从大型访谈数据集构建因果循环图

IF 1.7 3区 管理学 Q3 MANAGEMENT
Pablo Newberry, Neil Carhart
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引用次数: 0

摘要

“解决不健康城市发展上游的根本原因”是一个跨学科的研究项目,旨在绘制和理解城市发展决策,可视化利益相关者的心理模型,并共同开发改善干预措施。该项目的主要数据是通过123个半结构化访谈收集的。本文应用、比较并讨论了构建因果循环图的方法的四种变体,以阐明心理模型和集体决策,该方法基于人工和半自动过程,应用于个人访谈记录和主题分析收集的数据集。它的结论是,虽然半自动方法在应用于大型数据集时比人工方法节省了一些时间,但在解释和包括主题分析边界的外围上下文变量时需要小心。关于自动化的决策取决于建模的目的。最后,文章建议未来的应用记录定量描述符,描述从大型定性数据集构建cld的过程。©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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constructing causal loop diagrams from large interview data sets
Abstract “Tackling the Root Causes Upstream of Unhealth Urban Development” is a trans‐disciplinary research project seeking to map and understand urban development decision‐making, visualise stakeholder mental models and codevelop improvement interventions. The project's primary data was gathered through 123 semistructured interviews. This article applies, compares, and discusses four variations on a method for constructing causal loop diagrams to illuminate mental models and collective decision‐making, based on manual and semiautomated processes applied to individual interview transcripts and datasets collected by thematic analysis. It concludes that while semiautomated approaches offer some time saving over manual approaches when applied to large data sets, care is required in interpreting and including peripheral contextual variables at the boundaries of the thematic analysis. Decisions regarding automation depend on the purpose of the modelling. Finally, the article recommends future applications record quantitative descriptors characterising the process of constructing CLDs from large qualitative data sets. © 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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