Ch. 9
Building Model-Driven Decision Support Systems

As noted, a Model-Driven DSS may include more than one of the above types of models. For example, a specific Model-Driven DSS may include:

1. An explanatory regression model that identifies relationships among variables,
2. A contemplative financial model of a pro forma income statement, and
3. An algebraic optimization model like linear programming.

Some models are standard components in DSS development packages and some must be custom programmed. A DSS builder chooses appropriate models. Once models have been chosen, then a decision must be made to build the models, to use "ready-made" models, or to modify existing models. The software used for creating the model component also needs to be linked to any data and the DSS user interface. Also, a DSS analyst needs to choose to use either static or dynamic models, and to choose if the situation will be modeled assuming certainty, uncertainty, or risk.