Abstract
Structuring and exploring complex problems is still one of the most significant challenges in strategic decision-making and management. On the one hand, we strive to add as much rigor as possible to the analyses made, for example, through simulation models or data analyses. On the other hand, we need to stay connected with all kinds of stakeholders - an essential precondition for implementation.
Following up on our earlier research, we present an approach that combines narratives, Causal Loop Diagrams, and Behavior-Over-Time Graphs to illustrate the structure, dynamic patterns and quantitative scale of the problem under study step-by-step, allowing exploration and reflection by a broad audience.
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Notes
- 1.
Detailed instructions about how we can elicit BOTGs and CLDs in workshop settings can be found on Scriptapedia; https://en.wikibooks.org/wiki/Scriptapedia.
- 2.
We described some underlying ideas in [8]. We host the code open-source on GitHub. https://github.com/ims-fhs/cld.
- 3.
Among them are i) a project funded by the Swiss National Science Foundation about psychosocial risks at work; ii) a project funded by Innosuisse - Swiss Innovation Agency aiming at improving ambulant mobile psychotherapy; and iii) a project about common work-life-balance conflicts funded by the Swiss Federal Office for Gender Equality.
- 4.
See [8] for details about the DSL grammar and import options.
- 5.
Defined curve segments are: straight lines (%-%), upward (%(%) and downward (%)%) bent segments, and s-curves (%s%). Details in code documentation.
- 6.
An example of a complete narrative is accessible at https://fhsg.shinyapps.io/burnout/.
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Stämpfli, A. (2022). Combining Causal Loop Diagrams, Behavior-Over-Time Graphs, and Narratives to Structure and Explore Complex Decision-Making Situations. In: Trautmann, N., Gnägi, M. (eds) Operations Research Proceedings 2021. OR 2021. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-08623-6_63
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