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

2017 ◽  
Vol 22 (3) ◽  
pp. 258-273
Author(s):  
Yu.A. Kuznetsov ◽  
◽  
V.I. Perova ◽  
E.I. Lastochkina ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Network Analysis ◽  
Russian Federation ◽  
Capital Investment ◽  
Fixed Capital ◽  
Neural Network Analysis ◽  
The Russian Federation ◽  
Fixed Capital Investment

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

2017 ◽  
Vol 22 (3) ◽  
pp. 258-273
Author(s):  
Yu.A. Kuznetsov ◽  
◽  
V.I. Perova ◽  
E.I. Lastochkina ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Network Analysis ◽  
Russian Federation ◽  
Capital Investment ◽  
Fixed Capital ◽  
Neural Network Analysis ◽  
The Russian Federation ◽  
Fixed Capital Investment

Fixed investment: Trend assessment

2021 ◽  
Vol 19 (7) ◽  
pp. 1334-1354
Author(s):  
Lyudmila V. SHALAEVА ◽  
Ekaterina V. SHALAEVА
Keyword(s):  
Russian Federation ◽  
Capital Investment ◽  
Federal District ◽  
Fixed Investment ◽  
Fixed Assets ◽  
Perm Krai ◽  
Trend Assessment ◽  
The Russian Federation ◽  
Fixed Capital Investment ◽  
Investment In Fixed Assets

Subject. This article considers investment in fixed assets as an economic growth factor. Objectives. The article aims to identify trends in the field of investment in fixed assets in the Perm Krai, Volga Federal District, and the Russian Federation. Methods. For the study, we used the methods of analysis, synthesis, comparison, and generalization. Results. The article presents the changes in and patterns of fixed investment for 2015–2019, and it assesses the level of fixed investment in the Russian Federation, Volga Federal District, and the Perm Krai. Relevance. The results of the study can be used to improve the effectiveness of management decisions on fixed capital investment.

scholarly journals Estimation of Fixed Capital Investment in SMEs: the Existing Differentiation in the Russian Federation

2018 ◽  
Vol 9 (1) ◽  
pp. 65-78 ◽  
Author(s):  
Iuliia Pinkovetskaia ◽  
Vladislava Slepova
Keyword(s):  
Public Management ◽  
Capital Investment ◽  
Management Education ◽  
Specific Weight ◽  
Fixed Capital ◽  
Future Studies ◽  
Methodical Approach ◽  
The Russian Federation ◽  
Total Observation ◽  
Fixed Capital Investment

Abstract Background: One of the goals of Russia economy is to increase SMEs specific weight in GDP per 100% by 2030. Objectives: The purpose of this work is the assessment of the investments into fixed capital of SMEs and influence of factors such as size categories, types of economic activity and territorial placement, needed for the fulfillment of this goal. Methods/Approach: The comparative analysis of SMEs investments is based on relative indicators, which are calculated per enterprise and per worker. The research was conducted with the usage of the official statistical information obtained in the course of total observation of activity of the enterprises in 2015. Modelling of empirical data was based on functions of normal distribution. Results: We defined the values investments in SMEs which are located in 82 regions and related to three categories and six types of activity. We revealed regularities of distribution of investments calculated per enterprise and per worker, and identified the regions with the lowest investments in SMEs. Conclusions: New knowledge of the investment in the fixed capital in the Russian SMEs was achieved. Proposed information and tools are applicable for justification of the investments needed for the SMEs development. The methodical approach can be used in the future studies, as well in entrepreneurship and public management education.

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural

Towards New Policy Incentives for Fixed Capital Investment and Technological Upgrades in Russia

2011 ◽  
pp. 43-56
Author(s):  
A. Apokin
Keyword(s):  
Economic Policy ◽  
Capital Investment ◽  
Empirical Studies ◽  
Fixed Capital ◽  
Policy Framework ◽  
Private Companies ◽  
Russian Economy ◽  
Technological Modernization ◽  
Fixed Capital Investment ◽  
Policy Incentives

The paper approaches the problem of private fixed capital underinvestment in Russia. The author uses empirical studies of the Russian economy and cases of successful technological modernization to outline several groups of disincentives for private companies to perform fixed capital investment in Russia. To counter these constraints, a certain incentive-based economic policy framework is developed.

Network Analysis of the Integration Level of the Universities Participating in Project 5-100 in the International Higher Education Area

2019 ◽  
Vol 28 (11) ◽  
pp. 155-167
Author(s):  
P. A. Zhdanov ◽  
N. A. Polikhina ◽  
E. Yu. Sema ◽  
L. V. Kazimirchik ◽  
I. B. Trostyanskaya ◽  
...  
Keyword(s):  
Higher Education ◽  
Network Analysis ◽  
International Education ◽  
Russian Federation ◽  
Education System ◽  
Point Of View ◽  
International Higher Education ◽  
Scientometric Analysis ◽  
Higher Education System ◽  
The Russian Federation

The paper analyzes measures adopted by the Russian Federation on internationalization and globalization of the higher education system, its integration into the international scientific and education area. One of the initiatives of the authorities of the Russian Federation in this direction is Project 5-100, designed to increase the competitiveness of both a selected group of universities and the Russian higher education system as a whole. Among the successful practices of Project 5-100, one can identify the presentation of a single stand of participating universities at the international education exhibitions APAIE, EAIE, NAFSA. Within this study, we explore the cooperation of the universities participating in Project 5-100 with potential international partners at global educational exhibitions by means of network analysis with graphs. The effectiveness of such cooperation from the point of view of integration of the universities from this group into the international higher education area is determined through estimations of the usefulness of participation in such events made by the universities and through scientometric analysis. As a result of this study, it was revealed that active participation in international educational exhibitions including negotiating, establishing contacts with international partners, contributes significantly to the promotion of the universities participating in Project 5-100 in the international arena.

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