Improving Loops that Matter

William Schoenberg; John Hayward; Robert Eberlein

doi:10.1002/sdr.1728

journal article Open Access Jan 26, 2023

Improving Loops that Matter

William Schoenberg

John Hayward

Robert Eberlein

System Dynamics Review Vol. 39 No. 2 pp. 140-151 · Wiley

View at Publisher Save 10.1002/sdr.1728

Abstract

AbstractThe Loops that Matter (LTM) approach to understanding behavior has proven easy to use and broadly applicable, but it has a shortcoming in its original formulation. This is because the original formulation treats the impact of a flow on a stock relative to the net flow, so that all scores tend to get very large in magnitude as a stock approaches equilibrium, but how big depends strongly on how the flows are specified. By reformulating the link scores from a flow to a stock, this topological dependency is removed. The mathematics behind this approach makes clear the relationship of LTM to the Pathway Participation and Loop Impact analysis methods. The result of this, when applying the analysis to a variety of models, is that the determination of the structure responsible for behavior is clearer, and more clearly tied to work already documented using other techniques. © 2023 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

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Metrics

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Citations

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References

Details

Published: Jan 26, 2023
Vol/Issue: 39(2)
Pages: 140-151
License: View

Authors

W

William Schoenberg

System Dynamics Group, Department of Geography University of Bergen Fosswinckelsgt. 6, Postboks 7802 Bergen N‐5020 Norway; isee systems inc. Lebanon, New Hampshire USA 24 Hanover St, Ste 8A Lebanon New Hampshire 03766 USA

J

John Hayward

School of Computing and Mathematics University of South Wales Pontypridd CF37 1DL UK

R

Robert Eberlein

isee systems inc. Lebanon, New Hampshire USA 24 Hanover St, Ste 8A Lebanon New Hampshire 03766 USA

Cite This Article

William Schoenberg, John Hayward, Robert Eberlein (2023). Improving Loops that Matter. System Dynamics Review, 39(2), 140-151. https://doi.org/10.1002/sdr.1728

Improving Loops that Matter

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