Systems thinking: Critical thinking skills for the 1990s and beyond

Richmond, Barry J.

doi:10.1002/sdr.4260090203

Cited by 456 publications

(389 citation statements)

References 2 publications

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“…Fortunately, computer simulation makes the task of solving these systems trivial. Currently available software allows people from grade school to chief executive to build and simulate dynamic systems of arbitrary complexity on their personal computers (Richmond 1993, Diehl 1992, Eberlein and Peterson 1992, Morecroft and Sterman 1992. Nevertheless, the art of model building remains difficult.…”

Section: Discussionmentioning

confidence: 99%

Effects of Feedback Complexity on Dynamic Decision Making

Diehl

Sterman

1995

Organizational Behavior and Human Decision Processes

372

278

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Section: Discussionmentioning

confidence: 99%

Effects of Feedback Complexity on Dynamic Decision Making

Diehl

Sterman

1995

Organizational Behavior and Human Decision Processes

372

278

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“…System dynamics practitioners promote the use diagrams to enable one to see a visual map of the interrelationships 9,10 Figure 1 is a causal loop that depicts the reinforcing process that leads to attrition from materials engineering (MATE). A causal loop diagram depicts the interrelationship between events.…”

Section: Principle 1: Everything Is Connectedmentioning

confidence: 99%

Global challenges as inspiration: A classroom strategy to foster social responsibility

2006

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“…Several authors have recognized participatory SD as an ingredient of mental model refinement (Richardson, et al, 1994;Vennix, 1996;Akkermans & Vennix, 1997;Richmond, 1993;Maani & Maharaj, 2004;Rouwette, et al, 2011;Black & Andersen, 2012). During the modeling workshops, participants undergo a paradigm shift in their understanding of how the real world works.…”

Section: Data Collection and Analysismentioning

confidence: 99%

Transforming food systems at local levels: Using participatory system dynamics in an interactive manner to refine small-scale farmers’ mental models

Kopainsky

Hager

Herrera

et al. 2017

Ecological Modelling

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AcknowledgementsWe are very grateful to the research assistants and field officers in Zambia for facilitating communication with farmers and the implementation of individual interviews as well as the participatory system dynamics model building workshops. Our sincere gratitude goes to the traditional leadership in the workshop communities for their support and to all the farmers who generously shared their time and insight with us. Funding sourcesWork on this article was supported by the Norwegian Research Council through the project "Simulation based tools for linking knowledge with action to improve and maintain food security in Africa" (contract number 217931/F10) and the Peder Sather Center for Advanced Study through the project "Knowledge analysis in coupled social-ecological systems. A pilot study in smallholder farmer communities in Zambia". The views and conclusions expressed in this paper are those of the authors alone and do not necessarily reflect the views of the funding sources. The funding sources had no role in study design, collection, analysis and interpretation of data, in the writing of this article or in the decision to submit this article for publication. Conflicts of interestThe authors declare no conflict of interest. AbstractFood systems will need to undergo considerable transformation. To be better prepared for and resilient to uncertainty and disturbances in the future, resource users and managers need to further develop knowledge about the food and farming system, with its dominating feedback structures and complexities, and to test robust and integrated system-based solutions. This paper investigates how participatory system dynamics modeling can be adapted to groups at the community level with low or no formal educational background. The paper also analyses the refinement of workshop participants' mental models as a consequence of a participatory system dynamics intervention. For this purpose, we ran two workshops with small-scale farmers in Zambia. Analysis of workshop data and postworkshop interviews shows that participatory system dynamics is well adaptable to support an audience-specific learning-by-doing approach. The use of pictures, objects and water glasses in combination with the basic aspects of causal loop diagramming makes for a wellbalanced toolbox. Participants acquire understanding that is also relevant beyond systems thinking in that it offers a range of practical insights such as a critical evaluation of common food security strategies.

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Systems thinking: Critical thinking skills for the 1990s and beyond

Cited by 456 publications

References 2 publications

Effects of Feedback Complexity on Dynamic Decision Making

Effects of Feedback Complexity on Dynamic Decision Making

Global challenges as inspiration: A classroom strategy to foster social responsibility

Transforming food systems at local levels: Using participatory system dynamics in an interactive manner to refine small-scale farmers’ mental models

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