A novel hybrid MCDM approach to evaluate universities based on student perspective

Ayyıldız E., Murat M., İmamoğlu G., Köse Y.

SCIENTOMETRICS, vol.128, no.1, pp.55-86, 2023 (SCI-Expanded)

  • Publication Type: Article / Article
  • Volume: 128 Issue: 1
  • Publication Date: 2023
  • Journal Name: SCIENTOMETRICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, FRANCIS, Agricultural & Environmental Science Database, Applied Science & Technology Source, BIOSIS, CINAHL, Computer & Applied Sciences, Index Islamicus, Information Science and Technology Abstracts, INSPEC, Library and Information Science Abstracts, Library, Information Science & Technology Abstracts (LISTA), PAIS International, RILM Abstracts of Music Literature, zbMATH
  • Page Numbers: pp.55-86
  • Karadeniz Technical University Affiliated: Yes


University rankings are an essential source of comparisons between universities according to specific combinations of criteria. International or national rankings have an increasing impact on higher education institutions, stakeholders, and their environments. Thereby, on behalf of effective decision-making, university-ranking efforts should be a process involving some conflicting criteria and uncertainties in a more sensitive manner. This study presents a detailed university evaluation procedure under certain service criteria via multi-criteria decision-making (MCDM) methodologies and provides an appropriate clustering of universities according to teaching and research factors. A hierarchical cluster-based Interval Valued Neutrosophic Analytic Hierarchy Process (IVN-AHP) integrated VIKOR methodology that includes two stages, clustering and ranking, is proposed for the university evaluation problem. The hierarchical clustering method is performed using teaching and research factors in the first stage. The second stage addresses the determination weights of service criteria through IVN-AHP and the ranking of universities by using VIKOR according to service criteria under determined clusters. This study, in which the proposed methodology is applied to Turkish universities, is the most comprehensive in terms of the number of universities evaluated and participating students. Furthermore, the integration of IVN-AHP and VIKOR to solve MCDM problems is presented for the first time. This study differs from other studies in terms of novelties both methodological-based and application based. Moreover, categorizing universities with similar characteristics into groups using cluster analysis and ranking them with the MCDM methodology provide a more realistic and effective interpretation of the results.