2026-10-14T08:17:57Z https://api.figshare.com/v2/oai

oai:figshare.com:article/32641740 2026-10-01T16:20:55Z portal_1172 item_type_8 month_year_10_2026

Risk factors for delays in the GCC construction projects: mixed-methods evaluation and automated assessment tool. Mahmoud Mohamed Nasr Abdou Elshamy (24170211) PUREID: 656115635 Risk factors risk indentifications risk assessment construction projects gulf region thematic analysis structural equation modelling machine learning fisher's score feature selection technique Delays in construction projects are among the most critical challenges facing the Gulf Cooperation Council (GCC) construction industry. These delays not only lead to significant cost overruns and contractual disputes but also compromise the overall performance and delivery of large-scale, complex projects. The GCC region, characterised by its ambitious development plans and mega-projects, suffers from a high frequency of project delays due to its unique risk landscape. Despite previous studies on construction delays in the GCC, projects continue to experience delays, as these studies have several limitations: they often fail to fully address the region's risk landscape, rely on independent risk assessments while ignoring the effects of risk correlations, and lack practical risk management solutions that bridge the gap between research and industry. Therefore, the main aim of this study is to explore the risk factors that cause delays in construction projects in the GCC. To address this aim, the study pursues five objectives: (1) to investigate and identify significant risk factors contributing to delays; (2) to evaluate the relative impact of each risk; (3) to analyse the correlations among these risks; (4) to develop a practical risk management solution; and (5) to assess the usability and practicality of the developed solution through expert feedback. To achieve these objectives, the study adopted a comprehensive mixed-methods approach. Qualitative data were collected through 25 semi-structured interviews with construction professionals across the GCC and analysed using thematic analysis to gain in-depth insights into delay-related risks. This analysis revealed six main themes and twelve sub-themes, comprising 140 risk factors. These include the absence of 3D modelling/Building Information Modelling (BIM), issues in the testing and commissioning process, and deficiencies in developing a Project Management Information System (PMIS) and stage-gating processes. This was followed by a quantitative survey with 183 industry experts to assess the severity of the 140 risk factors using the Relative Importance Index (RII). The findings revealed that unclear project scope, selecting poorly qualified contractors, tight project durations, the absence of a qualified team to draft contracts, and delays in approving variation orders were among the most severe risks. To examine the correlations between risks, the study applied Structural Equation Modelling (SEM), while Machine Learning feature selection techniques (Fisher’s Score) were used for further validation. The correlation analysis showed that although safety, quality, and management risks may not be individually severe, their cumulative effect on project timelines is highly significant. Furthermore, a proof-of-concept methodology was adopted to develop and evaluate a new risk management solution tailored to the GCC construction context. The developed solution integrates project-specific parameters, such as project location, scale, type, and client category, to generate customised risk registers with dual risk-ranking mechanisms. Feedback from 12 GCC-based risk experts indicated a high level of usability and practicality, with average scores of 4.75 and 4.67 out of 5.0, respectively. The study offers several novel contributions. First, while previous studies only listed risk factors, this study used thematic analysis to provide deeper insight into the causes and impacts of each risk. Second, it introduces a phase-based categorisation of risks that aligns with the progressive elaboration of construction projects, enabling stakeholders to focus on each project phase effectively. Third, it introduces 54 previously undocumented risk factors, significantly contributing to the body of literature on project delays in the GCC. Moreover, this is the first study in the region to investigate correlations among risk factors using SEM and to analyse both individual and cumulative risk impacts. Lastly, it is also the first to develop a practical, context-specific risk management tool for the GCC, addressing the usability and accessibility limitations of global solutions. In conclusion, this study presents a region-specific, data-driven, and expert-validated risk management solution that bridges the gap between academic research and industry application. It empowers stakeholders to identify, assess, and manage delay-related risks more effectively. By highlighting the importance of risk correlations and offering a user-friendly solution designed specifically for the GCC, this study supports more proactive and informed decision-making, ultimately improving project delivery performance across the GCC. Thesis is embragoed until 31 December 2028. 2026-10-01T16:20:55Z Text Thesis 10.17034/32641740.v1 https://figshare.com/articles/thesis/Risk_factors_for_delays_in_the_GCC_construction_projects_mixed-methods_evaluation_and_automated_assessment_tool_/32641740 All Rights Reserved Open Access after 2028-12-31