Figure 1. Methodology Source: Authors’ own work A flowchart shows a mixed approach from literature analysis to conclusions and future work. The process starts with systematic literature analysis, then gap identification and research objectives, then development of theoretical propositions. ... More about this image found in Methodology Source: Authors’ own work A flowchart shows a mixed appro...

Figure 2. RII-based validation of research components: (a) drivers, (b) challenges, (c) benefits and (d) techniques Source: Authors’ own work A set of 4 bar charts shows R I I values for factors, barriers, outcomes, and V E tools. The 4 horizontal bar charts use values from about 0.70 to 0.... More about this image found in RII-based validation of research components: (a) drivers, (b) challenges, (...

Figure 3. Application of: (a) tools at various construction stages (in percentage) and (b) 3R at various construction stages (in %) Source: Authors’ own work A pair of radar charts compares digital tools and 3 R strategies across project stages. The panel a radar chart compares planning and... More about this image found in Application of: (a) tools at various construction stages (in percentage) an...

Figure 4. Heatmap of drivers, challenges, tools and benefits across project stages Source: Authors’ own work A heat map shows importance scores for factors across planning, design, construction, and operation. The heat map lists project stages as planning, design, construction, and operatio... More about this image found in Heatmap of drivers, challenges, tools and benefits across project stages ...

Figure 1. Enablers for qualitative design and construction outcomes in AEC projects Source: Authors’ own work [adapted from Royal Institute of British Architects, Chartered Institute of Building and Royal Institution of Chartered Surveyors (2019) ] Design management functions include crea... More about this image found in Enablers for qualitative design and construction outcomes in AEC projects...

Figure 2. Research methodology used in the study Source: Authors’ own work Flowchart outlining the process for identifying, ranking, and analysing design management risks affecting high-rise residential construction projects. The flowchart begins with Start and proceeds through a literature... More about this image found in Research methodology used in the study Source: Authors’ own work Flow...

Figure 3. Classification of respondents as per category, designation and work experience Source: Authors’ own work Horizontal bar charts show respondent designation, experience, and category distributions, with Senior-level respondents and respondents with over 15 years of experience forming... More about this image found in Classification of respondents as per category, designation and work experie...

Figure 4. Graphical model showing the relationships between the risk factors Source: Authors’ own work Multi-level structural model showing relationships among factors A 1 to G 4 distributed across 14 hierarchical levels. The hierarchical structural model displays 14 levels labelled Level 1... More about this image found in Graphical model showing the relationships between the risk factors Source...

Figure 5. Classification of risk factors as per RPN and Driving Power Source: Authors’ own work Scatter plot classifies factors A 1 to G 4 by driving power and risk priority number into very low, low, medium, high, and very high impact zones. The scatter plot displays Driving Power on the... More about this image found in Classification of risk factors as per RPN and Driving Power Source: Au...

Figure 1. High-level flowchart of the proposed framework for hazard cascade prediction, detailing the end-to-end pipeline from raw OSHA incident data acquisition and NLP-based semantic categorization to dynamic temporal graph construction and GNN-based link prediction Source: Authors’ own wor... More about this image found in High-level flowchart of the proposed framework for hazard cascade predictio...

Figure 2. Elbow method for K-Means clustering Note(s): The plot of inertia versus the number of clusters (k) shows a distinct elbow at K = 21, guiding the selection of the optimal number of hazard super-categories Source: Authors’ own work A line chart showing the elbow method used to sel... More about this image found in Elbow method for K-Means clustering Note(s): The plot of inertia versus ...

Figure 3. Frequency distribution of the 21 identified hazard categories across the 17,194 OSHA incident narratives (2015–2025) Source: Authors’ own work A horizontal bar chart ranking construction hazard super-categories by incident frequency within the dataset. The horizontal bar chart d... More about this image found in Frequency distribution of the 21 identified hazard categories across the 17...

Figure 4. Heatmap of sequential hazard co-occurrences Note(s): Cell intensity represents the absolute frequency of a directed spatiotemporal cascade transitioning from an initial source hazard (x-axis) to a subsequent destination hazard (y-axis) within a 30-day window Source: Authors’ own work A heat map showing co-occurrence frequencies and relationships among construction hazard categories. The heat map presents pairwise co-occurrence frequencies between hazard categories listed on both the x-axis and y-axis. Higher intensity values indicate stronger associations between hazard categories, while lower intensity values indicate weaker relationships. Strong co-occurrence patterns are observed among Fall From Height, Construction Materials, Manual Handling Task, and Caught In Between hazards. Moderate relationships appear among Assembly Demolition Task, Cutting Welding Task, and several material-related and equipment-related hazards. Lower co-occurrence frequencies are associated with Chemical and Toxic Substances, Environmental Conditions, and Guardrail Fall Protection Failure. The matrix highlights interaction patterns and dependencies among construction hazards. More about this image found in Heatmap of sequential hazard co-occurrences Note(s): Cell intensity repr...

Figure 5. Sensitivity analysis of the temporal co-occurrence window Source: Authors’ own work A line chart showing mean reciprocal rank performance across cascade definition time windows from 7 to 60 days. The line chart plots mean reciprocal rank on the y-axis against cascade definition ti... More about this image found in Sensitivity analysis of the temporal co-occurrence window Source: Author...

Figure 6. Model predictability relative to hazard frequency Note(s): The chart plots the average prediction rank for each specific destination hazard against its total occurrence frequency in the test set, illustrating that common physical hazards are predicted with significantly higher accurac... More about this image found in Model predictability relative to hazard frequency Note(s): The chart plo...