Resilient Industrial Systems: A Complex System Perspective to Support Business Decisions

Industrial systems increasingly need to become more resilient to developments in their environment. To take the right decisions and improve their resilience, those companies need insight into the effects of resilience-enhancing actions. A substantial part of those actions' effects follow from the adaptation of the focal company's environment in response to its actions. The current, predominantly inward focused, perspective used to assess actions cannot be used to capture those indirect effects of an action. Therefore, this thesis addresses how we can conduct a more comprehensive assessment of a company's actions that can enhance its resilience. This research develops and tests a novel combination of theoretical perspectives to execute such a comprehensive assessment. In five case studies, with increasing complexity along several variables, we develop simulation models to assess a variety of possible resilience-enhancing actions. The outcomes of the case studies indicate that our combination of theoretical perspectives, operationalized in our models, can indeed capture the indirect effects of the assessed actions, and that including those indirect effects substantially influences the performance of the focal company. With this approach, companies can assess their proposed actions more comprehensively, enabling them to take actions that improve their resilience to the increasing volatility in industrial systems.