Computer-augmented decision making

The principal judgmental components of multiattribute decision making are examined here with specific reference to how these components can be captured electronically. Once captured, a function, rule, or algorithm may be executed for the integration of this information and the selection of the optimal alternative(s). Two kinds of algorithms are discussed: one based on linear models, the other on fuzzy-set theory and ratio scaling. With on-line support and certain assumptions about human biases (which lead to nonoptimal decisions), the quality of decisions can be enhanced considerably. The principal concerns are with end-user acceptance of computer augmented decisions.