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针对高度复杂的多系统问题的参与式建模:平衡定性理解与定量问题的挑战与建议

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

作者信息

Deutsch Arielle R, Frerichs Leah, Perry Madeline, Jalali Mohammad S

机构信息

Avera Research Institute, Avera Health, Sioux Falls, SD, USA.

Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.

出版信息

Syst Dyn Rev. 2024 Oct-Dec;40(4). doi: 10.1002/sdr.1765. Epub 2024 Feb 22.

Abstract

Community stakeholder participation can be incredibly valuable for the qualitative model development process. However, modelers often encounter challenges for participatory modeling projects focusing on high-complexity, synergistic interactions between multiple issues, systems, and granularity. The diverse stakeholder perspectives and volumes of information necessary for developing such models can yield qualitative models that are difficult to translate into quantitative simulation or clear insight for informed decision-making. There are few reccomended best practices for developing high-complexity, participatory models. We use an ongoing project as a case study to highlight three practical challenges for tackling high-complexity, multi-system issues with system dynamics tools. These challenges include balanced and respectful stakeholder engagement, defining boundaries and levels of variable aggregation, and timing and processes for qualitative/quantitative model integration. Our five recommendations to address these challenges serve as a foundation for further research on methods for developing translatable qualitative multi-system models for informing actions for systemic change.

摘要

社区利益相关者的参与对于定性模型开发过程可能具有难以置信的价值。然而,建模人员在专注于多个问题、系统和粒度之间的高复杂性、协同相互作用的参与式建模项目中经常遇到挑战。开发此类模型所需的不同利益相关者观点和信息量可能会产生难以转化为定量模拟或难以获得清晰洞察以进行明智决策的定性模型。对于开发高复杂性、参与式模型,几乎没有推荐的最佳实践。我们以一个正在进行的项目作为案例研究,以突出使用系统动力学工具应对高复杂性、多系统问题的三个实际挑战。这些挑战包括平衡且尊重利益相关者的参与、定义变量聚合的边界和层次,以及定性/定量模型整合的时间安排和流程。我们针对这些挑战提出的五项建议为进一步研究开发可转化的定性多系统模型以指导系统性变革行动的方法奠定了基础。

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