Do Decision Makers Know What They Prefer?: MAVT and ELECTRE II
本文探讨了规范性决策分析中不同数学模型（如MAVT和ELECTRE II）对决策者偏好揭示的影响，指出技术选择不一定绑定特定的决策者模型，因此可将不同方法应用于同一问题进行比较。
Prescriptive decision analysis has become established internationally as a tool to support decision making. Its role is generally agreed; it is a tool which helps decision makers (DMs) explore problems and possible strategies for solving them. Through application of a specific analysis, the DMs are able to learn about their preferences and discover their real objectives. Although the function of prescriptive decision analysis is generally accepted, the choice of underlying mathematical model on which the analysis is based is a matter for much discussion. Different schools of thought have led to the development of a number of alternative methodologies. The different methodologies have arisen not just from contrasting intuitive ideas for solving multicriteria problems, but also from diverse views of the DM(s) and what information they ‘know’. Therefore, comparisons of decision analysis techniques have been confounded by both the mathematical model and the vision of the DM to whom this model has been applied. However, I have argued that the adoption of a particular technique does not necessarily require a particular model of the DM, and therefore, competing tools should and can be applied to the same problem