@ARTICLE{26583204_128738242_2014, 
	author = {Vasily Korf}, 
	keywords = {, rating, higher education, efficiency, competitiveness of universities, funding of educational, globalization of higher education, higher education as a social valueprincipal component analysis},
	title = {Estimating of Russian universities competitiveness using principal component analysis },
	journal = {},
	year = {2014},
	number = {2 (28)},
	pages = {63-71},
	url = {https://bijournal.hse.ru/en/2014--2 (28)/128738242.html},
	publisher = {},
	abstract = {Vasily Korf - Post-graduate Student, Department of Computer Systems in Economics,Faculty of Economics, St. Petersburg State University.Address: 62, Tchaikovskogo str., St. Petersburg, 191123, Russian Federation.E-mail: vasilykorf@gmail.com      This article deals with analysis of the competitiveness of leading Russian universities. On May 7, 2012 President of Russian Federation issued Executive Order No. № 599 "On Measures to Implement State Policy in Education and Science", which involves the development of leading universities, increase their competitiveness among the world's leading universities. The results of an experiment on the evaluation of competitiveness of Russian universities using the principal components method are presented in the paper.      Competitiveness assessment is required for a variety of operations, projects and processes. The principal component method helps to solve the problem of heterogeneity and incommensurability of indicators to measure competitiveness, enables to select leading factors of variation of random variables studied and to reduce the dimensionality of the data.      The source data for the evaluation of the competitiveness of universities have been aggregated from the official websites of universities, the admission quotas, examination results, resume database, documents of the RF Ministry of Education and Science. There are 14 indicators, that characterize the universities in terms of entrants (entry criteria) and graduates (exit criteria).      The study findings clearly show the relationship between the selected indicators and competitiveness of universities. Therefore, high values of input indicators are usually associated with high output performance, but they do not guarantee a high rate of competitiveness of the university. High requirements for applicants do not guarantee a high level of training of graduates and their relevant employment.},
	annote = {Vasily Korf - Post-graduate Student, Department of Computer Systems in Economics,Faculty of Economics, St. Petersburg State University.Address: 62, Tchaikovskogo str., St. Petersburg, 191123, Russian Federation.E-mail: vasilykorf@gmail.com      This article deals with analysis of the competitiveness of leading Russian universities. On May 7, 2012 President of Russian Federation issued Executive Order No. № 599 "On Measures to Implement State Policy in Education and Science", which involves the development of leading universities, increase their competitiveness among the world's leading universities. The results of an experiment on the evaluation of competitiveness of Russian universities using the principal components method are presented in the paper.      Competitiveness assessment is required for a variety of operations, projects and processes. The principal component method helps to solve the problem of heterogeneity and incommensurability of indicators to measure competitiveness, enables to select leading factors of variation of random variables studied and to reduce the dimensionality of the data.      The source data for the evaluation of the competitiveness of universities have been aggregated from the official websites of universities, the admission quotas, examination results, resume database, documents of the RF Ministry of Education and Science. There are 14 indicators, that characterize the universities in terms of entrants (entry criteria) and graduates (exit criteria).      The study findings clearly show the relationship between the selected indicators and competitiveness of universities. Therefore, high values of input indicators are usually associated with high output performance, but they do not guarantee a high rate of competitiveness of the university. High requirements for applicants do not guarantee a high level of training of graduates and their relevant employment.}
}