Abstract
Classifying universities is regarded as an efficient strategy for developing institution-based policy for different types of universities. In Turkey, there is no widely accepted classification or official classification of universities for researchers and policy makers. Regarding this need, the first purpose of this study is to classify universities in Turkey on the basis of institutional size and performance. Since the focus of the study is institutional size and performance, researchers approach the subject from the perspectives of management and organization. Universities were classified using hierarchical cluster analysis. All state and foundation universities were included in the study. The data sources were statistics of the Council of Higher Education (CoHE), ranking lists, University Ranking by Academic Performance (URAP), Ranking of the Entrepreneurial and Innovative University Index (TUBITAK), strategic plans and annual reports of higher education institutions, and related data on research and publications. Universities were clustured on the basis of objective data not predetermined criteria. The main variables for cluster analysis were quantitative measures, ranking scores, and measures of the quality of teaching and research for each university. The results of the cluster analysis showed that clustering universities by institutional size and performance as two separate variables provided better results. The scale and tenure of universities differentiated them in terms of institutional size and performance variables. Universities founded in the same years were divided into two clusters, mainly according to the size of their vocational schools. It was also found that when publication performance was expressed, those universities that were small/medium sized, focused, and long tenured were separate from other universities.
Highlights
Performance measurement in higher education has become an important subject in recent years
Universities in Turkey were classified by using hierarchical cluster analysis, which is a data-based classification
The results of the cluster analysis showed that clustering universities by using institutional size and performance as two separate variables provided better results
Summary
Performance measurement in higher education has become an important subject in recent years. Classifying universities is regarded as an efficient strategy for policy development in the field of higher education (Shin, 2009) since classification provides a basis for diversified policy approaches and collaboration between institutions, methodological and analytical tools for research, and transparency for stakeholders and other organizations (Bartelse & Vught, 2007). Researchers and policymakers have used a variety of criteria to develop typologies for higher education institutions (Shin, 2009). In order to build a useful classification system, we must consider multiple factors, such as the purpose of the classification, the nature of the objects or cases to be classified, the criteria and data available for classification, and the degree of differentiation (McCormick & Zhao, 2005)
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