordable housing, can revolutionize building practices by improving efficiency, reducing costs, and meeting the growing demand for housing.

Abstract: The majority of countries in the international context have set the timing of carbon peak, which is crucial for assisting countries in progressing towards the final goal of carbon neutrality. This paper reports the different carbon peak statuses between a sample of 154 countries in terms of carbon intensity. The data used in the analysis were gathered from 1990 to 2020. Peaking statuses are classified into three categories: true peaked, false peaked, and under peaked. The analysis reveals that most sample countries have attained the true peaked status in terms of carbon intensity. Higher-income countries reached true peaked status sooner. Those with false peaked status are primarily influenced by various economic, social, and political factors.

Abstract: Over the past decade, numerous buildings have collapsed, resulting in catastrophic consequences, including the loss of hundreds of lives and substantial material costs. These collapses were often due to structural failures linked to problems arising during construction, such as uncontrolled design changes or inadequately inspected works. Despite numerous studies and reports aiming to identify solutions, the complexity of the involved systems and variations in international legislation have rendered a universal solution nearly impossible. This exploratory research identified four primary causes: (1) poor initial design, (2) miscommunication of design requirements, (3) poor construction practices and (4) failure in monitoring and controlling design changes. The solution identified outlines a proposal to critically examine the current practices of reinforced concrete structural inspections to evaluate their effectiveness in documenting construction processes and identifying potential risks associated with these practices. New technologies could be pivotal in developing a classification system for building structures to gauge their integrity levels. An initial set of tests is proposed, serving as a reference for future building 'structural check-ups' to assess the ongoing and future reliability of a building’s framework. This is generally applicable across different countries and regulatory frameworks.

Abstract: Existing research indicates that the personality traits of miners influence their emotional regulation strategies, and these strategies in turn affect their performance in work fatigue. However, whether there is an intermediary or moderating role among these factors remains unclear.Additionally, while some studies suggest an increased likelihood of unsafe behavior among miners following fatigue, physiological data concerning their cognition remains incomplete and requires further exploration.This study aims to explore the mediating and moderating effects of emotional regulation strategies among miners regarding their personality traits and work fatigue, and to expand understanding of the cognitive and physiological data related to miners' risk decision-making following fatigue.Method: Fifty adult miners (Mage=25, aged 18-40, 100% male) were selected as participants. Emotional regulation tendency, significant levels of personality traits based on the Big Five Personality Traits questionnaire, and the three-dimensional levels of work fatigue were measured using emotional regulation strategy scale, Big Five Personality Traits questionnaire, and work fatigue scale, respectively.The eye-brain consistency hypothesis posits that eye movement trajectories and fixation points reflect the brain's cognitive processes and focus. Therefore, combining eye-tracking experiments, miners' preferences in risk decision-making were further measured.Results: Expressive suppression strategies mediated between conscientiousness and depersonalization; expressive suppression strategies moderated between agreeableness and emotional exhaustion. In eye-tracking physiological experiments, significant differences were found in eye movement data among miners with varying levels of emotional exhaustion.Conclusion: Preferences in emotional regulation strategies play mediating and moderating roles between miners' Big Five Personality Traits and work fatigue. The levels and dimensions of work fatigue are influenced not only by personality traits but also by individual tendencies in emotional regulation strategies, which significantly affect performance in risk decision-making.The findings of this study can further enrich theories related to work fatigue among miners and provide insights for personalized safety management in mining.

Abstract: Detecting module components at the factory is crucial for safety monitoring, quality control, and productivity enhancement. However, traditional segmentation methods are neither cost-effective nor capable of achieving real-time performance. To address these challenges, this study proposes an improved YOLOv8 modular integrated construction segmentation algorithm. The proposed method introduces the construction of a small object-YOLO, optimizing the YOLOv8 model by replacing the basic module with a novel cross-stage partial network fusion module. This new module employs deformable convolutional networks v2 to manage geometric variations of objects and focus on relevant image regions. Additionally, the Wise-IoU strategy reduces the competitiveness of highquality anchor boxes and mitigates harmful gradients generated by low-quality examples. The MultiHead self-attention mechanism further enhances detection accuracy by capturing the relationship between the image and significant objects, making it more suitable for the modular integrated construction dataset. Given that construction images are often taken from a top or bird's-eye view, small objects can be challenging to be detected. Therefore, this algorithm incorporates a small object detection algorithm to improve the model's capability in identifying small objects. Experimental results demonstrate that the improved YOLOv8 model effectively identifies moving objects, achieving a 4.4% increase in mAP and a 4.3% increase in F1 score compared to the original YOLOv8 model, while reducing parameters by 54.05% and GFLOPs by 55.39%. The proposed algorithm provides a reference for automatic segmentation methods of modular integrated construction components at the factory.

Abstract: Recent advances in Large Language Models (LLMs) have demonstrated their impressive capabilities in various tasks. However, their potential in the specialized field of green building assessment has not been explored. Such a study is necessary to understand their performance in this domain, with the goal of optimizing LLMs to reduce the workload of manual green building assessments and enable designers to conduct preliminary self-assessments more efficiently and economically. In this regard, this study expands the dataset from 112 to 1200 real-world cases, and then eleven leading LLMs are selected for evaluation using both long and short text inputs combined with three different prompt engineering techniques (i.e., zer0-shot, zero-shot CoT, few-shot) to determine their accuracy. The findings indicate that LLMs perform better with short text inputs, particularly GPT-4, which showed the highest effectiveness in the green building evaluation field. Prompt engineering improved the performance of GPT-4 with short text inputs, though its effectiveness varied across different LLMs. Furthermore, LLMs excelled in evaluating qualitative criteria that do not require logical reasoning but performed poorly in assessing quantitative criteria that involve complex mathematical calculations. Research findings provide valuable insights for future development of LLM-based methods for green building evaluation, aiming to alleviate current manual assessment burdens and improve design review processes.

Abstract: Modular construction (MC) is an innovative construction method for enhancing productivity and sustainability. Various countries and regions have adopted explicit policies to promote MC, but the complexity of relevant policies impairs understanding and knowledge sharing. This study develops a dialectical system framework of MC policies through the combination of literature review and content analysis and validates its effectiveness in the case of modular integrated construction (MiC) policies in Hong Kong. The framework addresses MC policies as complex dialectical systems, consisting of the technical system, stakeholder network, and the embedded political, economic, social, technological, environmental, and legal (PESTEL) contexts. The technical system further interprets MC policies in terms of four key components, namely, target and timeline, definition and scope, knowledge and labor, and capital. The framework underscores the interdependency between the technical elements of the policy within their complex and interactive broad contexts. Focusing solely on the technical system is inadequate to understand the policy intentions and may hinder effective policy implementation, highlighting the need to incorporate human behaviors and PESTEL contexts. The case study validates the framework as a theoretical lens to understand and analyze the complexity of MC policies, demonstrating the policy evolution on the four technical components and shaped by the broader PESTEL contexts. The developed framework can provide a foundation to review current policies and guide future policy development of MC.

Abstract: The construction industry is under constant pressure to maintain the continuous improvement in productivity and hence add value to the construction projects. Despite the introduction of various management concepts, methods and approaches, such as Lean Thinking, Supply Chain Management and Lean Construction Management, an integrated construction supply chain management approach that utilises the strengths of multiple existing methods is lacking. This paper proposes a conceptual model of Lean Construction Supply Chain Management (LCSCM) to fill the above-mentioned research gap. The proposed model shall incorporate integrating Green, Lean, Agile and Six Sigma (GLASS) management strategies with the integration management of Construction Supply Chain (CSC) to minimise waste and to improve productivity. The integration of Construction Supply Chain stakeholders promotes collaboration. The integration of GLASS into Construction Supply Chain Management (CSCM) optimises the combined advantages of Green, Lean, Agile and Six Sigma management strategies in CSCM. This more efficient Construction Supply Chain Management approach helps maintain the continuous improvement desired in the construction industry. The proposed novel approach to CSCM, is a contribution of this paper to the body of knowledge. It provides the construction industry with more confidence to widespread the integration of GLASS into CSCM.

Abstract: Cost overruns on public sector projects in South Africa have persisted despite multiple interventions. Although the prevalence of traditional cost management techniques has been blamed for the challenge's persistence, there are not many studies showing how collaborative cost management techniques can help address this issue in the context of South Africa. The goal of this study was to highlight the value of a collaborative cost management framework for engendering enhanced cost performance of public sector projects. In accordance with the case study research design, information was gathered through a combination of interviews and project-related documentation from five finished and ongoing public sector projects that served as cases. The study's projects and participants were chosen with purposefully. Thematic analysis was used to examine the data. The study's conclusions demonstrated how well public sector projects performed overall and at a lower cost when using the collaborative cost management approach. It was explained there how the framework may serve as a set of guidelines for all project participants to participate in cooperative cost management activities with the sole goal of adding value for the client. Also, the framework’s ability to minimize recognized cost management difficulties was enunciated. It is anticipated that this study's conclusions will lead to the effective cost management on public sector projects.

Abstract: The construction industry has experienced a lot of digital transformation during the present industrial revolution. This transformation has disrupted every aspect of the construction industry. However, little attention has been paid to the impact of this technology driven disruption on the research landscape. This study aims to identify the present research methods and approaches to check for a commensurate transformation in the research landscape. To achieve this, a bibliometric review was carried out. The data for the study was extracted using keywords from the Scopus database, and the analysis was done using VosViewer. It was observed that researchers are moving more towards the adoption of mixed methods research. Also, researchers are adopting technology-driven research methods (data collection and analysis).

Abstract: The construction industry is the largest emitter of greenhouse gases, accounting for 37% of global emissions, among which embodied carbon of modular buildings cannot be ignored. Although many studies have been conducted on monitoring the embodied carbon of modular buildings, there are still limitations, such as a lack of real-time and transparent data, fragmented and isolated systems, and inconsistent measurement and reporting standards. Therefore, this study aims to develop a real-time embodied carbon monitoring system for modular buildings. The system consists of three essential parts: (1) Firstly, through the Internet of Things (IoT) sensors, the system can automatically monitor and collect data from equipment such as factory processing machines, transport vehicles, and on-site installation equipment, etc. (2) Secondly, the data from the isolated system and the data collected by IoT sensors are stored in blockchain, which can ensure the transparency and credibility of the data. (3) Thirdly, the system has a visual web platform that presents and reports the embodied carbon, which uses a uniform life cycle assessment (LCA) method using the collected data. The study developed a novel multi-technological embodied carbon monitoring system, which will be applied to the Kowloon Tong student hostel being constructed by the Hong Kong Polytechnic University to test its effectiveness. We anticipate that the system can help monitor and manage carbon emissions during construction. This system provides a valuable implication and practical demonstration for the embodied carbon monitoring of modular buildings.

Abstract: The construction industry is undergoing a transformative shift driven by digital platform technologies, offering new methods to restructure traditional processes, project management, and supply chain oversight. This paper explores how integrating gig economy models with digital platforms can centralize project management control, improve resource efficiency, and minimize supply chain fragmentation. By assigning project management to consultant-led project management offices (PMOs), construction projects can become more adaptable and responsive to fluctuating labor and resource demands. Using a simulation-based approach, this study compares traditional contractor-driven project management with digital platform-based gig economy models. The results reveal significant improvements in project performance, including reduced delays, optimized resource utilization, and enhanced quality assurance. These findings highlight the gig economy’s potential to revolutionize construction supply chain management by fostering greater flexibility and more efficient project outcomes.

Abstract: Construction involves the design and assembly of immovable, site-specific structures, often delivered through temporary teams. The construction industry faces ongoing pressure to provide cost-effective, sustainable solutions. Many construction projects experience significant delays due to prediction errors at the initial phases of the project, and case-based reasoning (CBR) could offer an effective method for estimating and predicting accurate construction schedule to reduce delays. While CBR has been used to forecasting construction delays, research on applying it to construction schedules is limited.
This study focuses on developing a CBR-based methodology to predict construction schedule in residential high-rise construction, using equal weighting across various attributes (a "feature counting" approach). The predicted schedules are compared to observed data to assess model accuracy and reliability. A framework for continuously capturing and applying lessons learned can help future projects better anticipate and control project schedules.
Though the overall prediction accuracy is not exceptionally high, the models demonstrate improved reliability with larger case databases. Further research is still needed to refine and address practical implementation challenges.

Abstract: One of the important causes of structural deterioration in concrete structures subjected to a saline or maritime environment is chloride-induced reinforcement corrosion, which manifests as spalling, cracking, and delamination of the concrete cover. In addition, the loss of the link between the concrete and the reinforcement and the reduction in the cross-sectional area of the rebar may lead to additional damage to a corroded reinforced concrete element. Therefore, the samples were submerged in a solution of sodium chloride (NaCl), sodium sulfate (Na2SO4), and magnesium sulfate (MgSO4) to start the damaging process and achieve the anticipated chloride penetration. This study then examines wet-dry cycles (WDC) for 180-d. The volume fractions of date palm fibre (DF), polypropylene fibre (PF), and steel fibre (SF) of 0%, 0.2%, 0.6%, and 1.0%, respectively, were utilized for the fabrication of high-strength fibre-reinforced concrete (HSFRC). The crucial structural characteristics were assessed in this investigation, i.e., compressive strength, flexural strength, density, water absorption capacity, and load-displacement behaviour. The test results indicated that as the fibre contents increased under WDC exposure, the compressive strength of the high-strength concrete (HSC) with DF, PF, and SF increased by 25%, 27%, and 25%, respectively. Flexural strength increased by 37%, 28%, and 57%, respectively. The displaceability ductility, deformability, and energy ductility of the DF, PF, and SF-reinforced HSC were noticeably enhanced with the application of WDC. Hence, the natural DF fibres might be suitable to construct sustainable HSC and be applicable to protect against harsh weathering conditions compared to the PF and SF.

Abstract: Global warming has drastically increased the pressure to reduce energy use in buildings. The European construction sector is facing unprecedented challenges to achieve ambitious energy efficiency objectives and generalize near-zero energy buildings during an economic crisis that is dominated by reduced investments, and a search for cost effectiveness and high productivity. Moreover, the industry is experiencing a digital revolution and the Building Information Modelling (BIM) approach has been gaining interest across Europe. The member states of the EU have implemented many different approaches through regulations and maturity targets, which have to constantly face the traditional lowtech and informal practices of construction businesses.
This paper will provide an in-depth analysis of BIM-related roles and skills for construction professionals to inform current and future training strategies, and with a view to deliver energy-efficient buildings. The methodology included a Europe-wide consultation with experts and practitioners, as well as an in-depth analysis of social media sources used across construction communities, informed by a comprehensive literature review. This has helped to infer the roles and skills that are necessary in delivering a BIM-based project, as well as informing future BIM training and education needs. One of the main findings is that these roles, skills and associated training needs are not static but evolve to reflect the maturity and evolution of technology and the construction workforce.

Abstract: Hydrogels have gained considerable attention globally due to their distinct ability to retain substantial amounts of water without structural alteration, making them valuable for application in diverse fields. This research investigates hydrogel formation, particularly emphasising the influence of crosslinkers, initiators, and exposure to UV intensity on the polymerisation process. Several hydrogel samples were made under different UV exposure durations to investigate the influence of exposure time on the polymerisation process.
It was revealed that when the sample was exposed to low-intensity UV light for a prolonged period, a range of structures, from crystalline to dehydrated forms, formed. In contrast, a high-intensity UV light failed to initiate the polymerisation process. The characterisation of the developed polymer samples was conducted by scanning electron microscope (SEM), energy dispersive X-ray (EDX), and fouriertransform infrared spectroscopy (FTIR).
The study focuses on the need for standardised procedures in hydrogel research and highlights the potential of these materials for sustainable building solutions. By establishing well-documented methods for hydrogel synthesis, this research proposes a foundation for future advancements in solar reflective coatings to reduce building energy consumption and enhance environmental sustainability.

Abstract: Modern Methods of Construction (MMC) have been used to drive construction productivity, innovation, and sustainability in the building industry. However, the road to implementing MMC has been hindered. This paper attempts to establish a roadmap for the implementation of MMC in the Saudi construction sector through analyzing the current situation and determining the critical aspects involved. The research examines multiple aspects of MMC implementation in Saudi Arabia covering the type of MMCs available, the frequency of use of MMC, benefits, and barriers to MMC implementation. The investigation was executed through semi-structured questionnaire surveys involving 100 participants in the construction industry in Saudi Arabia. The study revealed that 66% of participants were aware of MMC, with flat slab construction being the most recognized method according to 86% of respondents. Furthermore, 98% believed MMC is underutilized in the Saudi Construction Industry. The potential benefits identified by the respondents include: reducing environmental harm according to 58% of the respondents, as well as improving project management, client satisfaction, and safety. However, concerns about training, supplier support, and rising costs were noted. The outcome of this investigation is expected to allow stakeholders to understand the key issues relating to MMC implementation and to develop suitable strategies for their wider implementation. The proposed roadmap is of a practical value which could support companies and practitioners on how to plan for MMC adoption.

Abstract: Carbon emissions from the building industry has significant impacts to the global warming. In the context of increasingly severe challenges posed by climate change, accurately assessing the carbon emissions throughout the entire life cycle of buildings is crucial. However, most previous studies have employed the traditional static life cycle assessment (LCA) method, neglecting the dynamic changes that buildings undergo during their life cycle. Comparative studies between dynamic and static life cycle assessments of buildings are scarce. The aim of this study is to analyze the differences in LCA results of buildings by incorporating dynamic factors. First, a static LCA model of a commercial building is established in SimaPro. Second, building information modelling (BIM) and building energy modelling program (BEMP) are integrated to generate dynamic inputs for a dynamic life cycle assessment (D-LCA) model. Revit is employed to establish the BIM model, which generates a bill of building materials. The Designer Simulation Toolkit (DeST) is utilized as the BEMP to simulate the operational energy consumption of the studied building, and the results from DeST are subsequently used as data inputs for the dynamic scenarios. The findings indicate that the differences between static and dynamic scenarios can reach up to 66.7%, with optimization of the electricity mix and incorporating global warming influences identified as the primary reasons for this significant discrepancy.

Abstract: The growing impacts of climate change have brought into question the effectiveness of traditional floodwall designs, which were developed under assumptions of historical climate patterns. This study addresses the urgent need for climate-adaptive floodwall designs (CAFD) in response to the increasing challenges posed by climate change. The research problem focuses on identifying key barriers that hinder the design and implementation of both traditional and climate-adaptive floodwalls, with the goal of informing more resilient and adaptable infrastructure solutions. Through a literature review and thematic analysis, the research identifies and categorises key barriers in the design and implementation of floodwalls, focusing on historical projects prior to the widespread recognition of climate change. The analysis reveals that floodwall projects were historically hindered by environmental, economic, technological, and institutional challenges. While these barriers were sometimes mitigated through advancements in technology, resource management, and community involvement, they persist in more complex forms within the context of climate change. The study further explores emerging barriers specific to CAFD, such as uncertainties in climate projections, the need for adaptive technologies, and socio-political obstacles. These insights are then integrated into a comprehensive framework to guide future floodwall projects, ensuring they are resilient and adaptable to the impacts of climate change.

Abstract: The construction industry creates a large quantity of waste, making effective construction waste (CW) management strategies crucial for environmental protection and resource utilization. However, determining the optimal strategies to maximize the benefits for all stakeholders is challenging and complex. This paper develops a decision-making model using system dynamics and multi-criteria decision analysis (MCDA). First, a system dynamics model is developed, incorporating the two main pillars of sustainability: environmental and economic perspectives. There are one causal-loop model and two stock-flow models developed to qualitatively and quantitatively evaluate the performance of the environmental and economic performance of CW management strategies. Based on the simulation results, an MCDA is applied to identify the optimal strategies considering these perspectives. The integration of dynamic simulation and MCDA effectively supports decision-making in CW management, providing a scientific foundation for reducing environmental impact and enhancing resource efficiency. This model offers a systematic and data-driven approach to developing CW management strategies, contributing to the advancement of sustainable construction practices. The research contributes an integrated decision-making framework that combines system dynamics and MCDA to optimize CW management strategies. It evaluates these strategies from both environmental and economic perspectives using causal-loop and stock-flow models, providing a comprehensive, data-driven approach. This framework supports informed decision-making for stakeholders, aiding in the development of sustainable practices that reduce environmental impact and enhance resource efficiency.

Abstract: The residential building sector is responsible for substantial amounts of energy use and greenhouse gas (GHG) emissions in Australia. To support a net-zero built environment, it is critical to evaluate both energy and financial requirements of energy-saving solutions and provide effective strategies for stakeholders of the built environment. The specific objectives of this project are: (a) identify and summarise the energy reduction strategies for residential buildings; (b) conduct a comprehensive life cycle energy and cost analysis of these strategies; and (c) provide the energy-efficient and cost-effective strategies for various decision-makers (e.g., building designers, contractors, occupants, urban planners, and policymakers). The expected outcomes will include detailed insights into the effectiveness of different energy reduction measures, balancing both environmental and economic considerations. This research will provide pathways to help Australian Residential buildings to achieve the life cycle net-zero emissions.

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