International Journal of Advanced Multidisciplinary Research and Studies
Volume 6, Issue 5, 2026
The Application of Total Quality Management (TQM) Approaches to Disaster Risk Reduction and Recovery in Nigeria
Author(s): Godspower Imiete, Sunny O Asomaku, Abiye Tomquin, Geoffrey Ebe, Victoria O Emelu, Perri Tamuno-Owunari
Abstract:
Nigeria has lived with floods, erosion, drought, pollution and conflict-driven displacement for decades, yet the performance of its disaster programmes is still judged more by activity than by the reliability of results. This article asks whether the principles and tools of Total Quality Management (TQM) can make disaster risk reduction (DRR) and recovery more dependable. Using a structured narrative review of the quality-management and disaster-management literatures, together with a descriptive analysis of figures published by the National Emergency Management Agency (NEMA) for the 2022, 2024 and 2025 flood seasons, we map eight TQM principles onto the disaster cycle, derive a Plan–Do–Check–Act (PDCA) framework for Nigerian agencies, and identify six institutional barriers to adoption. Three findings stand out. First, official casualty and displacement totals moved by a factor of several within weeks of the 2022 floods, and figures attributed to NEMA for 2024 differ markedly by source, which points to a weak measurement system. Second, forecasts and warnings were issued, but action at the last mile and the operation of dams did not follow the same discipline. Third, the barriers are largely managerial rather than technical. We propose a five-level maturity ladder for self-assessment and six testable propositions. The study is conceptual and relies on secondary data; it offers a structure for empirical work rather than a final verdict. The implications reach federal and state emergency agencies, dam operators and industry–community partnerships in the Niger Delta.
Keywords: Total Quality Management, Disaster Risk Reduction, Disaster Recovery, PDCA, Data Quality, Flood Management, Nigeria, Sendai Framework
Pages: 1717-1724
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