JOURNAL ARTICLE

Employing a Mental Model Framework to Explore Systems Thinking.

  • Published In: Systems Research & Behavioral Science, 2025, v. 42, n. 6. P. 1875 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Schaffernicht, Martin F. G.; López‐Astorga, Miguel; Rojas‐Barahona, Cristian A.; Castillo, Ramón D. 3 of 3

Abstract

This article conceptualizes systems thinking from the perspective of mental models. It portrays systems thinking as a combination of perception, prior knowledge and reasoning processes for guiding decision‐making in complex, dynamic situations. Systems thinking is mostly considered as a skill, and assessment instruments are based on the observable products of thinking. However, there is a lack of research on the cognitive processes involved in generating mental representations of complex dynamic systems, deriving possible behaviours and decisions. Thus, we propose a conceptual framework that combines mental models of dynamic systems and the cognitive theory of reasoning with mental models of possibilities. This theory identifies an intuitive and a deliberative reasoning process describing how the deliberative process influences the mental model of the perceived situation. While remaining compatible with the existing literature on systems thinking, this framework addresses this gap. Through examples, the study illustrates how the distinct levels of systems thinking knowledge of three stylized agents lead to different models, even when the reasoning process is identical. Boundary mismatch errors in the represented structure lead to errors in judging‐system behaviours as necessary, possible or impossible, leading to different decisions. Based on this finding, several new research questions are proposed concerning the dynamics of the cognitive processes and mental models over the iterations of dynamic decision‐making in laboratory experiments. We close with a call for more research to move beyond the current limitations. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Systems Research & Behavioral Science. 2025/11, Vol. 42, Issue 6, p1875
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1092-7026
  • DOI:10.1002/sres.3125
  • Accession Number:190385078
  • Copyright Statement:Copyright of Systems Research & Behavioral Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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