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Researching the trends in innovation activity of Russian regions using the neural simulation

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Zaitseva K.V. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( mmep@iee.unn.ru )

Journal: Economic Analysis: Theory and Practice, #5, 2017

Importance The introduction of advanced technologies is associated with the level of innovative development of regions of the Russian Federation. Expenditures in technological innovation are of particular importance in the statistics of innovation in view of economic importance of the latter.
Objectives The paper aims to study trends in innovation activity of Russian regions using neural networks.
Methods We apply neural simulation on the basis of neural networks that are trained without a teacher, namely, Kohonen self-organizing maps realized in the Viscovery SOMine software package.
Results The research identified the nature of changes in innovative indicators of Russian regions and showed their innovative development disparity. The regions were distributed in four clusters (groups) by the level of this activity. Cores with invariable composition of regions were formed in all clusters during the period under investigation. Most of the regions are included in the core of cluster with significantly lower rates of innovation activity as compared to the average values across Russia.
Conclusions and Relevance The results of the research have practical importance for formation and implementation of innovation policy of Russian regions. The analysis of trends in innovation activity leads to conclusion that it is necessary to adopt a set of measures to boost innovative processes countrywide, especially in regions with underdeveloped innovation.


A Neural Network Analysis of the Fixed Capital Investment Trends in Regions of the Russian Federation

Kuznetsov Yu.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( Kuznetsov_YuA@iee.unn.ru )

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Lastochkina E.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( mmep@iee.unn.ru )

Journal: Digest Finance, #3, 2017

Importance The article considers the changes in and characteristics of the investment activities and behavior of the Russian Federation regions.
Objectives The article aims to analyze and describe the trends and characteristics of fixed capital investment behavior of the Russian Federation regions to ensure the economic growth and socio-economic development of the country and regions.
Methods We examine the regions' investment activities for the period from 2012 through 2014 using the neural modeling methodology on the basis of thirteen indicators characterizing the investment activities of the regions and defining their socio-economic development prospects. We also apply the Self Organizing Map using the STATISTICA software. Data of the Federal State Statistics Service of Russia on fixed investment by type of economic activity in the regions underlie our study.
Results The paper shows certain characteristics and peculiarities of the investment performance and behavior of the Russian Federation regions.
Conclusions and Relevance The cluster analysis of the Russian Federation regions' investment activities shows their uneven nature. The findings indicate the need for comprehensive measures to help change the structure of the investments involved and stimulate investment activity in all regions of the Russian Federation.


A neural network analysis of the fixed capital investment behavior of regions of the Russian Federation

Kuznetsov Yu.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( Kuznetsov_YuA@iee.unn.ru )

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Lastochkina E.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( mmep@iee.unn.ru )

Journal: Regional Economics: Theory and Pactice, #7, 2017

Subject The article considers the changes in and characteristics of the investment activities and behavior of the Russian Federation regions.
Objectives The article aims to analyze and describe the trends and characteristics of fixed capital investment behavior of the Russian Federation regions to ensure the economic growth and socio-economic development of the country and regions.
Methods We examine the regions' investment activities for the period from 2012 through 2014 using the neural modeling methodology on the basis of thirteen indicators characterizing the investment activities of the regions and defining their socio-economic development prospects. We also apply the Self Organizing Map using the STATISTICA software. Data of the Federal State Statistics Service of Russia on fixed investment by type of economic activity in the regions is the basis of our study.
Results The paper shows certain characteristics and peculiarities of the investment performance and behavior of the Russian Federation regions.
Conclusions The cluster analysis of the Russian Federation regions' investment activities shows their uneven nature. The results obtained indicate the need for comprehensive measures to help change the structure of the investments involved and stimulate investment activity in all regions of the Russian Federation.


Social and economic development of the Syrian Arab Republic during the pre-crisis period: A retrospective analysis

Kuznetsov Yu.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( Kuznetsov_YuA@iee.unn.ru )

Perova V.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Waddah Al Jarad. c National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( waddah.ja@gmail.com )

Journal: Economic Analysis: Theory and Practice, #7, 2017

Subject The article reviews the specifics of economic development of the Syrian Arab Republic during the pre-crisis period.
Objectives The purpose of the study is to analyze and describe trends in the economic development of the Syrian Arab Republic to define its actual economic situation during the pre-crisis period and prospects for economic advancement and social progress of the entire country and its certain provinces subject to peaceful development.
Methods We employ neural simulation based on indicators characterizing the economic condition of the country as a whole and its certain provinces. The research tools include self-organizing maps based on Deductor analytical platform.
Results The paper reveals major trends in GDP, focuses on economic restructuring of the Syrian Arab Republic. Based on five indicators of economic activity of provinces in the private sector, we performed a cluster analysis of their development. It shows that in 2007–2010, fourteen provinces were divided into three groups (clusters). We describe the composition and characteristics of each cluster, show changes in indicators of province development by clusters. The forecast for 2011–2017 is quite optimistic as long as peace is maintained.
Conclusions and Relevance The revealed specific features of socio-economic status of the Syrian Arab Republic before 2011 are indicative of unrealized opportunities for the country's economy since then.


The neural network analysis of trends in innovative activity of the regions of the Russian Federation

Perova V.I. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( perova_vi@mail.ru )

Goncharova D.G. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( mmes@mm.unn.ru )

Journal: Financial Analytics: Science and Experience, #29, 2015

Importance The Russian economy undergoes the transition from its export and raw materials focus to innovation. Scientific and technological achievements should contribute to a higher standard of living of population and competitiveness of the country and its regions.
     Objectives The article aims at analyzing trends in innovative activity of the Russian regions. For this, we examined data of the Federal State Statistics Service on economic and social development of the Russian regions.
     Methods We examined the trends in innovative activities of the regions within the period of 2009 to 2013 using the neural network modeling and such innovation indicators as headcount of staff who deal with developments (technologies), the number of patent applications concerning inventions, useful models; the number of patents issued for inventions, useful models; current internal costs for fundamental, applied research and development. The research uses the Kohonen self-organizing maps via MATLAB, i.e. self-trained neural networks.
     Results The research allows identifying the specifics of trends in innovative activities in the Russian regions and determining innovative development centers. The regions get split into five groups (clusters) in terms of their innovative activity. During the period, each cluster formed a nucleus with the constant content. The highest figures are seen in the nucleus of the cluster, which includes the regions with significantly lower indicators of innovative activity as compared with the average indicators throughout Russia.
     Conclusions and Relevance The results of the research indicate the uneven nature of innovative activity in the Russian regions. To modernize the Russian economy successfully, it is necessary to undertake a set of measures stimulating innovative activity in every region, rather than in the most developed ones.


Virtualization of financial sector as trend and adapting to current economic conditions of business

Novikov V.S. PhD in Economics, Associate Professor of department "Management, Marketing and entrepreneurship, the Southern Institute of Management ( vs.novikov@mail.ru )

Perova A.E. PhD in Economics, Associate Professor of department "Management, Marketing and entrepreneurship, the Southern Institute of Management ( nasper13@mail.ru )

Journal: Financial Analytics: Science and Experience, #32, 2012

In the article virtualization of the financial sphere of business process is considered. The category "virtualization of the economic sphere", including financial is characterized, their schematically interpretation is given; the characteristic of such categories, as "electronic payment system", "electronic money", "digital signature" is provided.


New mechanisms in practice of foreign investments of the USA

Perova M.K. Institute of World Economy and International Relations, Moscow, Russian Academy of Science ( mkperova@yandex.ru )

Journal: Economic Analysis: Theory and Practice, #13, 2014

The study focuses on the outward investment of the US private equity (PE) firms. Private equity is essentially a way to invest in some asset that isn't publicly traded. This article examines main factors, stimulating foreign activity of US PE firms, including their powerful national capabilities; features of PE investment model; geographic distribution of US PE investment. Attention is focused on the adaptation of PE firms in the conditions of global crisis 2008-2009 and their further strategy.


Management of innovative activity of small-scale business as the factor of potential of development of Krasnodar territory

Zelinskaya M.V. candidate of economic sciences, associate professor of chair of the accountant, analysis and audit’s, South Institute of Management ( zelinskaya@inbox.ru )

Perova A.E. candidate of economic sciences, associate professor of chair of the finance and the credit, the Kuban institute of the international business and management ( nasper13@mail.ru )

Journal: Financial Analytics: Science and Experience, #30, 2011

Small-scale business can become the catalyst of innovative activity in economy of regions and the countries as owing to the specificity it constantly faces necessity to make the newest technologies and products. However to solve a problem of transition of Russia to the economy based on knowledge, it is necessary to change small-scale business operating conditions.


Estimation of the investment factor of development of innovative economy of Krasnodar territory

Zelinskaya M.V. associate professor, professor assistant of chair of the accountant, analysis and audit’s, South institute of management ( zelinskaya@inbox.ru )

Perova A.E. associate professor of chair of the Finance and the credit, the Kuban institute of the international business and management ( nasper13@mail.ru )

Asheulov A.V. graduate student of chair of the Finance and the credit, the teacher the Kuban institute of the international business and management ( asheulov.16@mail.ru )

Journal: Financial Analytics: Science and Experience, #9, 2011

Level of investment appeal of subjects of managing in modern Russia is strongly differentiated. Authors study character of investment influence on economic system of Krasnodar territory of subjects of different levels of the organization of the economic relations, different objects on structure of economic process, functional characteristics, scales of localization of space.


In search of new investment decisions

Perova M.K. Institute of World Economy and International Relations, Russian Academy of Sciences, Moscow, Russian Federation ( mkperova@yandex.ru )

Journal: Financial Analytics: Science and Experience, #25, 2014

The trend towards relocation of overseas activities becomes more evident in today's world. The companies, which had previously left their domestic markets in search of countries with the lowest costs, are now returning to invest in their domestic markets. The focus of the research is the re-shoring of the US manufacturing companies. The author examines the main determining the investment decision (to reduce costs in the United States economy, technological innovation, rising increasing transportation costs, proximity to centres of research and development and consumer preferences). The author also dwells on the implications of this decision for the US economy and the difficulty of implementing this approach.


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