Session 15: Quantitative Systems Modeling Approaches
11:00 AM - 12:10 PM | Room 104
Combining System Dynamics Modeling with Other Methods: A Systematic Review
Mohammadreza Zolfagharian and Georges Romme
Eindhoven University of Technology
Many SD studies draw on multi-method approaches in order to demonstrate more profound articulation of complex problems and more robust policy analysis. However, there is not much knowledge on when and how to combine SD with other methods. Adopting an evidence-based systematic approach, we assess 37 studies that use SD modeling along with at least one other method. This review produces several insights and learnings. We conclude with suggestions for future research in this area.
Models, Hypotheses, and Ecological Theory: Can an Iterative Institutionalized Model-Making Research Program Help Bridge the Gap Between Empirical and Theoretical Ecology?
Stuart J. Whipple and Bernard C. Patten
University of Georgia
We propose that institutionalized model-making (IMM) can generate productive linkages between empirical studies and theory-based ecological modeling approaches, and provide for the construction and testing of model-based hypotheses about ecosystems. IMM prescribes the model as a multi-generational, iteratively developed asset of a research site. Models are made by collaborative teams of site scientists and stakeholders. Through building, using, evaluating, and modifying the same set of models, theorists and empiricists are provided with a powerful platform to build constructive interactions of theory building and empirical testing. IMM provides a large set of benefits to the research site and its scientists. Among these are social benefits of enhancing communication and collaboration, synthesizing coherent empirical and theoretical constructs through model construction, and future research benefits with models providing a tangible construct from which to create research proposals and direct future empirical and theoretical projects.
Principles of Participatory Ensemble Modeling to Study Complex Socioecological Systems
Arika Ligmann-Zielinska, Laura Schmitt Olabisi, Sandy Marquart-Pyatt, and Saweda Liverpool-Tasie
Michigan State University
Louie Rivers III and Jing Du
North Carolina State University
We propose three intertwined design principles to guide the development of policy-relevant models: legitimacy, parsimony, and practicality. Model legitimacy means that models incorporate the perspectives of all involved stakeholders. Model parsimony is necessary because legitimate models often result in a large number of overlapping system representations, which can be further simplified and grouped to minimize model complexity. To satisfy practicality, we need to maintain a certain level of uncertainty in models to provide means of comprehensive experimentation. Taken together, these principles form a framework that allows for synthesizing qualitative and quantitative information, enhancing both communication of critical societal problems and their potential solutions.