Testing the Effects of a System Dynamics Decision Aid on Mental Model Accuracy and Performance on Dynamic Decision Making Tasks

Previous studies have suggested that decision aid support can positively affect performance on dynamic decision making tasks. However, few studies have examined the effects of decision aid support on the cognitive mechanisms underpinning performance. This study tested the relationships between decision aid support (in the form of causal loop diagrams), task complexity, cognitive load, mental model accuracy and performance, using a product lifecycle management simulation. Results indicate that task complexity and decision aid support are significant predictors of mental model accuracy, and that decision aid support moderates the relationship between task complexity and mental model accuracy. In addition, task complexity and mental model accuracy are significant predictors of performance. Our findings regarding the beneficial impact of decision aid support on mental model accuracy and on incremental gains in learning and performance highlight the importance of understanding the underlying cognitive mechanisms at work. Designing more effective decision aids to enhance the development of accurate mental models is one path with a great deal of potential to improve performance in dynamic decision making environments.