The development of a sustainable institutional resilience index in disaster management: The case of Turkey's AFAD

Institutions are the fundamental building blocks for coping with disasters and emergencies. Institutional inadequacies not only cause emergencies to escalate into disasters but also intensify their economic, social, and physical impacts. Although there is a broad literature on disaster resilience, there is still a lack of quantitative assessment studies focusing specifically on institutional resilience in disasters and examining the factors that influence how institutions respond to disaster situations. Therefore, this study developed the Institutional Resilience Index (IRI) model to evaluate the organizational preparedness level of institutions against disasters and emergencies. The 55 factors influencing institutional resilience were identified through expert opinions using the Delphi method. The developed IRI model was tested at the provincial level in the case of the Disaster and Emergency Management Authority (AFAD) under both retrospective and possible future disaster scenarios. In the first scenario, the institutional resilience of AFAD provincial directorates involved in response activities during the magnitude 7.7 and 7.6 earthquakes that occurred in Kahramanmaraş on February 6, 2023, was evaluated. In the second scenario, the institutional resilience of AFAD provincial directorates in Erzincan, Tunceli, and Bingöl—located on the Yedisu Fault Zone—was analyzed under a potential future earthquake scenario. The ranking results obtained from the IRI model were validated by comparing them with the TOPSIS and MARCOS methods, and a sensitivity analysis was conducted using Monte Carlo simulation to examine the effects of variations in criteria weights on the ranking outcomes. As a result, it was concluded that the developed index is applicable for assessing the resilience levels of institutions responsible for disaster management. Additionally, the index provides a decision-support mechanism for understanding past disaster experiences and identifying priority actions at the policy and operational levels by predicting vulnerability factors for future disaster scenarios. Thus, the proposed model can serve as a strong catalyst for institutional learning and can be used as a tool to enhance organizational preparedness.