Abstract
Despite its conceptual uncertainty, resilience is mostly about the measurement of capacity. Current studies confirm the importance of resilience measurement and the necessity to support policy makers with a measurement mechanism. A holistic approach considering the measurement of different resilience domains interactively and concurrently is the critical element in this endeavor. In parallel with the rise of popularity of resilience in international organizations, NATO has initiated a project with the objective to discover whether the resilience capacity of a country can be evaluated in a dynamic way via a prototype model execution. The implemented model running both baseline (without any shock) and extraordinary scenarios (with strategic shocks), clearly demonstrates its capacity to represent quantitatively the resilience related factors of a country in the complex operational environment. Moreover, the outputs of the model substantially comply with the resilience concept existing in the literature and NATO applications. One of the main strengths of the model is its almost infinite capacity to create various scenarios and make what-if analysis limited only by the current number of endogenous parameters of the model. It allows studying the secondary and the third order effects of events introduced in scenarios. The user interfaces (input and output dashboards) of the model help decision makers modify the values of selected endogenous parameters, see and compare the time-based values of the resilience factors, and doing so to evaluate risk related to the Area of Operations. Subject matter experts have validated the model and identified the main areas of improvement. The further development brings more countries to the model and implements an aggregation mechanism for output values of both resilience capacity and risk functions. The model will form the core of the NATO Resilience expert system.
Highlights
The concept of resilience has been defined in various forms and studied especially in natural disaster and hazards domains [1]
In order to reflect this nonlinear behaviour over time and to understand the complexity of the system, we have used system dynamics entities such as time and to understand the complexity of the system, we have used system dynamics entities such causal loops, modules, stocks, flows, and converters in the modeling process
The system dynamics technique operates continuously to achieve results with high precision Calculations are repeated at each unit of time, and each calculation depends on the previous one
Summary
The concept of resilience has been defined in various forms and studied especially in natural disaster and hazards domains [1]. Expressed by different terminologies, “resist”, “recover”, “adapt”, and “transform” [2,3,6,7] can generally be considered as the main pillars of the resilience concept There are both theoretical and practical studies in the literature using this modality. Literature review on resilience models for critical infrastructures highlights the importance of describing the complex interactions and dynamic behaviours Ran et al [4] highlight the need for more hypothesis/discovery-driven experiments against descriptive mapping exercises to understand better the mechanisms through which vulnerability and resilience shape the capacity to prepare for, respond to, and recover from disasters.
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