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The Need for and Possible Methods of Objective Ranking

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Trends in Multiple Criteria Decision Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 142))

Abstract

The classical approach in decision analysis and multiple criteria theory concentrates on subjective ranking, at most including some aspects of intersubjective ranking (ranking understood here in a wide sense, including the selection or a classification of decision options). Intuitive subjective ranking should be distinguished here from rational subjective ranking, based on the data relevant for the decision situation and on an approximation of personal preferences. However, in many practical situations, the decision maker might not want to use personal preferences, but prefers to have some objective ranking. This need of rational objective ranking might have many reasons, some of which are discussed in this chapter. Decision theory avoided the problem of objective ranking partly because of the general doubt in objectivity characteristic for the twentieth century; the related issues are also discussed. While an absolute objectivity is not attainable, the concept of objectivity can be treated as a useful ideal worth striving for; in this sense, we characterize objective ranking as an approach to ranking that is as objective as possible. Between possible multiple criteria approaches, the reference point approach seems to be most suited for rational objective ranking. Some of the basic assumptions and philosophy of reference point approaches are recalled in this chapter. Several approaches to define reference points based on statistical data are outlined. Examples show that such objective ranking can be very useful in many management situations.

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Correspondence to Andrzej P. Wierzbicki .

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Wierzbicki, A.P. (2010). The Need for and Possible Methods of Objective Ranking. In: Ehrgott, M., Figueira, J., Greco, S. (eds) Trends in Multiple Criteria Decision Analysis. International Series in Operations Research & Management Science, vol 142. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5904-1_2

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