Co-creating evidence-based business roadmaps and policy solutions for enhancing coastal-rural collaboration and synergies

System Dynamics Modelling: Capturing complexity in COASTAL for rapid policy/business analysis

Coastal areas are environmentally fragile but also attractive areas where business opportunities in many sectors are dependent on the environmental qualities affected by activities in hinterlands. 

The COASTAL project applies Systems Dynamics modelling (SD modelling), as a key method to analyze and understand the functioning of the coastal-rural system, to explore scenarios and transition pathways on how territorial governance approaches and cross-sectoral economic development approaches could deliver mutually beneficial impacts for rural territories and coastal areas and seas.

System Dynamics or SD modelling is widely used since the 1950s for problem analysis in applications ranging from logistics, control management, engineering and financial management to public policy. They include the quantification of relationships and allow explaining the underlying dynamics of the problem. 
Typical questions answered are: why do certain businesses fail and others not under similar circumstances? Why do certain management strategies work on the short term, but not on the long term? Although the human brain is capably of providing part of the answer this becomes more difficult when multiple factors play a role. This is certainly true for complex social-environmental systems such as coastal regions which are densely used and rapidly developing, with economic activities competing for resources such space, water, and skilled labour. 

A tutorial example was demonstrated during the project kick-off meeting, showing the interaction between tourism, pressure on space and the attractiveness of  a coastal region for new tourists. This model shows that limiting the total number of tourists can be necessary to avoid economic collapse of tourism. The true strength of SD modelling lies in the transparency of the graphical models, enabling interactive design and use of the models, the limited data requirements and high computing speed. 

In coastal, SD models will be used to understand and quantify the relationships that result from the multi-actor labs. During the coming months these relationships are transferred in Causal Loop Diagrams, which in turn will be quantified and turned into SD models. We specifically aim at SD models that have a high added value for concrete applications, such as understanding the different effects of transition pathways. Because of the complicated coastal and rural interactions in the different case studies of COASTAL, SD models are the ideal tool to capture the complexity while still allowing to make data understandable.