White concrete falls under the category of archi-tectural concrete and stands out for its aesthetic appear-ance and sustainability. This study presents experimental research on 15 white concrete mixtures, evaluating their performance in maritime environments. The experimen-tal research examined the effects of cement type, the com-position and dosage of metakaolin, and the addition of titanium dioxide on the properties of white concrete. Tests were carried out to evaluate the properties of fresh con-crete, as well as the mechanical and durability properties of the hardened concrete. Particular emphasis was placed on the chloride diffusion coefficient, a key parameter for concrete durability in marine conditions. The findings from this study were implemented in the construction of two coastal structures - a hotel and a beach promenade. Due to its high-quality finish, properties, sustainability, and cost-effectiveness compared to natural stone, white concrete has demonstrated significant potential for use in maritime environments.
Uncertainty in construction project management (PM) involves the perceived unpredictability of disruptions that influence project duration, costs and resource availability. This issue is particularly pronounced for micro, small and medium-sized enterprises (MSMEs), especially in regions lacking strong institutional support, digital infrastructure and facing environmental and logistical volatility. This study investigates the internal and external sources of perceived uncertainty among MSMEs in southwestern Colombia. Data from surveys of 25 construction firms were analysed to assess how frequently uncertainties occur, their magnitude, and signalling across 10 domains, both internal and external. Using bootstrapped random forest (RF) models, the most impactful features associated with higher perceived uncertainty were identified. These were complemented by classification trees (CTs) to generate interpretable decision rules. To cope with small sample sizes, a class-preserving data augmentation strategy was validated through Mann-Whitney U Tests. Results indicated that internal sources, such as organisational dynamics and resource estimation, are strongly linked to operational maturity and diversification strategies. External uncertainties, such as logistics, weather and sociopolitical factors, vary notably across different regions. Interestingly, 82.9% of firms with over 29 months of experience followed the most common path for higher perceived market uncertainty, suggesting that experience influences perception. Moreover, high uncertainty was predicted in several domains even without typical signals, implying latent variables, possibly undetected by surveys but captured by models, may be affecting perception. This research offers a practical, data-driven framework employing interpretable machine learning to model uncertainty perception in MSMEs, providing tools for early warning and better decision-making in resource-constrained contexts.
The Fourth Industrial Revolution (4IR) has transformed numerous sectors, yet the construction industry lags in adopting technologies such as artificial intelligence (AI), robotics and Internet of things (IoT). This study explores how leadership styles can drive the integration of 4IR technologies in construction, aiming to identify approaches that foster innovation and technological advancement. Using principal component analysis (PCA), the research examines data collected via a structured questionnaire from built environment professionals in Gauteng Province, South Africa. The data were analysed with Statistical Package for Social Sciences v29 to uncover key leadership patterns. The findings highlight four pivotal leadership styles: transformational, transactional, charismatic and autocratic, as essential for 4IR technology adoption. Transformational leadership encourages innovation and empowerment, transactional leadership ensures procedural compliance, charismatic leadership inspires during uncertainty and autocratic leadership offers decisive guidance. Based on these insights, a four-dimensional leadership framework was developed to assist stakeholders in balancing these styles for effective 4IR integration. The study underscores the importance of leadership training and adaptability to accelerate technological uptake and support industry progress. Despite the limitations emanating from this study, it contributes to practice by providing a practical four-dimensional leadership framework for construction stakeholders to enhance 4IR technology adoption, improving efficiency and innovation. It also provides a roadmap for further research to validate the framework and expand across different industries and regions.
Delays in transportation projects are frequently miscontrolled by contractors submitting unrealistic and inaccurate baseline schedules. Poorly developed schedules can lead to significant project overruns, making it essential for State Highway Agencies (SHAs) to evaluate and approve high-quality schedules. Despite the availability of scheduling guidelines, many SHAs lack effective evaluation processes, resulting in poor project control. This study aims to evaluate the effectiveness of industry-recognised metrics (IRMs) and the Government Accountability Office (GAO) best practices (BPs) in assessing the quality of baseline schedules in transportation projects. The study also seeks to provide practical recommendations for improving the schedule baseline review process. Baseline schedules and daily work reports (DWRs) were collected from four transportation projects managed by one SHA of the United States. The as-built schedules were developed using the DWR data, and the baseline schedules were compared to the as-built schedules using the as-planned vs. as-built delay analysis method. In addition, the baseline schedules were evaluated using IRMs and GAO BPs. The findings revealed that 24% and 41% of the performance metric thresholds were not met when evaluated using IRMs, and only 14%-71% of GAO BPs were satisfied across the projects. The analysis identified significant deficiencies in task descriptions, work breakdown structure (WBS) element identifiers, relationships between activities and float management. The results highlight flaws in current scheduling practices and emphasise the need for SHAs to adopt more robust methods for evaluating baseline schedules. This study provides actionable recommendations to enhance the review and approval processes, ultimately contributing to the timely and efficient completion of transportation projects.
Aligning with industry trends towards digitalisation, sustainability, and the use of high-strength materials, this study aims to enhance the operational efficiency and environmental performance of high-strength rebar (HSS) construction. This study aims to address critical challenges in the construction industry, such as the need for digital integration, sustainable practices, and efficient use of high-strength materials by developing a comprehensive, data-driven framework for digital transformation focussed on optimising HSS operations. The core objective of this framework is to optimise HSS management by providing real-time, actionable insights. The study employs a closed-loop, hybrid methodology that integrates remote sensing for data capture from construction sites, utility theory to model complex decision-making under uncertainty across quality, safety, and environmental factors, and a data-driven optimisation model. By applying this utility-driven approach in a case study, the research demonstrates significant improvements, including a 15% increase in schedule adherence, a 3% reduction in material waste (MW), and measurable gains in operational efficiency, safety, and resource optimisation. Ultimately, this research provides a practical, utility-driven approach that offers clear metrics for progress tracking and resource optimisation, representing a significant advancement in lean and digital construction management.
