The construction industry builds infrastructure and strengthens the global economy, but it struggles with cost overruns. This systematic study used scientometrics and Social Network Analysis to examine the multifaceted factors causing construction project cost escalations. After reviewing 405 scholarly works, the research mapped and analyzed 66 interconnected cost overrun factors in 69 high-impact studies between 2000 and 2024. To uncover the patterns, the study used two main research methods. First, this study applied a scientometric analysis that reviewed trends and gaps from the previous studies. Second, this study used Social Network Analysis (SNA) to examine how different factors were connected and which factors had the strongest influence on cost overruns. The methodology comprised a systematic literature search, document selection, scientometric analysis, factor standardization, and an SNA application. Seven critical drivers with high network centrality were identified: planning and scheduling issues, project estimation inaccuracies, design inefficiencies, negative weather conditions, scope definition challenges, contractual ambiguities, and unforeseeable site conditions. By applying the SNA degree centrality (DC), the analysis quantified the significance of each factor within the network. With the use of this dual analysis, a novel mapping of the main causes of cost overruns was produced, leading to the discovery of seven core factors that significantly affected project outcomes, including planning and scheduling issues, project estimation problems, and design inefficiencies. The findings advance the knowledge of the dynamics of cost overruns and offer practical insights for enhancing cost management practices in the construction industry.

In response to the critical need for enhanced resource management in the construction industry, this research develops an innovative, integrated methodology that synergistically combines Agent-Based Modeling (ABM), Building Information Modeling (BIM), and Bluetooth Low Energy (BLE) technologies. Central to our approach is a sophisticated technological framework that incorporates a Client Early Warning System (CEWS) and a Decision Support System (DSS). These systems facilitate real-time monitoring and management of construction resources, ensuring operational efficiency and optimal resource utilization. Our methodology was empirically validated through a comprehensive case study at Helwan University’s College of Engineering. The results demonstrated a significant enhancement in operational efficiency, particularly in resource allocation and progress tracking. Key practical outcomes include the development of a CEWS master dashboard that provides in-depth, real-time insights into project metrics. This dashboard was crucial for managing compliance with health protocols during the COVID-19 pandemic, showcasing the framework’s adaptability to critical health standards. Further, the integration of indoor tracking technology revolutionized attendance tracking by replacing outdated manual methods with automated processes. This capability not only underscores the practical applicability of our research but also establishes a new benchmark for future technological advancements in construction project management. Our study sets the stage for subsequent innovations, paving the way for a more connected, efficient, and data-driven approach in the construction industry.

This study delves into the dynamics of ‘Variations’ and ‘Claims’ in construction projects. This study aims to identify, categorize, and devise mitigation strategies for critical types of variations and claims that are aligned with the contract’s FIDIC conditions. The research draws on input from construction industry professionals, including contract administrators and project managers, and focuses on the MENA region. The region’s extensive adoption of FIDIC standards and the rapidly growing construction sector drive this choice. Data collection encompassed a questionnaire distributed to 80 industry experts, predominantly through interviews focused on countries such as Saudi Arabia, the UAE, Kuwait, and Egypt. Utilizing SPSS-V.25 for statistical analysis, this study uncovers the most prevalent and impactful causes of variations and claims, highlighting the critical need for managerial intervention. A key feature is the integration of scientometric analysis into a quantitative finding. Implementing a k-means clustering analysis is a significant addition to the methodology. The survey had high internal consistency with a Cronbach’s alpha of 0.97, and the respondents reported frequent and significant claims such as delayed drawings, ambiguous documents, and client changes. The results showed that effective claims management requires clear communication and balanced contracts, while poor design and contract documentation cause variations and claims. The correlation analysis showed strong positive correlations between claim types and causes. To reduce claims and address these factors, most respondents said the survey could predict and reduce claims.

The construction industry faces persistent challenges from disputes and claims, leading to delays, cost overruns, and strained stakeholder relationships. This study proposes a strategic framework that integrates building information modeling (BIM) as a proactive tool for dispute avoidance. Using a causal loop diagram (CLD), the research maps the relationships among systemic factors contributing to disputes, such as poor communication, ambiguous specifications, and ineffective stakeholder engagement. The study highlights BIM’s transformative potential in enhancing visualization, improving collaboration, and fostering proactive conflict resolution. Validated through expert insights, the framework provides actionable recommendations for integrating BIM (with ISO19650 specs) into construction workflows, addressing the root causes of disputes, and driving project efficiency. This research contributes a structured roadmap for advancing construction management practices, emphasizing early BIM adoption considered with ISO19650, stakeholder alignment, and balancing systemic dynamics. The findings underscore BIM’s pivotal role in reshaping conflict prevention strategies, paving the way for sustainable and dispute-free project delivery.

The construction industry builds infrastructure and strengthens the global economy, but it struggles with cost overruns. This systematic study uses scientometrics and Social Network Analysis to examine the multifaceted factors causing construction project cost escalations. After reviewing 405 scholarly works, the research maps and analyzes 66 interconnected cost overrun factors in 69 high-impact studies between 200 and 2024. To uncover the patterns, the study used two main research methods. First, this study applied a scientometric analysis that reviews trends and gaps from the previous studies. Second, this study used Social Network Analysis (SNA) to examine how different factors are connected and which factors have the strongest influence on cost overruns. The methodology comprises a systematic literature search, document selection, scientometric analysis, factor standardization, and SNA application. Seven critical drivers with high network centrality were identified: planning and scheduling issues, project estimation inaccuracies, design inefficiencies, negative weather conditions, scope definition challenges, contractual ambiguities, and unforeseeable site conditions. By applying SNA Degree Centrality (DC) the analysis quantifies the significance of each factor within the network. With the use of this dual analysis, a novel mapping of the main causes of cost overrun was produced, leading to the discovery of 7 core factors that significantly affected project outcomes, including planning and scheduling issues, project estimation problems, and design inefficiencies. The findings advanced the knowledge of the dynamics of cost overrun and offered practical insights for enhancing cost management practices in the construction industry.