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Towards a Framework for the Measurement and Reduction of User-Perceivable Complexity of Group Decision-Making Methods

Methods for group decision analysis are based on various preference and aggregation models, and may exhibit a significant level of complexity that is perceived by decision-makers. It is therefore essential to apply appropriate methods and keep the complexity within controllable limits. In the paper, factors that influence the user-perceivable complexity are systematically specified, correlated and decomposed into measurable units. They address cognitive load, asynchronous interaction, autonomous guidance and conflict resolution, thoroughness and depth of analysis, problem structuring, efficiency of judgements, imprecision, psychophysical applicability, etc. In addition, several mechanisms and techniques to reduce complexity are presented, evaluated and systematized in accordance with the factors of the framework.