A Multi-Criteria Decision-Making Approach to University Rankings Based on URAP Data: The LOPCOW-Based COBRA Method
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https://doi.org/10.5281/zenodo.14616552Keywords:
University Ranking, URAP, MCDM, LOPCOW, COBRAAbstract
This study develops a novel model integrating the LOPCOW (Logarithmic Percentage Change-driven Objective Weighting) and COBRA (Comprehensive Distance Based Ranking) methods as an alternative to existing ranking approaches for evaluating the performance of universities in Turkey. The primary aim of the study is to overcome the limitations of current ranking systems by establishing a more objective and comprehensive evaluation framework and to assess the applicability of the proposed model. In this context, university performance is analyzed based on multidimensional criteria such as academic productivity, the number of scientific documents, citations, international collaborations, and the faculty-to-student ratio. Using Microsoft Excel 365, the LOPCOW method was employed to calculate the weights of the criteria, ensuring their relative importance was determined objectively. The analysis revealed that the “citations” criterion held the highest weight, while the “faculty-to-student ratio” was assigned the lowest weight. The COBRA method, utilizing these weights, facilitated the ranking of universities and provided a comparative perspective on the impact of alternative ranking methods. The findings indicate notable variations in the rankings of some universities, although the institutions occupying the first and last positions remained unchanged. The proposed model effectively highlights the strengths and weaknesses of universities, offering a valuable tool for strategic planning and policy development processes. Furthermore, this study emphasizes the academic and societal impacts of ranking methodologies in higher education and aims to contribute to a more objective and transparent evaluation process.
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