Abstract
Multiple criteria decision analysis is devoted to the development of decision support tools to address complex decisions, especially where other methods fail to consider more than one outcome of interest. The approach is very flexible as outcomes can be quantifiable in non-monetary terms and be expressed in ordinal or numerical terms (Sect. 11.1). Basically speaking, it starts with the construction of a value tree and the identification of relevant criteria (Sect. 11.2). The approach then proceeds with gathering information about the performance of each assessed alternative against the whole set of criteria. Values are generally normalized from 0 to 1, thereby constituting what is termed a score matrix (Sect. 11.3). Numerical weights are also assigned to criteria to better reflect their relative importance (Sect. 11.4). Weights and scores are then combined to arrive at a ranking or sorting of alternatives. Should a compensatory analysis be implemented, the approach would rely on aggregation methods to build a composite indicator (Sect. 11.5). Should a non-compensatory analysis be carried out, the approach would instead examine each dimension individually (Sect. 11.6). Furthermore, a sensitivity analysis of the weights and scores can be used to explore how changes in assumptions influence the results (Sect. 11.7).
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Josselin, JM., Le Maux, B. (2017). Multi-criteria Decision Analysis. In: Statistical Tools for Program Evaluation . Springer, Cham. https://doi.org/10.1007/978-3-319-52827-4_11
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