An Evaluation Study of the Effectiveness of Multi-attribute Decision Support as a Function of Problem Complexity

Abstract

This study focuses on the evaluation of multi-attribute (MAU) decision support for problems differing in complexity. In this study we compared decision making with a computerized decision support system (DECAID) with the unaided process. Overall, results indicate that MAU support led to a more thorough decision process, had more impact on preference formation, and led to a larger decrease of perceived difficulty of the decision problem as compared to the no-support condition. The MAU decision aid turned out to be less lime efficient than the unaided mode, especially with increasing numbers of alternatives. Results suggest that the MAU decision aid is effective for problems of low and moderate complexity only. For highly complex problems, results are less favorable.