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A qualitative perspective to deriving weights from pairwise comparison matrices

  • Ram Ramanathan
    ,
  • Usha Ramanathan
Research Output:
Contribution to journal
Article
 Peer-review

Abstract

Deriving weights from pairwise comparison matrices (PCM) is a highly researched topic. The analytic hierarchy process (AHP) traditionally uses the eigenvector method for the purpose. Numerous other methods have also been suggested. A distinctive feature of all these methods is that they associate a quantitative meaning to the judgemental information given by the decision-maker. In contrast, the verbal scale used in AHP to capture judgements does not associate such a quantitative meaning. Though this issue of treating judgements qualitatively is recognized in the extant literature on multi-criteria decision making, unfortunately, there is no research effort so far in the AHP literature. Deriving motivation from the application of data envelopment analysis (DEA) for deriving weights, it is proposed in this paper that DEA models developed to deal with a mix of qualitative and quantitative factors can be used to derive weights from PCMs by treating judgements as qualitative factors. The qualitative DEA model is discussed and illustrated in this paper.

Publication Information

Output type

Research Output:
Contribution to journal
Article
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 228

Journal (Volume, Issue Number)

Omega (United Kingdom) (Volume 38, Issue 3-4)

Publication milestones

  • Published - 12/09/2009

Publication status

Published - 12/09/2009

ISSN

0305-0483

Publication IDs

  • handle.net: 10547/244268
  • Scopus: 70649103863

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