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Network-based safety risk analysis and interactive dashboard for root cause identification in construction accident management

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  • Kumi, Louis
  • Jeong, Jaewook
  • Jeong, Jaemin
  • Son, Jaehui
  • Mun, Hyeongjun

Abstract

Construction projects are characterized by dynamic environments where numerous safety risks interact, leading to high rates of accidents and fatalities. Traditional safety analysis methods often overlook these complex relationships, hindering effective risk mitigation strategies. This study uses graph theory and network analysis to analyze the interconnectivity of safety factors in construction incidents. Using a dataset of injury and fatal accident cases, a network was constructed to represent safety factors and their co-occurrences. Centrality measures were applied to identify influential factors, while the Louvain algorithm facilitated community detection. The results identified PM10 groups (air quality) and temporal factors (specific times of day) as key risks. Three major clusters of safety factors were also detected, representing environmental, incident-related, and demographic influences. An interactive dashboard was developed for scenario simulation, allowing construction professionals to visualize the effects of removing key factors from the network. These findings offer a practical framework for targeted safety interventions and real-time management of construction risks. The study concludes that integrating graph theory into construction safety analysis can provide a more comprehensive approach to accident prevention by focusing on interconnected risk factors rather than isolated incidents.

Suggested Citation

  • Kumi, Louis & Jeong, Jaewook & Jeong, Jaemin & Son, Jaehui & Mun, Hyeongjun, 2025. "Network-based safety risk analysis and interactive dashboard for root cause identification in construction accident management," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:reensy:v:256:y:2025:i:c:s0951832025000171
    DOI: 10.1016/j.ress.2025.110814
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    6. Moslem, Sarbast & Gholamizadeh, Kamran & Zarei, Esmaeil & Pasman, Hans J & Martinez-Pastor, Beatriz & Pilla, Francesco, 2025. "A comparative assessment of domino accident analysis methods in process industries using LMAW and DNMA techniques," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    7. Sarmah, Achinta Kr. & Dhalmahapatra, Krantiraditya, 2026. "Enhancing safety management: A data-driven approach for accident mitigation in a steel industry," Reliability Engineering and System Safety, Elsevier, vol. 268(C).
    8. Cao, Kunyu & Chen, Shu & Chen, Yun & Nie, Benwu & Li, Zhi, 2025. "Decision analysis of safety risks pre-control measures for falling accidents in mega hydropower engineering driven by accident case texts," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    9. Sun, Xufeng & Wang, Wanqing & Liu, Jie & Yao, Xiuyi, 2026. "Construction and application of a building construction safety risk assessment model based on combined weighting and an improved discrete Hopfield neural network," Reliability Engineering and System Safety, Elsevier, vol. 266(PB).

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