加强薄弱环节:因果循环图的透明度——现状和建议

IF 1.7 3区 管理学 Q3 MANAGEMENT System Dynamics Review Pub Date : 2023-11-12 DOI:10.1002/sdr.1753
Mohammad S. Jalali, Elizabeth Beaulieu
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引用次数: 0

摘要

透明是系统科学的一个重要方面。虽然对定量模型的透明度进行了评估,但对其定性结构的透明度审查较少。我们评估因果循环图(CLDs)的透明度,一个关键的定性可视化工具在系统动力学。我们评估了《系统动力学评论》(SDR)上的出版物和其他期刊上被引用次数最多的可比文章样本。我们评估了包括一个简单的语言方法声明,方法的整体可辨性,以及因果关系来源的识别。审稿72篇(SDR: 36篇;其他期刊:36),分别只有44%、38%和25%完全满足每项标准。SDR条款的特点是在CLD开发方法的清晰度和因果关系来源的沟通方面具有更高的透明度,但增强的潜力是显而易见的。我们提供了具体的建议,以提高cld的透明度。透明报告有利于原始研究作者、cld的未来扩展和系统科学界。©2023作者。John Wiley &出版的《系统动力学评论》;儿子有限公司代表系统动力学学会。
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Strengthening a weak link: transparency of causal loop diagrams — current state and recommendations
Abstract Transparency is a critical aspect of systems science. While transparency of quantitative models has been assessed, transparency of their qualitative structures has been less scrutinized. We assess the transparency of causal loop diagrams (CLDs), a key qualitative visualization tool in system dynamics. We evaluate System Dynamics Review ( SDR ) publications and a sample of most‐cited comparable articles in other journals. We assess the inclusion of a plain‐language methods statement, overall discernibility of the methods, and identification of causal link sources. Reviewing 72 articles ( SDR : 36; other journals: 36), only 44%, 38%, and 25% fully satisfy each criterion, respectively. SDR articles are characterized by higher transparency in the clarity of CLD development method and communication of causal link sources, yet the potential for enhancement is evident. We provide specific recommendations to increase the transparency of CLDs. Transparent reporting benefits original research authors, future expansion of CLDs, and the systems science community. © 2023 The Authors. 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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