2409-1634Research result. Economic Research2409-163410.18413/2409-1634-2017-4-1-35-531348branch and regional economyON THE EVALUATION OF THE REGIONAL UNIVERSITY COMPETITIVENESSON THE EVALUATION OF THE REGIONAL UNIVERSITY COMPETITIVENESSMoskovkinVladimir M.MoskovkinVladimir M.moskovkin@bsu.edu.ruLiuYaweiLiuYaweiBelgorod State National Research University20184100

Research subject deals with the regional university competitiveness on the case of   the Central Federal District regions of the Russian Federation. Aim: quantitative evaluation of the regional university competitiveness. Methodology: it focuses on developing a procedure for aggregation of the position of the regional universities in the Webometrics ranking, Expert RA university ranking and Interfax university ranking on the case of 18 Central Federal district regions of the Russian Federation. On the basis of the average University ranking for each region and the number of universities in the region, the regional university competitiveness index of the region has been calculated in three ways. There has been introduced the concept of a triangular matrix of coefficients exceeding one of the values of the regional university competitiveness index. Results and discussion: Calculations on the above mentioned methodology have been done for 18 Central Federal district regions of the Russian Federation. A good cross-correlation has been obtained between the values of three indicators of regional university competitiveness. In all three calculations, Moscow is the leader and the worst positions are occupied by Bryansk and Kaluga regions. It shows that the obtained values of the calculated indicators are sensitive to the changes in the number of higher education institutions. For one indicator whose values have the smallest dispersion, a triangular matrix coefficients exceeding one of the values of the regional University competitiveness indicator over another has been calculated. The maximum value in this triangular matrix is equal to 23,780, which means that the value of Moscow University competitiveness indicators exceeds the value of Kaluga region by the aforementioned number of times. Conclusion: The suggested methodology for calculating the university competitiveness index can be used for any set of University rankings and any regional grouping. It can also be adapted to the country level.

Research subject deals with the regional university competitiveness on the case of   the Central Federal District regions of the Russian Federation. Aim: quantitative evaluation of the regional university competitiveness. Methodology: it focuses on developing a procedure for aggregation of the position of the regional universities in the Webometrics ranking, Expert RA university ranking and Interfax university ranking on the case of 18 Central Federal district regions of the Russian Federation. On the basis of the average University ranking for each region and the number of universities in the region, the regional university competitiveness index of the region has been calculated in three ways. There has been introduced the concept of a triangular matrix of coefficients exceeding one of the values of the regional university competitiveness index. Results and discussion: Calculations on the above mentioned methodology have been done for 18 Central Federal district regions of the Russian Federation. A good cross-correlation has been obtained between the values of three indicators of regional university competitiveness. In all three calculations, Moscow is the leader and the worst positions are occupied by Bryansk and Kaluga regions. It shows that the obtained values of the calculated indicators are sensitive to the changes in the number of higher education institutions. For one indicator whose values have the smallest dispersion, a triangular matrix coefficients exceeding one of the values of the regional University competitiveness indicator over another has been calculated. The maximum value in this triangular matrix is equal to 23,780, which means that the value of Moscow University competitiveness indicators exceeds the value of Kaluga region by the aforementioned number of times. Conclusion: The suggested methodology for calculating the university competitiveness index can be used for any set of University rankings and any regional grouping. It can also be adapted to the country level.

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