The global building and construction industry faces increasing challenges related to efficiency, performance, and sustainability, which significantly impact project success, particularly in developing economies. The timely and successful completion of building and construction projects is crucial for economic development; however, various barriers hinder effective project execution. This study identifies and empirically analyzes the critical barriers affecting building and construction project performance in two developing countries with distinct economic profiles, Ghana and the Kingdom of Saudi Arabia (KSA). A comprehensive literature review and expert interviews identified fourteen key barriers to project performance, ensuring clarity and technical relevance. Using an empirical questionnaire survey targeting experienced professionals, including contractors, clients, and consultants, the study employed the Relative Importance Index (RII) and Spearman’s correlation analysis to rank and examine the interrelationships between these barriers. The findings reveal that poor communication (RII = 0.831, ranked 1st), project cost and schedule constraints (RII = 0.806, ranked 2nd), and inadequate monitoring and evaluation (RII = 0.786, ranked 3rd) are the most significant barriers to project success in both contexts. These challenges align with global sustainability concerns, particularly Sustainable Development Goal (SDG) 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities), which emphasize resilient infrastructure and sustainable urban development. The study highlights the crucial role of decision makers, regulatory frameworks, and financial planning in overcoming these barriers and enhancing project outcomes. By addressing these constraints, the study provides actionable insights for policymakers, project managers, and industry stakeholders to improve project execution efficiency and foster sustainable building and construction practices. Future research should explore adaptive mitigation strategies and technological innovations that enhance project delivery efficiency in developing economies.

Construction site layout planning (CSLP) is the strategic arrangement and planning of construction site spaces, which has an enormous impact on the success of any construction project. Over the past two decades, multiple planning models have been developed to generate layouts that maintain safety and productivity within the construction environment. Yet these models vary significantly with disparate assumptions, many of which remain unstated. This study harnesses social network analysis (SNA) as a means to convert data into knowledge. It applies SNA to shed light on CSLP, providing a comprehensive overview of the existing models, and illuminating the critical parameters that should be considered in layout planning. This analysis delves deep into past methodologies and sets the potential for forthcoming research investigations. This study aims to be a reference for readers and researchers venturing into the realm of CSLP. Numerous related records and studies from diverse databases and sources were reviewed and analyzed. Out of these, 70 articles were singled out, from which 14 pivotal parameters were distilled as the foundation for any CSLP framework. Through the application of SNA, gaps within the existing research domain and literature were pinpointed. The study findings demonstrate the growing interest in shifting to cutting-edge approaches in CSLP. However, the results show that the majority of these models in the literature fall short of sufficiently addressing realistic facility representation, noise effects, or the construction impact on the surrounding environment. Accordingly, this research illuminates these knowledge gaps. The findings of this review guide future research by sketching a broad outline for future optimization models and planning studies.

The process of designing reinforced concrete (RC) buildings has traditionally relied on manually evaluating a limited number of layout alternatives—a time-intensive process that may not always yield the most functionally efficient solution. This research introduces a parametric algorithmic model for the automated optimization of RC buildings with solid slab systems. The model automates and optimizes the layout process, yielding measurable improvements in spatial efficiency while maintaining compliance with structural performance criteria. Unlike prior models that address structural or architectural parameters separately, the proposed framework integrates both domains through a unified generative design approach within a BIM environment, enabling automated evaluation of structurally viable and architecturally coherent slab layouts. Developed within the parametric visual programming environment in Dynamo for Revit, the model employs a generative design (GD) engine to explore and refine various design alternatives while adhering to structural constraints. By leveraging a BIM-based framework, this method enhances efficiency, optimizes resource utilization, and systematically balances structural and architectural requirements. The model was validated through three case studies, demonstrating cost reductions between 2.7% and 17%, with material savings of up to 13.38% in concrete and 20.87% in reinforcement, achieved within computational times ranging from 120 to 930 s. Despite the current development being limited to vertical load scenarios and being most suitable for regular slab-based configurations, the results demonstrated the model’s effectiveness in optimizing grid dimensions and reducing material quantities and costs, and highlighted its ability to streamline early-stage design processes.

The construction industry is a major contributor to environmental degradation, primarily due to the substantial volumes of construction waste (CW) generated on-site. As sustainability becomes a global imperative aligned with the UN 2030 Agenda, identifying and mitigating the root causes of CW is essential. This study adopts a cross-disciplinary approach to explore the drivers of CW and support more effective, sustainable waste reduction strategies. A systematic literature review was conducted to extract 25 key CW source factors from academic publications. These were analyzed using Social Network Analysis (SNA) to reveal their structural relationships and relative influence. The results indicate that the lack of structured on-site waste management planning, accumulation of residual materials, and insufficient worker training are among the most influential CW drivers. Comparative analysis with industry data highlights theoretical–practical gaps and the need for improved alignment between research insights and site implementation. This paper recommends the adoption of tiered waste management protocols as part of contractual documentation, integrating Building Information Modeling (BIM)-based residual material traceability systems, and increasing attention to workforce training programs focused on material handling efficiency. Future research should extend SNA frameworks to sector-specific waste patterns (e.g., pavement or demolition projects) and explore the intersection between digital technologies and circular economy practices. The study contributes to enhancing waste governance, promoting resource efficiency, and advancing circularity in the built environment by offering data-driven prioritization of CW sources and actionable mitigation strategies.

Site layout is the front-end planning for construction sites, aiming for a safe and productive work environment. The layout planning is a complex optimization problem which involves identifying, sizing, and positioning temporary facilities within the construction site boundaries. The main concern in layout planning is the optimization process, in which designer searches among multiple solutions of locating site facilities and choose the best one. The layout optimization problem has been solved using Mathematical and Heuristic methods. This paper studies the applicability of using Visual Programming, Generative Design as the optimization technique, to search for the optimum site layout. As well as, the paper presents an initial development in site layout planning to serve as a foundation that could be enhanced through more future detailed research. In general, the study describes how to model the site and facilities by forming a simulation model applies the parametric visual programming concept through Dynamo-Revit software. Also, it describes the modeling of different geometric and safety constraints between temporary facilities. Then, discussing how the optimization process takes place through the generative design engine. To validate this new optimization technique and the performance of the developed model, a case study from literature is presented and the results are compared