What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create

IF 1.7 3区管理学 Q3 MANAGEMENT

System Dynamics Review Pub Date : 2024-02-05 DOI:10.1002/sdr.1762

Asmeret Naugle, Saeed Langarudi, Timothy Clancy

{"title":"What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create","authors":"Asmeret Naugle, Saeed Langarudi, Timothy Clancy","doi":"10.1002/sdr.1762","DOIUrl":null,"url":null,"abstract":"A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics. © 2024 The Authors. <i>System Dynamics Review</i> published by John Wiley & Sons Ltd on behalf of System Dynamics Society.","PeriodicalId":51500,"journal":{"name":"System Dynamics Review","volume":"20 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"System Dynamics Review","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1002/sdr.1762","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}

引用次数: 0

Abstract

A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

查看原文本刊更多论文

什么是（定量）系统动力学建模？定义特征及其带来的机遇

对系统动力学建模的明确定义可以提供共同的理解并明确该领域的影响。我们介绍了一组定义定量系统动力学的特征，这些特征是为了捕捉核心理念、描述理论和实践原则、适用于历史工作，但又足够灵活，以便随着该领域的发展保持相关性。这些特征包括(1) 模型基于因果反馈结构，(2) 积累和延迟是基础，(3) 模型基于方程，(4) 时间概念是连续的，(5) 分析侧重于反馈动力学。我们讨论了这些原则的含义，并利用它们确定了系统动力学领域可以推进的研究机会。这些研究机会包括因果关系、分解、数据科学和人工智能，以及促进科学进步。这些领域的进展有可能改善系统动力学的科学和实践。© 2024 作者。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。

求助全文

约1分钟内获得全文求助全文

来源期刊

System Dynamics Review Multiple-

CiteScore

6.60

自引率

8.30%

发文量

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.