Multi-Criteria Analysis Applied on Selected Higher Education Institutions in European Union

Tetiana Kalinichenko

Master's thesis

Abstract:

The present increasing trend of people with higher education indicates undeniable demand for the highly qualified specialists on the labour market. However, the challenging task for an enrollee is to determine higher education institutions that value the qualitative aspect of education rather than quantification of enrolment rates. The ranking schemes may be seen as a practical tool to conclude the decision since they purposely account for criteria, which are most authoritative. While such education selection factors mostly remain unchanged predicated on gender and field of study, yet the importance of specific criteria differs among these subgroups. This research aims to facilitate Multi Criteria Decision Analysis within an educational framework to establish the rank among top 44 European Union universities. The main emphasis is placed on the dissimilarities of criteria importance order between genders as well as a field of study and their respective ranks. The theoretical review addresses the decision making background encompassing, its history, process flow, and models. Decision analysis is considered within the scope of multi criteria input. Therefore, extensive multi criteria method review contributes to the selection of appropriate techniques for further analysis. The ranking task is explicitly represented at the beginning of a practical part of the thesis. In order to enhance the accuracy of findings, information was gathered in the form of independent survey. The criteria weights concluded upon the results of the questionnaire finalize the model inputs. Aggregated data is incorporated into TOPSIS, VIKOR and WASPAS methods to achieve the final ranking of EU higher education institutions. Multi Criteria Decision Analysis results are introduced and explained in the closing part of practical implementation.

Abstract:

The present increasing trend of people with higher education indicates undeniable demand for the highly qualified specialists on the labour market. However, the challenging task for an enrollee is to determine higher education institutions that value the qualitative aspect of education rather than quantification of enrolment rates. The ranking schemes may be seen as a practical tool to conclude the decision since they purposely account for criteria, which are most authoritative. While such education selection factors mostly remain unchanged predicated on gender and field of study, yet the importance of specific criteria differs among these subgroups. This research aims to facilitate Multi Criteria Decision Analysis within an educational framework to establish the rank among top 44 European Union universities. The main emphasis is placed on the dissimilarities of criteria importance order between genders as well as a field of study and their respective ranks. The theoretical review addresses the decision making background encompassing, its history, process flow, and models. Decision analysis is considered within the scope of multi criteria input. Therefore, extensive multi criteria method review contributes to the selection of appropriate techniques for further analysis. The ranking task is explicitly represented at the beginning of a practical part of the thesis. In order to enhance the accuracy of findings, information was gathered in the form of independent survey. The criteria weights concluded upon the results of the questionnaire finalize the model inputs. Aggregated data is incorporated into TOPSIS, VIKOR and WASPAS methods to achieve the final ranking of EU higher education institutions. Multi Criteria Decision Analysis results are introduced and explained in the closing part of practical implementation.

Keywords

Multi Criteria Decision Analysis, University rankings, VIKOR, WASPAS, TOPSIS

Keywords

Multi Criteria Decision Analysis, VIKOR, WASPAS, University rankings, TOPSIS

Language used: English

Date on which the thesis was submitted / produced: 15. 10. 2018

Thesis defence

• Date of defence: 7. 6. 2019
• Supervisor: Martina Kuncová
• Reader: Petr Fiala

Vysoká škola ekonomická v Praze

Master programme / field:
Kvantitativní metody v ekonomice / Quantitative Economic Analysis