Development of Disaster Demand Matrix for Bangladesh

Abstract

Bangladesh, as one of the world's most hazard-vulnerable nations, experiences recurrent cyclone disasters that devastate coastal populations, livelihoods, and critical infrastructure, particularly in its densely populated littoral regions. While conventional disaster response mechanisms have achieved notable successes in casualty mitigation over recent decades, multifaceted gaps persist across the disaster management continuum, encompassing mitigation, preparedness, response, and recovery phases. These operational deficiencies reflect misalignment between national disaster management capacities and internationally established best practices, creating systematic barriers to comprehensive risk reduction and resilience augmentation. This doctoral research addresses this fundamental challenge through development of an evidence-based Disaster Demand Matrix (DDM) framework, systematically identifying and quantifying critical unmet demands across Bangladesh's cyclone disaster management architecture. The study employs an integrative methodological approach combining multiple investigative dimensions. First, empirical analysis of four decades of cyclone data (1982–2024) establishes contemporary cyclone activity patterns and intensity trends affecting Bangladesh's coastal zone. Second, systematic comparative analysis of Bangladesh's existing disaster management practices against globally established best practices across thirteen cyclone-prone nations identifies substantive implementation gaps, institutional coordination deficiencies, and policy-practice divergences. Third, the research develops a comprehensive Disaster Demand Matrix encompassing nine major disaster management domains, comprising mitigation, preparedness, early warning, evacuation, emergency response, damage assessment, healthcare provision, recovery operations, and long-term reconstruction that systematically quantifies performance gaps between optimal operational standards and prevailing local realities. To establish strategic prioritization among ninety multifaceted disaster management sub-activities, the research applies the Fuzzy Analytical Network Process (FANP) methodology, a sophisticated multi-criteria decision-making technique accommodating criterion interdependencies, decisionmaker uncertainty, and complex priority interactions. This rigorous prioritization exercise synthesizes expert professional judgment from academicians, government functionaries, and iii emergency management practitioners, yielding analytically derived hierarchical rankings of critical interventions requiring prioritized resource allocation and institutional development. The prioritization results reveal that information dissemination and community risk communication systems constitute the paramount intervention priority, followed sequentially by spatially resolved evacuation coordination mechanisms, continuous meteorological monitoring with predictive analytics capabilities, and comprehensive community-level hazard awareness programming. These priority activities, representing foundational demand-driven interventions, collectively address systemic preparedness deficiencies, reduce information asymmetries, and enhance population protective action capacity, thereby generating multiplicative risk reduction benefits across all subsequent disaster management phases. Beyond these principal findings, the research identifies priority institutional capacity-building requirements, governance-level coordination mechanisms, and policy-implementation frameworks necessary for effective DDM operationalization. The framework explicitly acknowledges methodological limitations, including constraints regarding empirical field-level validation, expert-judgment subjectivity, geographic specificity to coastal cyclone contexts, technical accessibility barriers for frontline practitioners, and data integration limitations, while simultaneously delineating prospective research trajectories for methodological extension and practical framework advancement. Ultimately, this research contributes a novel, systematically derived decision-support instrument enabling Bangladesh's disaster management community to allocate resources strategically, prioritize institutional development investments, and align policy interventions toward addressing the most consequential unmet demands within the disaster management system. By facilitating demand-driven, evidence-based disaster management planning, the Disaster Demand Matrix framework supports sustainable resilience enhancement, accelerated emergency response effectiveness, and expedited recovery processes benefiting Bangladesh's climate-vulnerable coastal populations and contributing toward attainment of global Sendai Framework disaster risk reduction objectives.