Eigenvector Priority Function Causes Strong Rank Reversal in Group Decision Making

• Autorzy: Pérez J. , Mokotoff E.

Identyfikatory

DOI

10.3233/FI-2016-1333

• Języki publikacji: EN

Abstrakty

EN

This paper shows an example of strong rank reversal in group decision making. Decision makers have preferences expressed through a reciprocal paired comparison matrix. Every one of them applies the eigenvector priority function to her paired comparison matrix to obtain her individual priority vector and then a group priority vector is computed by any of the following two procedures: a) Averaging the already computed individual priority vectors, and b) Averaging the entries of the comparison matrices to obtain a group comparison matrix, and applying to it the eigenvector priority function. Strong rank reversal means that there is one alternative that has the highest priority for every decision maker, and consequently the highest priority in the averaged priority vector obtained by procedure (a), but loses such highest priority when procedure (b) is applied.

Słowa kluczowe

EN

rank reversal; paired comparison matrix; reciprocal matrix; AHP

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2016
• Tom: Vol. 144, nr 3/4
• Strony: 255--261
• Opis fizyczny: Bibliogr. 22 poz.

Twórcy

autor

Pérez J.

• Departamento de Economía, Universidad de Alcalá, 28802, Alcalá de Henares, Madrid, Spain

autor

Mokotoff E.

• Departamento de Economía, Universidad de Alcalá, 28802, Alcalá de Henares, Madrid, Spain

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