Decision-Making in Natural Disaster Response: A Comprehensive Review of Strategies, Models, and Technological Advancements

Vian Ahmed; Zied Bahroun; Omar Abdulkarim; Hamdan Alteneji

doi:10.31181/dmame8220251490

Authors

Vian Ahmed Department of Industrial Engineering, Faculty of Engineering, American University of Sharjah, Sharjah, UAE https://orcid.org/0000-0002-1176-6509
Zied Bahroun Department of Industrial Engineering, Faculty of Engineering, American University of Sharjah, Sharjah, UAE. https://orcid.org/0000-0003-2832-3672
Omar Abdulkarim Department of Industrial Engineering, College of Engineering, American University of Sharjah, Sharjah, UAE. https://orcid.org/0009-0006-8313-6991
Hamdan Alteneji Sharjah Head-Quarter Police, Sharjah, UAE https://orcid.org/0009-0003-4671-6848

DOI:

https://doi.org/10.31181/dmame8220251490

Keywords:

Disaster Response Decision-Making; Emergency Management Strategies; Response Models in Disaster Management; Systematic Review in Disaster Response

Abstract

Natural disasters such as hurricanes and earthquakes cause extensive damage, requiring effective decision-making frameworks during emergency responses. Disaster management traditionally involves four phases: Mitigation, Preparation, Response, and Recovery. This study focuses on the Response phase, aiming to evaluate and categorise existing disaster response models to enhance decision-making and address challenges during this critical period. Employing bibliometric analysis and systematic content review of 86 scholarly works, the study identifies key patterns, research gaps, and challenges in disaster response. Bibliometric methods reveal global research trends and collaboration networks, while content analysis uncovers recurring themes in decision-making, resource allocation, and communication. The findings highlight a shift towards technology-driven frameworks, including IoT, remote sensing, augmented reality, and blockchain, which aid real-time decisions and resource management. However, limitations remain in developing adaptive decision-support systems and fostering multi-stakeholder collaboration. Furthermore, low international co-authorship—especially among researchers from disaster-prone regions—indicates scope for enhanced global cooperation. The study recommends greater adoption of emerging technologies and strengthened international partnerships to improve disaster response effectiveness. Its systematic classification of response models offers a practical tool for advancing evidence-based decision-making and capacity building in emergency management.

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References

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