dc.contributor.author | Schoenberg, William Alexander | |
dc.contributor.author | Eberlein, Robert | |
dc.contributor.author | Davidsen, Pål Ingebrigt | |
dc.date.accessioned | 2024-08-15T12:22:52Z | |
dc.date.available | 2024-08-15T12:22:52Z | |
dc.date.created | 2023-12-01T09:53:10Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 0883-7066 | |
dc.identifier.uri | https://hdl.handle.net/11250/3146586 | |
dc.description.abstract | Loops that Matter (LTM) provides a practical and comprehensive way to understand which feedback loops are driving model behavior at different points in time. LTM describes from which loops the observed change in behavior across all stocks in the model originate. In this paper we present a method to measure the magnitude of the change in behavior of all stocks in the model based on net flow values, relative to the magnitude of change taking place across an entire observation (simulation) period. We call this new metric the “system change”. We then demonstrate how our system change metric can be visualized using loop scores to highlight those loops that are predominantly responsible for the changes in behavior exhibited by the model. This helps analysts focus in on the feedback loops that are prime candidates for interventions to change the model behavior. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Wiley | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Measuring the change in behavior of a system with a single metric | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright 2023 The Author(s) | en_US |
dc.source.articlenumber | e1754 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.doi | 10.1002/sdr.1754 | |
dc.identifier.cristin | 2207146 | |
dc.source.journal | System Dynamics Review | en_US |
dc.identifier.citation | System Dynamics Review. 2023, 40 (1), e1754. | en_US |
dc.source.volume | 40 | en_US |
dc.source.issue | 1 | en_US |