Abstract for: Ethnography and Epistemological Uncertainty: An Integrative Methdology for Modeling Complex System Dynamics

Systems dynamics scholarship has explored the growing interest in qualitative data among modelers, and argued that qualitative data and analysis play an important role at each stage of the modeling process. Qualitative reasoning has been shown to be especially effective for representing and managing the kind of uncertainty known as “epistemic uncertainty,” which is associated with incomplete knowledge about a given process, and incomplete knowledge of the limits of one’s knowledge. Techniques such as mental modeling, which draw on qualitative data from in-depth open-ended interviews, have both complemented and extended quantitative modeling; aggregate and individual mental models offer a more nuanced understanding of nonlinear processes, and enable systemic analysis of complex and subjective decision-making (Whitley et al 2018). Participatory system dynamics modelling approaches attempt to address epistemic uncertainty through the incorporation of multiple points of view and types of expertise in the modelling process. This integration allows for participants in the modeling exercise to challenge, question, and augment one another’s knowledge of the complex system being modeled. These and other scholars have called for more systems dynamics research that combines qualitative and quantitative methods. Responding to this call, we propose that ethnography, as a unique qualitative methodology, can make valuable contributions to data collection and model building in systems dynamics, particularly under epistemic uncertainty.