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Analyzing the Demand for Educational Services of Higher Education Institutions in Terms of Individual Specialties
Skrypnyk A. V., Nehrey M. V., Petrenko A. A.

Skrypnyk, Andrii V., Nehrey, Marina V., and Petrenko, Anna A. (2021) “Analyzing the Demand for Educational Services of Higher Education Institutions in Terms of Individual Specialties.” Business Inform 2:111–118.
https://doi.org/10.32983/2222-4459-2021-2-111-118

Section: Education and Science

Article is written in Ukrainian
Downloads/views: 2

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UDC 330.43

Abstract:
Ukrainian higher education is in a state of reforming, which aimes at improving its quality and is accompanied by a reduction in its generality. During the admission campaign in 2020, the concept of «indicative self-cost of educational services» was for the first time used, the purpose of which was to reduce the demand for training at the expense of individuals (contract) in the State-owned higher education institutions. The publication considers the study of the efficiency of the State regulation of qualifying for a government scholarship as to certain specialties. For this purpose, data on the results of the 2020 admission campaign from the unified State electronic database on education were used. The educational space was divided into several subspaces, for each of these the ratio between the number of applications submitted and the license volume was obtained. It was found that the most in demand for a long time are specialties related to jurisprudence, in the smallest demand are specialties of engineering, where the competition is two applications for three budget places (1.50). The publication uses econometric methods of analysis of digital information, assessments of the elasticity of the introductory score according to the general competition and its marginal value are carried out. Recommendations on refusal of expert assessments in the regulation of the students’ admission and redistribution of financial resources in favor of high-demand specialties are provided.

Keywords: higher education, competition, competitive score, passing score, demand, supply, specialties, educational programs, specializations, econometric models, approximation, error.

Fig.: 5. Tabl.: 3. Formulae: 9. Bibl.: 17.

Skrypnyk Andrii V. – Doctor of Sciences (Economics), Professor, Professor, Department of Economic Cybernetics, National University of Life and Environmental Sciences of Ukraine (15 Heroiv Oborony Str., Kyiv, 03041, Ukraine)
Email: [email protected]
Nehrey Marina V. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Economic Cybernetics, National University of Life and Environmental Sciences of Ukraine (15 Heroiv Oborony Str., Kyiv, 03041, Ukraine)
Email: [email protected]
Petrenko Anna A. – Student, National University of Life and Environmental Sciences of Ukraine (15 Heroiv Oborony Str., Kyiv, 03041, Ukraine)
Email: [email protected]

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