我们到了吗?饱和度分析作为系统动力学建模信心的基础,应用于使用定性数据的概念化过程

IF 1.7 3区 管理学 Q3 MANAGEMENT
Andrada Tomoaia‐Cotisel, Samuel D. Allen, Hyunjung Kim, David F. Andersen, Nabeel Qureshi, Zaid Chalabi
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引用次数: 0

摘要

饱和对于系统动力学来说是一个有用的概念,但它尚未被广泛探索或纳入建模过程。在本文中,我们将饱和描述为一个隐喻,意指系统的概念表述达到了研究目的,不再需要修改。当达到饱和状态时,有关该问题的其他数据将不会提供更多信息,从而表明额外的数据收集和分析可能是多余的。我们讨论了两种可视化技术,即 "饱和曲线 "和 "共同理解图",用于在使用因果循环图进行概念化时评估饱和度,并在一个案例中展示了这两种技术的应用。在系统动力学研究过程中使用饱和度分析有很多好处,包括:(i) 识别可能需要修改的模型结构;(ii) 观察证据对当前概念化的支持程度;(iii) 广泛反思;(iv) 记录重要的建模决策;(v) 可能改进问题陈述。© 2024 作者简介系统动力学评论》由 John Wiley & Sons Ltd 代表系统动力学学会出版。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Are we there yet? Saturation analysis as a foundation for confidence in system dynamics modeling, applied to a conceptualization process using qualitative data
Saturation is a useful concept for system dynamics, yet it has not been widely explored or integrated into the modeling process. In this article, we describe saturation as a metaphor describing the point at which a conceptual representation of a system meets the study purpose and no longer requires modification. When saturation is reached, additional data about the problem would not offer added information, thus indicating that additional data gathering and analysis would likely be redundant. We discuss two visualization techniques, “saturation curves” and “shared understanding diagrams,” for assessing saturation when conceptualizing with causal loop diagrams and show their application in a case example. Using saturation analysis during a system dynamics research process has many advantages, including: (i) identifying model structures potentially needing revisions, (ii) observing the extent to which evidence supports the current conceptualization, (iii) reflecting extensively, (iv) documenting important modeling decisions, and (v) potentially improving the problem statement. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.
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来源期刊
CiteScore
6.60
自引率
8.30%
发文量
22
期刊介绍: The System Dynamics Review exists to communicate to a wide audience advances in the application of the perspectives and methods of system dynamics to societal, technical, managerial, and environmental problems. The Review publishes: advances in mathematical modelling and computer simulation of dynamic feedback systems; advances in methods of policy analysis based on information feedback and circular causality; generic structures (dynamic feedback systems that support particular widely applicable behavioural insights); system dynamics contributions to theory building in the social and natural sciences; policy studies and debate emphasizing the role of feedback and circular causality in problem behaviour.
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