From equality to diversity

Classifying Russian universities in a performance oriented system

Journal Article (2016)
Author(s)

Irina Abankina (National Research University Higher School of Economics (HSE University))

Fuad Aleskerov (National Research University Higher School of Economics (HSE University), V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences)

Veronika Belousova (National Research University Higher School of Economics (HSE University))

Leonid Gokhberg (National Research University Higher School of Economics (HSE University))

Sofya Kiselgof (National Research University Higher School of Economics (HSE University))

Vsevolod Petrushchenko (National Research University Higher School of Economics (HSE University))

Sergey Shvydun (V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, National Research University Higher School of Economics (HSE University))

Kirill Zinkovsky (National Research University Higher School of Economics (HSE University))

Affiliation
External organisation
DOI related publication
https://doi.org/10.1016/j.techfore.2015.10.007 Final published version
More Info
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Publication Year
2016
Language
English
Affiliation
External organisation
Journal title
Technological Forecasting and Social Change
Volume number
103
Pages (from-to)
228-239
Downloads counter
136

Abstract

Over the last few decades, performance-based funding models of universities have been introduced and have made universities build and implement different strategies to enable them to compete and be viable in changing circumstances. In turn, national governments are focused on providing universities with more opportunities to run efficient programmes that advance higher education. This paper includes a detailed review of various taxonomies for structuring university. More importantly, it develops a typology of higher education institutions that is relevant for the Russian context. The Ward method is used to cluster universities on the basis of university distinctions in terms of the availability of resources, education, and research and development. This typology of universities is verified by assessing their efficiency score gained from modified Data Envelopment Analysis, incorporating universities' heterogeneity. Finally, the paper gives a decision tree for classifying universities bearing in mind their diversity. It might be expanded for a broader set of inputs and outputs, namely external projectbased research funding modes and cooperation between universities and industry to pursue the development of innovation. The results can be used for shaping targeted policies aimed at particular university groups.