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Model with distributed lags dynamics of innovative activity of industrial enterprises

Boldyrevskii P.B. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( bpavel2@rambler.ru )

Kistanova L.A. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( lakistanova@mail.ru )

Journal: Economic Analysis: Theory and Practice, #25, 2014

In the present work, we consider the dynamics of the main indicators of innovation activity of Russian industrial enterprises and examine their relationship. Using the methods of time series analysis built a dynamic model with distributed lags on the basis method Almon. It is shown that the proposed model adequately describes the analyzed statistical data and can be used to describe the processes of innovation development and forecasting


A mathematical-statistical model of innovation activity of industrial enterprises

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 )

Journal: Economic Analysis: Theory and Practice, #15, 2014

The increasing competitiveness of Russian industry is possible only through the development of innovation activity; therefore, enterprises should develop and follow the strategic concept of innovation development. The paper discusses the dynamics of the indicators of innovation activity of the processing-industry enterprises, which play an important role in the economy. Using econometric methods, the authors made a regression model on the principal components that allows determining the influence of the factors on the dynamics of innovation activity of metallurgical production and production of finished metal products. The authors concluded that the proposed mathematical-statistical model is adequate and can be used by enterprises in developing a strategic and innovation concept.


Analyzing the innovation and investment activities of Russian agricultural engineering companies

Boldyrevskii Р.B. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( bpavel2@rambler.ru )

Kistanova L.A. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( lakistanova@mail.ru )

Journal: Economic Analysis: Theory and Practice, #2, 2016

Subject The article analyzes the current state of innovation and investment in agricultural engineering and offers mathematical models for investment management. It also considers factors contributing to and limiting the development of the agricultural engineering sector.
Objectives The aim of the study is to review the dynamics of innovation processes in the Russian agricultural engineering industry based on the analysis of mathematical models of relevant indicators interrelation, including the profitability of investment projects aimed at innovation.
Methods To build mathematical models and obtain quantity-related findings, we applied methods of systems analysis, econometrics and mathematical analysis. For multiparameter calculations and graphing, we used MathCad 15 application package.
Results The paper presents polynomial models of trends in the indicators of innovation activity of enterprises and their comparative analysis. We formulated and analyzed the life cycle stages of innovation product of agricultural engineering enterprises. We offered a method to estimate the investment project payback period, taking into account the cost of each phase of the project.
Conclusions The findings show that the main factor in increasing the efficiency of innovative activity of agricultural engineering enterprises is a reduction in investment repayment period through the income generated from innovation. We offer a calculation and graph method to estimate the distribution of investment in time, which enables to determine the repayment time of the total amount of investments in innovative projects.


A Cluster analysis of Russian industrial enterprises' economic sustainability

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

Igoshev A.K. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( akigoshev@iee.unn.ru )

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

Journal: Economic Analysis: Theory and Practice, #10, 2017

Subject The article reviews the elements and factors of economic sustainability and offers mathematical models enabling to assess the economic condition of Russian industrial enterprises under current market conditions.
Objectives The purpose is to build economic and mathematical models to analyze factors of economic stability and assess conditions for their stabilization and development.
Methods To build mathematical models and obtain quantitative findings, we employ methods of systems theory, and cluster and factor analysis. Relevant statistical data of the Federal Service of State Statistics of the Russian Federation for the period from 2010 to 2015 served as the information base for the models' development. We performed multiparameter calculations and plotting, using the Statistica software package.
Results We present the results of cluster analysis of an array of economic indicators reflecting the economic stability of industrial enterprises. We distinguish and compare two main clusters. The paper formulates and analyzes conditions, under which industrial enterprises are incorporated in a certain cluster. We present a graphical interpretation of the clustering process, along with numerical estimates.
Conclusions We offer a technique of multiparameter analysis of industrial enterprises' economic activity, enabling to evaluate their economic sustainability based on a cluster analysis. It shows that at present the enterprises of the fuel and energy complex, steelmaking industry, and finished metal product manufacturers are the most stable enterprises of the Russian industry.


Models to manage the innovation activity of agricultural engineering enterprises based on the graph theory

Boldyrevskii P.B. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( bpavel2@rambler.ru )

Kistanova L.A. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( lakistanova@mail.ru )

Gudoshnikov V.A. SAREX, Machinery & Industrial Group N.V., Saransk, Republic of Mordovia, Russian Federation ( VladimirSAREX@mail.ru )

Journal: Economic Analysis: Theory and Practice, #30, 2015

Subject The current challenges related to increasing the competitiveness and economic efficiency of Russian industrial enterprises necessitate improving and searching for new forms and methods of managing all aspects of their operation. One of the most important areas of handling these issues is the development of effective innovation activities of industrial enterprises. It is therefore highly relevant to develop mathematical models and algorithms to manage innovation and investment projects enabling to increase the economic efficiency and sustainability of production systems.
     Objectives
The objective of the study is a mathematical simulation of managing the innovative activity of industrial enterprises. We analyze the status of innovation and investment in agricultural engineering, mathematical models of investment management, and the factors that contribute to and limit the development of the agricultural engineering sector.
     Methods To build mathematical models reflecting the optimal allocation of investments, we employed the systems analysis and the graph theory. Building the resulting graph of investment allocation rests on the Bellman method (the dynamic programming method).
     Results We have built mathematical models using specific economic results of the Russian machine-building industrial group Machinery & Industrial Group N.V., one of the largest Russian production associations in the field of agricultural engineering. The specific features of the group are its vertically integrated structure and high rates of innovative activity.
     Conclusions The obtained findings may be interesting for companies with vertically integrated structure of production management to forecast expected profits depending on the amount of investment in innovation.


Prediction of the dynamics of innovation activity of industrial enterprises

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 )

Journal: Economic Analysis: Theory and Practice, #8, 2015

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.


Forecasting models of the main indicators of innovative activity of the industrial companies

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 )

Journal: Economic Analysis: Theory and Practice, #29, 2014

Strengthening enterprise competitiveness of the Russian industry at the current stage is possible only through the development of innovation. The main indicators of innovation activity of enterprises are the values of the shipped innovation products and cost of some technological innovation. For the effective management of innovation and development of enterprise, the issues related to the development of models of quantitative predictions and forecast scenarios to assess the determinants of innovation development are highly relevant. The present paper analyzes the dynamics and forecasting of innovation activity of industrial enterprises of the Russian Federation in the manufacture of machinery and equipment. On the basis of collected and processed statistical data for 2002-2012, we have developed mathematical-statistical models to perform a quantitative forecast of the shipped product innovation of industrial enterprises in this kind of economic activity. Forecasting models are based on a time series analysis. We are considering such methods for predicting as the trend component analysis and forecasting based on Autoregressive models. We are showing that a polynomial model is ineffective for trend prediction, for it does not provide sufficient accuracy of the forecast. The results obtained aimed at the construction and analysis of Autoregressive time series models allow us to conclude that the forecast provides sufficient accuracy of the Autoregressive model developed using the method of instrumental variables. The introduction of a new instrumental variable allows us to estimate the parameters of the regression dynamic model built by using standard methods of Econometrics. The obtained model is statistically significant and is characterized by small autocorrelation in residues (random deviations). When constructing an instrumental variable, we used time series, reflecting the dynamics of the cost of technological innovation. The proposed model prediction error does not exceed 9.5%, which determines the possibility of its use for analyzing and predicting the values of basic indicators of innovation activity of enterprises.


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