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The probabilistic weighted averaging distance and its application in group decision making

Jose M. Merigo (Department of Business Administration, University of Barcelona, Barcelona, Spain and Manchester Business School, The University of Manchester, Manchester, UK)

Kybernetes

ISSN: 0368-492X

Article publication date: 24 May 2013

422

Abstract

Purpose

The purpose of this paper is to develop a new decision making method based on distance measures that uses the probabilistic weighted averaging (PWA) operator. The paper introduces the PWA distance (PWAD) operator. It is a new aggregation operator that uses probabilities, weighted averages (WAs) and distance measures. Some of its main properties and particular cases are studied such as the arithmetic weighted Hamming distance and the arithmetic probabilistic Hamming distance. An application in a group decision making problem concerning the selection of investment strategies is also presented.

Design/methodology/approach

The paper follows the aggregation operator literature by designing new aggregation operators based on the use of distance measures. Also an application in investment selection is developed.

Findings

The PWAD operator is presented. It permits to use distance measures with probabilities and WAs in the same formulation. Moreover, the paper also finds the PWA norm aggregation and implements them in a group decision making problem.

Practical implications

The PWAD operator can be applied in a wide range of problems including statistics, economics and engineering. The paper focuses on a multi‐person decision making application concerning the selection of the optimal investment strategies.

Originality/value

New aggregation operators by using distance measures are presented. Their main advantage is that they unify the WA with the probability. Thus, the paper considers distance measures that include subjective and objective information in the same formulation.

Keywords

Citation

Merigo, J.M. (2013), "The probabilistic weighted averaging distance and its application in group decision making", Kybernetes, Vol. 42 No. 5, pp. 686-697. https://doi.org/10.1108/K-06-2013-0107

Publisher

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Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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