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Classification of Foundation Universities' Satisfaction through a Cluster Analysis and Ranking with the FUCOM-PROMETHEE Method

Author

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  • Abdulkerim GÃœLER

Abstract

The multi-criteria decision-making methods (MCDM) are increasingly being used to solve decision-making problems with multiple options and criteria. The integrated use of weighing methods is particularly important both for obtaining reliable results and for effectively evaluating the weight coefficients included in the methods. Cluster analysis is a technique used to divide various data into groups based on their similar characteristics. The aim of this study is to categorize Foundation Universities in Turkey using cluster analysis based on satisfaction and then rank these institutions using the MCDM. Thus, Foundation Universities, divided into various groups, are both separated into clusters within themselves and ranked overall. As a result of the cluster analysis, Foundation Universities were divided into four clusters. Subsequently, the ranking results of the universities were obtained using the FUCOM-PROMETHEE integrated multi-criteria decision-making method. According to these results, each cluster and the overall ranking of universities were examined and compared with the TÃœMA 2024 data. The study found a highly significant correlation between the TÃœMA 2024 report ranking and the FUCOM-PROMETHEE method ranking. According to these results, similar outcomes were reached between this method and the actual ranking. As a result of the clustering analysis, clusters that are generally consistent with the ranking of universities have been formed.

Suggested Citation

  • Abdulkerim GÃœLER, 2025. "Classification of Foundation Universities' Satisfaction through a Cluster Analysis and Ranking with the FUCOM-PROMETHEE Method," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 4.
    • Handle: RePEc:fis:journl:250421
    DOI: 10.25295/fsecon.1642315
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    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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