Проблемы финансирования инновационной деятельности
The article discusses the new organizational form of the activity of a regional industrial complex in the form of a system and structure that provide for the interaction of innovation-active enterprises and venture investors on the market.
The paper studies the problems of venture investment development in Russia. The conclusion on the need for serious changes in the existing legislation of Russia in the sphere of venture investment is made.
Venture capital (VC) provides financial and managerial support for new innovative ideas at the initial stages of commercialization. It has helped to find the market for many radical innovations of 20th century, including personal computer, Internet and genetic engineering.
As a part of market economy venture business was not stable from the very beginning. The periods of rapid growth alternated with deep recessions. However each time VC revived anew as the Phoenix due to its very important function in modern knowledge-based economy.
This report presents an analysis of statistical data that prove the existence of several cycles in VC dynamics in the USA and the Great Britain. The main factors of these cycles formation are discussed. The author proposes two possible scenarios of development of VC market for the first 30 years of the new 21st century. A hypothesis is put forward about the relation between VC cycle's amplitude and a phase of Kondratieff's cycle.
This monograph focuses on the nature of factors and mechanisms of the innovation processes in the Regional innovation systems with catch-up type of economy. The monograph shows that the further development of cooperation of innovation entities and the development of technological entrepreneurship in the regions of Russia is impossible without a planned and systematic processes of regionalization of the innovation business ecosystem.
The monograph substantiates that the state-owned private Regional Center for Incubation and Acceleration and the multifunctional state Single Regional Investment Fund should become the basis for the development of the ecosystem of innovative entrepreneurship in the region of the country.
The monograph is intended for researchers, graduate students, students specializing in the field of innovation management, as well as managers and decision makers who are responsible for the development of regional innovation systems.
The monograph proposed promising forms and models of the innovation process, contributing to the development of the innovation process in the Russian regional innovation systems, in the conditions of a shortage of technological entrepreneurs and systems of business angel financing.
This monograph proposes a model of the innovation funnel with positive feedback, which is shown as the basis for the development of models a new generation of innovation process (G7), which can be effective in conditions of accelerated development of industries and markets.
The monograph is addressed to specialists in innovative management and R & D, innovation systems, students of economic faculties and business areas preparation of higher educational institutions, graduate students and researchers.
Despite the widespread use of project and program management methodologies in various fields of practical activity, they have not yet become widespread in the venture capital business. An attempt was made to find common ground between these two areas that are developing rapidly today and to assess the prospects for their closer integration.
Currently, the venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high risk level. In the developed countries it plays a key role in transforming innovation projects into successful businesses and creating prosperity of the modern economy. Actually in Russia there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates, there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyze the influence of the previous round such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. As a result of the research, the participation of investors with first-class reputation has a small impact on an indicator of the value of investment of the second round. The expected positive dependence of the second round investments on the forecasted market growth rate at the moment of the deal is also rejected. So, the most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the startup teams which can attract more money on the start, and the target market growth is not the factor of crucial importance.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.