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Economic Analysis: Theory and Practice
 

Prediction of the dynamics of innovation activity of industrial enterprises

Vol. 14, Iss. 8, FEBRUARY 2015

PDF  Article PDF Version

Available online: 15 February 2015

Subject Heading: ECONOMIC AND MATHEMATICAL MODELING

JEL Classification: 

Pages: 60-66

Boldyrevskii P.B. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation
bpavel2@rambler.ru

Kistanova L.A. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation
lakistanova@mail.ru

Rakhmelevich I.V. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation
igor-kitpd@yandex.ru

One of the most important factors determining the currently increasing competitiveness and successful functioning of the Russian industry is the development of all areas of innovation. Therefore, companies should develop effective methods and adhere to the concept of strategic innovation-driven growth. In this paper, we analyze the dynamics of innovation activity indicators of manufacturing enterprises, which play an important role in the economy. Using econometric techniques, we have built regression models to determine the effect of factors on the dynamics of innovation activity of the machine-building complex. Based on the collected and processed statistical data reflecting the innovative activity of industrial enterprises of the Russian Federation in the field of machinery and equipment for the period from 2002 to 2013, we have developed dynamic models enabling to forecast the volume of shipped innovative products and industrial machinery and equipment. The set of criteria for assessing the quality of regression equations leads to the conclusion that the proposed mathematical and statistical models are adequate and can be used by enterprises in developing the innovative strategic concept. On the basis of the proposed econometric equations, we have developed models that include the differential equations, which take into account a continuous connection between the factors and the response of the system, and the relationship between the factor and the dynamics of change in the response under the influence of this factor. We demonstrate the advantages of such models as compared to the multifactorial regression models, and the prospect of their use to predict and parameters and analyze the sustainability of innovation processes development.

Keywords: innovation-driven activity, production, machinery and equipment, dynamics model, differential equations, forecasting

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