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Detecting and monitoring change in models

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  • Martin Schaffernicht

Abstract

System dynamics is often brought into connection with a double‐loop learning process. Learning has been the object of an increasing number of studies. However, inquiry has focused on using models rather than modeling, and there are huge differences in assessment approaches. If learning changes models then it can be inferred from comparing models. Here it is argued that monitoring learning from modeling is feasible and desirable. One possibility is to conceive of a model as a series of versions and compare their structure. One possible method for comparing model versions is presented. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Martin Schaffernicht, 2006. "Detecting and monitoring change in models," System Dynamics Review, System Dynamics Society, vol. 22(1), pages 73-88, March.
  • Handle: RePEc:bla:sysdyn:v:22:y:2006:i:1:p:73-88
    DOI: 10.1002/sdr.329
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    Cited by:

    1. Kim, Sehoon & Connerton, Timothy Paul & Park, Cheongyeul, 2021. "Exploring the impact of technological disruptions in the automotive retail: A futures studies and systems thinking approach based on causal layered analysis and causal loop diagram," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    2. Raffaele Giordano & Elisabetta Preziosi & Emanuele Romano, 2013. "Integration of local and scientific knowledge to support drought impact monitoring: some hints from an Italian case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(1), pages 523-544, October.
    3. Raffaele Giordano & Marcela Brugnach & Irene Pluchinotta, 2017. "Ambiguity in Problem Framing as a Barrier to Collective Actions: Some Hints from Groundwater Protection Policy in the Apulia Region," Group Decision and Negotiation, Springer, vol. 26(5), pages 911-932, September.
    4. Novie Andri Setianto & Donald Cameron & John B. Gaughan, 2014. "Identifying Archetypes of an Enhanced System Dynamics Causal Loop Diagram in Pursuit of Strategies to Improve Smallholder Beef Farming in Java, Indonesia," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(5), pages 642-654, September.
    5. Schaffernicht, Martin F.G. & Groesser, Stefan N., 2014. "The SEXTANT software: A tool for automating the comparative analysis of mental models of dynamic systems," European Journal of Operational Research, Elsevier, vol. 238(2), pages 566-578.

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