Endowing cognitive mapping with computational properties for strategic analysis

Modeling for Policy Formulation: Causal Mapping, Scenario Generation, and Decision Evaluation

“…Several "dialects" of cognitive maps have emerged, which share focus on the qualitative aspects of problem structuring, see, e.g., (Acar and Druckenmiller 2006). Although a cognitive map serves its purpose as a problem structuring method, its content is too informal to be used as an underlying model for simulation of how changes in one node affects other nodes through causal relations.…”

Designing insightful inquiring systems for sustainable organizational foresight

“…Our journey is taking us to the approach Acar [7] developed as an offshoot of the ideas generated by Churchman and Ackoff. Acar and Druckenmiller [33] summarize the computational properties of his form of causal mapping, known as comprehensive situation mapping (CSM), against the backdrop of its competing approaches (see Fig. 2).…”

“…A fully detailed presentation of it can be found in Acar [7] and mid-length descriptions with some examples are given in Georgantzas and Acar [26]. Recently, Acar and Druckenmiller [33] provided an initial topological analysis of the place of CSM in the vast family of graphical and computer simulation-based approaches to decision-making, in particular its relationship to cognitive mapping and influence diagramming. This paper complements that article by showing how successfully CSM integrates causal mapping with DI.…”

“…More oriented toward presenting the graphing techniques than the present paper's focus on the DI process capability of CSM, Acar and Druckenmiller illustrated their article [33] with one of Acar's original case study maps. Because it illustrates all three types of links from a real-life situation, and shows that nodes have to be quantitative or at least quantifiable variables, we reproduce this concrete illustration in Fig.…”

“…The flow of change through the system can thereby be computed manually in CSM, in spite of the nonlinearity due to the presence of loops discovered by Maruyama, and also those due to production function nonlinearity that would normally require computerized simulation. As discussed by Acar [43], Georgantzas and Acar [19], and Acar and Druckenmiller [33], CSM's computation of scenarios goes beyond the traditional qualitative devising of scenarios, and can also assist in the evaluation of goal compatibilities and feasibilities. Causal maps thus become the basis for the simulation of the propagation of change through the network of presumed causal relations; in other words, for the analysis of the implications of one's assumptions.…”