Journal of Mathematics and Statistics

Efficiency Estimation of Innovative Activity the Enterprises

Andrey Sergeevich Nechaev, Dmitry Alekseevich Antipin and Oksana Victorovna Antipina

DOI : 10.3844/jmssp.2014.443.447

Journal of Mathematics and Statistics

Volume 10, Issue 4

Pages 443-447

Abstract

The widely acknowledged fact is that the economic growth based only on an export of the raw materials cannot be stable for a long time and thereupon the financial support of an innovative activity gets of a special urgency. To provide higher and steady rates of an economy growth it is necessary to carry out a transition to an innovative way of the development and to spur the creation of the hi-tech manufactures. At the same time it does not mean the automatic termination of the raw materials extraction. The stocks of some kinds of them make the state the leading one in the world. The aim of the article is to review the main aspects of the selection of indicators to measure innovation in enterprises. To improve the efficiency of innovation investment enterprises must evaluate the potential of the company and on this basis to identify priority areas of investments completed. The paramount value for the given problem decision has a choice of the indicators for the estimation of the enterprises innovative activity. The paper substantiates the need for regression analysis when selecting indicators. A mathematical model using different combinations of options indicators of innovation activities of enterprises. Mathematical models are made and used for three generalized purposes such as for an explanation, a prediction and a management. The study suggested indicators for assessing the potential of the enterprise. It is necessary to prioritize the financing of innovation enterprises. In the article conclusions about possible directions for further research and also presents some limitations of the analysis."

Copyright

© 2014 Andrey Sergeevich Nechaev, Dmitry Alekseevich Antipin and Oksana Victorovna Antipina. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.