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Article


Title

Applying Data Envelopment Analysis Principle in Ordinal Multi Criteria Decision Analysis

Authors

Year of publication

2021

Published in

Foundations of Computing and Decision Sciences

Journal year: 2021 | Journal volume: vol. 46 | Journal number: no. 2

Article type

scientific article

Publication language

english

Keywords
EN
  • multiple criteria analysis
  • ordinal scale
  • DEA
  • extreme-point
  • discriminating factor
Abstract

EN We consider a multicriteria decision analysis (MCDA) problem where importance of criteria, and evaluations of alternatives with respect to the criteria, are expressed on a qualitative ordinal scale. Using the extreme-point principle of Data Envelopment Analysis (DEA), we develop a two-parameter method for obtaining overall ratings of the alternatives when preferences and evaluations are made on an ordinal scale. We assume no parametric setup other than the two parameters that reflect minimum intensities of discriminating among rank positions: one parameter for the alternatives’ ranking and one for the criteria ranking. These parameters are bounded by the ordinal input data, and they imply a universal tie among the alternatives when both parameters are selected to be zero. We describe the model, discuss its theoretical underpinning, and demonstrate its application.

Pages (from - to)

147 - 157

DOI

10.2478/fcds-2021-0010

URL

https://sciendo.com/article/10.2478/fcds-2021-0010

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

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Points of MNiSW / journal

20.0

Points of MNiSW / journal in years 2017-2021

20.0