Principles for a New-generation Innovation Policy
Today the Russian economy is facing long-term challenges, connected with the global rivalry and exhaustion of sources for growth of raw materials exports. These challenges have led to activation of S&T and innovation policies during the last decade. The shift towards innovation-based growth has been declared in Russia as the key objective of the state policy and the only possible development model. During recent years a number of strategic documents was adopted, which were aiming at public support to S&T, integration between science and universities, creation of organizational, legal and economic incentives for innovation, improvement of the IPR regulation, etc. Further policy agenda for innovation is being intensively discussed.
Today the increasing number of constant consumers is a strategic aim for any organization which is possible to be achieved only under condition of continuous perfection of organizational activity quality. If the service representation doesn't correspond to the consumers’ expectations they lose their interest to the service organization, if it does correspond or surpass their expectations they probably would readdress to service provider. For this reason the service organization should more precisely reveal consumers requirements and expectations, namely provider should constantly measure its service quality.
In the given work approaches by the Russian and foreign researchers in the field of quality management are studied and analyzed in details, namely:
- approaches to the «service quality» definition;
- the basic components of service quality management process;
- service organization quality model.
The purpose of research work consists of ISQM (Innovation System of Quality Management) model creation taking into account features of TCS providing, which, in turn, is targeted on TCS company purposes achievement in the field of quality by means of:
- setting the control values of TCS quality indicators;
- measuring of the reached results and their comparison with expected results;
- effective management decision making as a result of carrying out the analysis of managerial activity in the field of quality on the basis of the report containing recommendations for the company activity improvement, prepared due to the results of measuring and collecting quality indicators.
The data book presents the results of statistical innovation surveys in the Russian Federation. It contains internationally compatible indicators characterizing the level of innovative activity in industry and services. The publication covers statistical data reflecting innovation expenditure and output, co-operational linkages, and factors hampering innovation. Specific chapter is devoted to ecological innovation. International comparisons with a wide range of innovation indicators are provided as well. The data book includes information of the Federal Service for State Statistics, Organisation for Economic Co-operation and Development, European Commission, Eurostat, national statistical agencies, and results of own methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.
As the economies of western countries move from primarily resource-based to knowledge-based, and trade liberalization limits what governments can do through direct action, the landscape of innovation is changing and policymakers must react accordingly. This exciting new book examines the challenges that policy makers face in responding to a new environment. The book addresses how governments are now seeking to drive innovation through new forms of R&D policies, through public procurement, skills development, entrepreneurship and innovation culture to name but a few of the approaches.
Innovation Policy Challenges for the 21st Century explores these and other contemporary issues in innovation, reviewing the state of the art literature and consolidating current thinking at the frontiers of innovation. The volume debates and presents scattered and anonymous material in a coherent way, with a particular focus is on ‘hot topics’ in the field of innovation studies that have been previously under-researched. The book is divided into four key themes: government as a key actor in the innovation process, entrepreneurs as innovators, skills and competences required to maintain and improve innovation performance in Europe and finally, the wider context in which innovation policy develops.
Chapter 6 presents an analysis of Russian innovation system accompanied by an overview of state science, technology and innovation (STI) policy practice.
The authors cover the most urgent institutional cleavages, including the split-offs of science and industry, issues of institutional model of the R&D sector, sectoral discrepancies and regional polarization.
An outline of STI policy framework evolution is presented, including the most recent Strategy for Socio-Economic Development of Russia till 2020 topics. A special regard is paid to linkage-stimulating policy instruments, including grants for joint research for Universities, R&D organisations and companies, technology platforms, regional innovation clusters program and elaboration of innovation development plans for state-owned companies.
Over the last two decades national policy makers drew special attention to the implementation of policy tools which foster international cooperation in the fields of science, technology, and innovation. In this paper, we look at cases of Russian-German collaboration to examine the initiatives of the Russian government aimed at stimulating the innovation activity of domestic corporations and small and medium enterprises. The data derived from the interviews with companies’ leaders show positive effects of bilateral innovative projects on the overall business performance alongside with major barriers hindering international cooperation. To overcome these barriers we provide specific suggestions relevant to the recently developed Russian Innovation Strategy 2020.
The authors of this paper present the results of their studies of genesis of the notion «innovation» and adjacent terms in regulatory legal acts of the Russian Federation, since 1998.
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.