A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction
Growing complexity represents an issue that can be identified in various disciplines. In system dynamics, causal loop diagrams are used for capturing dynamic nature of modelled systems. Increasing complexity of developed diagrams is associated with the tendency to include more variables into a model...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-07-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/5/3/46 |
| _version_ | 1797999282307989504 |
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| author | Vladimír Bureš |
| author_facet | Vladimír Bureš |
| author_sort | Vladimír Bureš |
| collection | DOAJ |
| description | Growing complexity represents an issue that can be identified in various disciplines. In system dynamics, causal loop diagrams are used for capturing dynamic nature of modelled systems. Increasing complexity of developed diagrams is associated with the tendency to include more variables into a model and thus make it more realistic and improve its value. This is even multiplied during group modelling workshops where several perspectives are articulated, shared and complex diagrams developed. This process easily generates complex diagrams that are difficult or even impossible to be comprehended by individuals. As there is a lack of available methods that would help users to cope with growing complexity, this manuscript suggests an original method. The proposed method systematically helps to simplify the complex causal loop diagrams. It is based on three activities iteratively applied during particular steps: endogenisation, encapsulation and order-oriented reduction. Two case studies are used to explain method details, prove its applicability and highlight added value. Case studies include the simplification of both original group causal loop diagram, and group diagram adapted from a study already published in a prestigious journal. Although the presented method has its own limitations, meaningfulness of its application in practice is verified. The method can help to cope with the complexity in any domain, in which causal loop diagrams are used. |
| first_indexed | 2024-04-11T11:02:10Z |
| format | Article |
| id | doaj.art-a87cdc6fa39644a68315224b50348101 |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-04-11T11:02:10Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-a87cdc6fa39644a68315224b503481012022-12-22T04:28:31ZengMDPI AGSystems2079-89542017-07-01534610.3390/systems5030046systems5030046A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented ReductionVladimír Bureš0Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 50003 Hradec Králové, Czech RepublicGrowing complexity represents an issue that can be identified in various disciplines. In system dynamics, causal loop diagrams are used for capturing dynamic nature of modelled systems. Increasing complexity of developed diagrams is associated with the tendency to include more variables into a model and thus make it more realistic and improve its value. This is even multiplied during group modelling workshops where several perspectives are articulated, shared and complex diagrams developed. This process easily generates complex diagrams that are difficult or even impossible to be comprehended by individuals. As there is a lack of available methods that would help users to cope with growing complexity, this manuscript suggests an original method. The proposed method systematically helps to simplify the complex causal loop diagrams. It is based on three activities iteratively applied during particular steps: endogenisation, encapsulation and order-oriented reduction. Two case studies are used to explain method details, prove its applicability and highlight added value. Case studies include the simplification of both original group causal loop diagram, and group diagram adapted from a study already published in a prestigious journal. Although the presented method has its own limitations, meaningfulness of its application in practice is verified. The method can help to cope with the complexity in any domain, in which causal loop diagrams are used.https://www.mdpi.com/2079-8954/5/3/46causal loop diagramcomplexityfeedback loopmethodmulti-input multi-outputsimplificationsystem dynamicsvariables |
| spellingShingle | Vladimír Bureš A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction Systems causal loop diagram complexity feedback loop method multi-input multi-output simplification system dynamics variables |
| title | A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction |
| title_full | A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction |
| title_fullStr | A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction |
| title_full_unstemmed | A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction |
| title_short | A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction |
| title_sort | method for simplification of complex group causal loop diagrams based on endogenisation encapsulation and order oriented reduction |
| topic | causal loop diagram complexity feedback loop method multi-input multi-output simplification system dynamics variables |
| url | https://www.mdpi.com/2079-8954/5/3/46 |
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