A comparison of representations for discrete multi‐criteria decision problems

Discrete multi‐criteria decision problems with numerous Pareto‐efficient solution candidates place a significant cognitive burden on the decision maker. An interactive, aspiration‐based search process that iteratively progresses toward the most preferred solution can alleviate this task. In this paper, we study three ways of representing such problems in a DSS, and compare them in a laboratory experiment using subjective and objective measures of the decision process as well as solution quality and problem understanding. In addition to an immediate user evaluation, we performed a re‐evaluation several weeks later. Furthermore, we consider several levels of problem complexity and user characteristics. Results indicate that different problem representations have a considerable influence on search behavior, although long‐term consistency appears to remain unaffected. We also found interesting discrepancies between subjective evaluations and objective measures. Conclusions from our experiments can help designers of DSS for large multi‐criteria decision problems to fit problem representations to the goals of their system and the specific task at hand.