The comparison of mental models of dynamic systems improves our understanding of how people comprehend, interpret, and subsequently influence dynamic management tasks. Approaches to comparing mental models currently used in managerial and organizational cognition research, especially the distance-ratio and the closeness-approaches, have been criticized for not considering essential characteristics of dynamic managerial situations. This paper builds on a recent analysis method developed to compare mental models of dynamics systems, and introduces this mathematical approach to management and organizational researchers by means of the SEXTANT software. It presents the process of mental model elicitation, analysis, comparison, and interpretation. An example with four elicited mental models illustrates the software's features to analyze and present the results. Then, the software is compared with existing software to map and com-pare mental models. Our conclusion is that SEXTANT marks a significant step in enabling large-scale studies about mental models of dynamic systems.
Mental models are the basis on which managers make decisions even though external decision support systems may provide help. Research has demonstrated that more comprehensive and dynamic mental models seem to be at the foundation for improved policies and decisions. Eliciting and comparing such models can systematically explicate key variables and their main underlying structures. In addition, superior dynamic mental models can be identified. This paper reviews existing studies which measure and compare mental models. It shows that the methods used to compare such models lack to account for relevant aspects of dynamic systems, such as, time delays in causal links, feedback structures, and the polarities of feedback loops. Mental models without those properties are mostly static models. To overcome these limitations of the methods to compare mental models, we enhance the widely used distance ratio approach (Markóczy and Goldberg, 1995) so as to comprehend these dynamic characteristics and detect differences among mental models at three levels: the level of elements, the level of individual feedback loops, and the level of the complete model. Our contribution lies in a new method to compare explicated mental models, not to elicit such models. An application of the method shows that this previously non-existent information is essential for understanding differences between managers' mental models of dynamic systems. Thereby, a further path is created to critically analyze and elaborate the models managers use in real world decision making. We discuss the benefits and limitations of our approach for research about mental models and decision making and conclude by identifying directions for further research for operational researchers.
Current teaching and learning of system dynamics is based on materials derived from the expertise of masters. However, there is little explicit reference to the stages which beginners go through to become proficient nor what is learned at each of these stages. We argue that this hinders cumulative research and development in teaching and learning strategies. We engaged 15 acknowledged masters in the field to take part in a three-round Delphi study to develop an operational representation of the competence development stages and what is learned at each stage. The resulting system dynamics competence framework consists of a qualified, expert-evaluated, empirically based set of seven skills and 265 learning outcomes. The skills provide a common orientation, in the language of current educational research, to facilitate research, course design and certification efforts to ensure quality standards. To conclude this paper provides avenues for future work.
The comparison of mental models of dynamical systems can help understanding they way individuals understand dynamic situations and how their understanding changes. Current approaches like the Distance Ratio and the Closeness Ratio have been criticized for not taking into account feedback loops and delays; an improved comparison method has been proposed, specifying an Element Distance Ratio, Loop Distance Ratios and a Model Distance Ratio. We are advancing in the automation of the computations in order to take this burden away from analysts. This paper describes the essential computations. It briefly presents the comparison method for the different ratios. Then it introduces the conceptual architecture of the software tool, its main data structures and algorithms. The tool shall be put to use in mental model research.
We examine whether and when executives' attentional capacity imposes
limits to the number of strategic issues on their agenda. Based on a multi-method study of 79 private banks in Switzerland, Luxembourg, Austria, Singapore, and Hong Kong that face a broad range of issues in the regulatory, economic, and technological domains, we find that executives are able to attend to multiple issues simultaneously, but that their attentional capacity relates to the nature of the issue context. Issues
tend to interact with each other and the more pervasive issues tend to consume more attentional capacity crowding out other issues. Moreover, the strategic agenda size shapes the richness of organizational change actions. Contributions are intended to be made to selective attention and strategic issue management research by theorizing the role of simultaneous issue processing and of the limits of attention.
