Abstract for: Crossing the Modeling Chasm from Qualitative Causal Loop Diagrams to Simulation Modeling

Causal loop diagrams (CLDs) are frequently used in participatory systems modeling for conceptualizing systems. Easy to learn and apply in practice, they generate rich conversations by stakeholders and help conceptualize system boundaries from an endogenous perspective. However, CLDs can be misleading and difficult to interpret into simulation models without the motivation and resources, contributing to a widening chasm between qualitative and quantitative system dynamics. CLDs represent an initial core feedback theory of a system with each concept representing a subsystem to be instantiated by auxiliary theories using a custom assembly of three generic structures. We illustrate the approach with a regional model of food systems CLD developed through a series of group model building workshops. We evaluate the model by comparing a series of “shock scenarios” as retrospective natural experiments. We were able to translate a CLD with 26 variables, 21 major balancing loops, and 12 major reinforcing loops into a system dynamics simulation model with user parameterized initial conditions in approximately two hours. Shock scenarios identify patterns of associations between variables that can be compared against data in the real systems. The resulting model highlights the sensitivity of results to initial conditions. Being able to move from initial conceptualization of systems using CLDs to an initial simulation scoping model in a structured approach where the boundary objects remain intact facilitates faster transition to understanding the implications of nonlinear interactions and identify limitations in the core feedback theory of a system. The use of standard pretested structures with interventions and loop switches exposes more options for exploring interventions. Implications and limitations are discussed.