Participatory Modeling for High Complexity, Multi-System Issues: Challenges and Recommendations for Balancing...

Area of Science:

• Systems Science
• Participatory Modeling
• Computational Social Science

Background:

• Community stakeholder participation enhances qualitative model development.
• Participatory modeling faces challenges with high-complexity, multi-system interactions.
• Translating qualitative models into quantitative simulations for decision-making is difficult.

Purpose of the Study:

• To highlight practical challenges in developing high-complexity, participatory models.
• To present recommendations for addressing these challenges in system dynamics projects.
• To provide a foundation for research on translatable qualitative multi-system models.

Main Methods:

• Case study of an ongoing participatory modeling project.
• Focus on system dynamics tools for high-complexity, multi-system issues.
• Identification of key challenges in stakeholder engagement and model integration.

Main Results:

• Three primary challenges identified: stakeholder engagement, boundary definition, and qualitative/quantitative integration.
• Recommendations provided to address these specific challenges.
• Emphasis on the need for best practices in complex participatory modeling.

Conclusions:

• Addressing engagement, boundaries, and integration is crucial for effective participatory modeling.
• Further research is needed on methods for developing translatable qualitative multi-system models.
• Improved models can inform actions for systemic change.