Correspondence analysis as an aid to multicriteria decision making

Stephen Y L CHEUNG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Correspondence analysis is a relatively little used multivariate statistical technique in the English speaking world. This study aims to show how the technique can be used as an aid to multiple criteria decision making. Based on expressed pairwise indifferences, pairs of alternatives are classified into one of the three categories: 'indifferent', 'indifferent-indifferent' and otherwise. A coefficient of similarity is assigned to each category, and using this information, correspondence analysis is used to display these alternatives onto a map. The first principal axis of the map tends to be the axis of preference and groups of the most preferred and least preferred policies may be identified. Application of the method is further examined in the case of incomplete information and is found to be capable of providing an 'accurate' result. The maps are also compared with those obtained by Rivett using multidimensional scaling.

Original languageEnglish
Pages (from-to)149-155
Number of pages7
JournalOmega
Volume19
Issue number2-3
DOIs
Publication statusPublished - 1991

Scopus Subject Areas

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

User-Defined Keywords

  • correspondence analysis
  • multiple criteria decision making

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