Modeling dynamic resilience in coupled technological-social systems subjected to stochastic disturbance regimes

Resilience of engineered systems is measured by the ability to anticipate, prepare for, recover, learn, and improve from an external disturbance regime that comprises of a series of chronic low-intensity and infrequent acute shocks, which disrupt functionality. Here, we present a new systems-level model for coupled technological systems, which provide functionality, and social systems in charge of management. Each system is characterized by a single, aggregated, dynamic state variable, namely (1) critical service deficit, representing services/functionality not provided by the technological system to match demands, and (2) adaptive capacity, representing total resources available to the managing/social institutions to maintain and repair critical services. These coupled systems are subjected to an external stochastic disturbance regime (Poisson shocks), and temporal perturbations in the two state variables are simulated. We use this “toy” model to simulate four hypothetical scenarios to illustrate likely coupled system temporal trajectories and shifts between a desirable (full service) and an undesirable (limited service) regime or complete system collapse (no service, no adaptive capacity). We also present several quantitative approaches to assess time series data and examine coupled systems dynamics. Resilience of the coupled systems for coping with and recovering from service losses is a dynamic property, contingent on system parameters that define the initial conditions before the shocks and recovery, and the frequency and magnitude of shocks.