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Decision support systems continue to be very popular in business, despite mixed research evidence as to their effectiveness. We hypothesize that what-if analysis, a prominent feature of most decision support systems, creates an "illusion of control" causing users to overestimate its effectiveness. Two experiments involving a production planning task are reported which examine decision makers' perceptions of the effectiveness of what-if analysis relative to the alternatives of unaided decision making, and quantitative decision rules. Experiment 1 found that almost all subjects believed what-if analysis was superior to unaided decision making, although using what-if analysis had no significant effect on performance. Experiment 2 found that decision makers were indifferent between what-if analysis and a quantitative decision rule which, if used, would have led to significant cost savings. Thus, what-if analysis did create an illusion of control: decision makers perceived performance differences where none existed, and did not detect large differences when they were present. In both experiments, decision makers exhibited difficulty realizing that their positive beliefsabout what-if analysis were exaggerated. Such misjudgments could lead people to continue using what-if analysis even when it is not beneficial and to avoid potentially superior decision support technologies.Subject Areas: Decision Support Systems and Production/Operations Management.

Model integration extends the scope of model management to include the dimension of manipulation as well. This invariably leads to comparisons with database theory. Model integration is viewed from four perspectives: Organizational, definitional, procedural, and implementational. Strategic modeling is discussed as the organizational motivation for model integration. Schema and process integration are examined as the logical and manipulation counterparts of model integration corresponding to data definition and manipulation, respectively. A model manipulation language based on structured modeling and communicating structured models is suggested which incorporates schema and process integration. The use of object-oriented concepts for designing and implementing integrated modeling environments is discussed. Model integration is projected as the springboard for building a theory of models equivalent in power to relational theory in the database community.

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