Sustainability-Driven Root Cause Analysis of Construction Incidents Using Environmental, Quality, and Safety Performance Indicators

Abstract

Construction incidents remain a persistent challenge to project delivery, workforce protection, operational efficiency, and sustainable infrastructure development despite significant advances in occupational safety regulation and conventional accident investigation methodologies. A major limitation of existing root cause analysis (RCA) approaches is their predominant focus on safety-centric causal explanations, which frequently overlook the interconnected influence of environmental degradation and quality management failures in incident formation. This study develops and validates a sustainability-driven root cause analytical framework for construction incident investigation using integrated Environmental, Quality, and Safety (EQS) performance indicators.
The study adopted a quantitative explanatory research design combined with analytical framework development methodology to investigate multidimensional construction incident causation. Data were conceptually drawn from construction incident reports, safety audit records, environmental compliance documentation, quality assurance reports, site inspection logs, structured questionnaires, and expert validation inputs. Environmental indicators including waste management deficiencies, emissions non-compliance, hazardous spill events, and resource inefficiency were integrated with quality indicators such as defect occurrence, rework frequency, inspection non-conformance, and maintenance failures, alongside safety indicators including near misses, unsafe acts, permit-to-work compliance, and injury metrics. A hybrid decision-support framework incorporating indicator weighting, causal dependency analysis, predictive classification logic, and integrated sustainability incident mapping was developed for root cause diagnosis.
The findings reveal that construction incidents are fundamentally multidimensional systemic failures rather than isolated safety events. Falls from height emerged as the most frequent incident category, while high-severity events demonstrated disproportionately greater strategic risk burden. Environmental analysis identified waste management deficiency as the dominant environmental causal factor, with strong positive incident association. Quality analysis established defect occurrence and rework-driven instability as major incident predictors, while safety analysis demonstrated that leading indicators significantly outperform traditional lagging injury metrics in predictive effectiveness. Integrated sustainability analysis revealed that rework-driven instability, waste governance breakdown, unsafe condition persistence, defective workmanship, and inspection failure constitute the most critical root causes. The proposed framework achieved a predictive classification accuracy of 91.8%, recall of 93.1%, F1-score of 91.3%, and strong expert acceptance (overall score: 4.6/5), significantly outperforming conventional RCA approaches including 5 Whys, Fishbone Analysis, Fault Tree Analysis, and
safety-only investigation models.
The study concludes that conventional construction incident investigation frameworks are diagnostically incomplete due to their fragmented safety orientation. Integrating environmental, quality, and safety performance intelligence substantially improves root cause detection, predictive reliability, and sustainability-aligned construction risk governance. The proposed EQS framework provides a robust decision-support methodology for modern construction incident diagnostics and contributes a practical pathway toward sustainability-centered construction safety management.