Application of technical analysis in management decision-making in higher education institutions
S M Abilov, A A Kaigorodtsev
S M Abilov
Available Online November 2019.
- https://doi.org/10.2991/icsdcbr-19.2019.41How to use a DOI?
- labor market, education market, forecasting demand for specialists, technical analysis, university management, managerial decisions
- University management should be organized in such a way that it may provide the labor market with specialists needed today. In order to solve the problem, a hypothesis on the possible use of such method of technical analysis as the moving average method is being applied for forecasting in the financial market. The market analysis makes it possible to identify specialties that are currently in greatest demand. At the same time, universities do not immediately respond to the needs of the labor market. An average university training is four years; therefore, university graduates of the highly demanded specialties will similarly appear four years late. The moving average method to predict future labor market demands for specialties enables universities to train the necessary specialists for the market without delay. The results of the market analysis are the basis for the development by the university administration of strategic and tactical solutions necessary for the development. At the same time, special attention should be paid to ensuring the quality of specialists’ training, which corresponds to the demand of the labor market.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - S M Abilov AU - A A Kaigorodtsev PY - 2019/11 DA - 2019/11 TI - Application of technical analysis in management decision-making in higher education institutions BT - International Conference on Sustainable Development of Cross-Border Regions: Economic, Social and Security Challenges (ICSDCBR 2019) PB - Atlantis Press SP - 192 EP - 197 SN - 2352-5398 UR - https://doi.org/10.2991/icsdcbr-19.2019.41 DO - https://doi.org/10.2991/icsdcbr-19.2019.41 ID - Abilov2019/11 ER -