MCDM'22 - paper no. 4

 

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OBJECTIVE WEIGHTS FOR SCORING: THE AUTOMATIC DEMOCRATIC METHOD

Chris Tofallis

Abstract:

When comparing performance (of products, services, entities, etc.), multiple attributes are involved. This paper deals with a way of weighting these attributes when one is seeking an overall score. It presents an objec-tive approach to generating the weights in a scoring formula which avoids personal judgement. The first step is to find the maximum possible score for each assessed entity. These upper bound scores are found using Data Envelopment Analysis. In the second step the weights in the scoring for-mula are found by regressing the unique DEA scores on the attribute data. Reasons for using least squares and avoiding other distance measures are given. The method is tested on data where the true scores and weights are known. The method enables the construction of an objective scoring for-mula which has been generated from the data arising from all assessed en-tities and is, in that sense, democratic.

Keywords:

multi attribute decision making, weighting, ranking, performance measurement, composite indices, data envelopment analysis

Reference index:

Chris Tofallis, (2022), OBJECTIVE WEIGHTS FOR SCORING: THE AUTOMATIC DEMOCRATIC METHOD, Multiple Criteria Decision Making (17), pp. 69-84

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