Multi-attribute decision support and complexity: An evaluation and process analysis of aided versus unaided decision making

The present study addresses the effectiveness of a computerized decision aid (DECAID, Pitz 1987) based on the Multi-Attribute Utility Model (MAU). The effectiveness of DECAID was investigated for personnel selection problems varying in complexity (number of alternatives and number of attributes). Results show that the decision aid was most successful for problems of medium complexity. DECAID significantly affected the thoroughness of the decision, preference formation, and the perceived difficulty of the decision problem for medium complex problems. This was not the case for highly complex problems. Next, a process analysis is presented of unaided decision making focusing on the selection and evaluation of information. This process analysis of verbal protocols was based on the same decision problems as the first study. Results indicate that problem complexity had a significant impact on the decision process. Increasing complexity resulted in a less thorough evaluation, and selective information processing. Subjects tended to focus on one or two most promising alternatives. Furthermore, evaluation strategies diverged from those used in DECAID in terms of standard of comparison. The paper concludes with implications for the design of decision aids.