Common Steps of MADA Methods

All MADA methods require a definition and structuring of objectives, attributes and alternatives and the majority of methods also requires a definition of weights that reflect the importance of different sub-objectives. In 

Structuring a decision problem is an iterative process that ideally involves all major stakeholders and might lead to considerable revisions of the original problem formulation (cf. Roy 1999, pp. 1-6). In practice, the process in itself often is at least as valuable as the recommendation arrived at by later use of a decision analysis model (cf. Belton and Hodgkin 1999, p. 248 Goodwin and Wright 1998, p. 397 Phillips 1986, p. 189). 

A critical assumption of all additive, compensatory MADA tools is that the decision maker s preferences with respect to one objective are independent of the alternative s attribute value with respect to another objec- 

Of course, also the set of relevant alternatives has to be defined. If too many alternatives exist, a checklist approach might be used to arrive at a shortlist or a dominance analysis can be performed based on the performance matrix of the alternatives. In case of a lack of alternatives various techniques can be explored to generate additional alternatives (cf. Keeney 1992, pp. 198-240). The alternatives to be analyzed in detail should be described carefully because the way they are described can have unintended effects on decision makers preference statements. The examples provided by Tversky and Kahneman (1986) illustrate this point. 

Clearly, not all (sub-) objectives of a decision problem are equally important. Consequently, most MADA tools require that the decision maker defines weights for each objective. Common weight elicitation methods with varying degrees of sophistication are introduced below and pitfalls in weight elicitation discussed. 

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