Pilot Innovative Territorial Clusters in Russia: A Sustainable Development Model
Leading countries consider regional clusters as an efficient tool of interaction between actors of a region’s innovation system, which allows generating new poles of economic growth. There is a plenty of literature describing positive experience of clusters’ public support. In Russia, this process is still at an early stage. Russia’s strategy of innovative development until 2020 includes a program for supporting pilot innovative regional clusters. The aim is to make these clusters self-sustained.
Emergence and outlook of a cluster’s evolution are largely dependent on a range of basic conditions, such as: the urban environment; available critical mass of specialized companies; internal competition and openness to the outside world. There is always a risk that without government support the cluster will not be able to shift to the desired trajectory.
The paper presents a detailed overview of research devoted to the best practices of implementing state cluster policy. It provides a detailed analysis of the characteristic features of successful clusters, evaluates matching of Russia’s pilot innovative regional clusters to these criteria, as well as quantitative comparison between domestic and foreign clusters, suggests a model for sustainable cluster development.
The empirical base of the study is the development programmes of pilot innovative regional clusters, submitted to Ministry of Economic Development of Russia through 2012 in the framework of a special contest, as well as the results of the survey, commissioned by the JSC "Russian Venture Company" at the end of 2013.
The state policy on stimulation of development innovative clusters at regional level is considered. By the analysis of experience of realisation кластерных initiatives in various regions, the basic directions of assistance to their development, public authorities and local government are established. The basic reference points of the state policy aimed at creation clusters are defined. The technique of identification innovative territorial clusters is proved.
The paper investigates the process of evolutionary transformation of cooperation and integration modes of industrial and construction enterprises in St.-Petersburg. The study has been performed at the period since 1998 to nowadays. The network form of integration was chosen as the main objet of this research. The paper is aimed at identifying the path of knowledge management development in different types of networks.
One of the peculiarities of the network form of integration is the high level of independence of the network participants that interact with each other. Key issues in this cooperation would be the following:
How to organize an effective transfer of knowledge and technologies within a network?
How to find a balance between open systems of innovation and the protection of the intellectual property of network participants?
How to evaluate the intellectual capital of a network? Is it necessary to make an assessment for each participant separately? Should one take into account synergies that increase the value of the intellectual capital because of the network participants’ interaction and knowledge sharing?
How to increase competitiveness of each company and of the whole network by the effective use of the intellectual capital?
How to measure the impact of open innovations on the intellectual capital of the companies interacting within a network?
Thus, it is important to reveal how knowledge management system is developing within a network of inter-related enterprises.
On the base of interviews of top-managers of companies in industrial and construction companies there were identified five different types of networks and knowledge management systems within these types. It is demonstrated how the knowledge management model is growing and becoming mature from the amorphous type of network cooperation to the integrated type. Factors, influencing this evolutionary development, have been revealed. Also, the paper proposes an approach to the evaluation of knowledge management systems based upon the value-based management indicators.
Purpose: Today many programs supporting clusters are introduced in Russia and other countries. The purpose of the research is to provide a relevant quantitative study assessing the effectiveness of cluster policy. Design/methodology/approach: In this paper, the effectiveness of Russia's cluster policy is analyzed using regression analysis. The survey covers data on 516 Russian enterprises divided into two groups: companies from supported clusters and firms that are members of similar but not supported clusters. To the classical variables of Cobb-Douglas production function (companies’ revenue, number of workers, capital of the company) we added cluster program dummy variable. The main question of the research is whether companies in supported clusters operate more effectively than other companies. Findings: The analysis provided quite interesting results. It was found that governmental support which was received by 27 innovative clusters didn’t have any effect on the revenue of the companies. This means that Russian innovation clusters work equally efficiently, regardless of whether they have government support. Research/practical implications: We have not found short-term effects on the enterprises associated with the supported clusters. The obtained results indicate that cluster policy conducted from 2012 to the present time requires adjustment. In this regard, the authors propose recommendations on further implementation of cluster policy. Originality/value: We have described the production function of Russian companies which work in the clusters. We have found that there is no significant effect on companies' output from government supporting of the clusters in Russia. Effectiveness of cluster policy has never been evaluated empirically before this research. Keywords: Cluster, Cluster Policy, Cluster Policy Impact Assessment, Innovative Territorial Clusters
Public research plays an extremely important role in social and economic development, and has implications for industry, services, education, training, the creation and diffusion of knowledge, management etc. In turn, R&D and innovation activities in the business sector are becoming increasingly open. Being influenced by increasingly tightened global competition, companies are entering into partnerships with other companies, universities or public research institutions (PRIs) to leverage competences from different places and organizations to foster innovation. The search for partners and the management of many co-operations itself are new challenges especially in terms of administering intellectual property rights. Universities and PRIs must respond to the changing requirements imposed by companies while maintaining their unique positions as research and science related institutions. The overall framework conditions for these actors are changing, which in turn requires new government policies especially given the slowdown in key performance indicators of the commercialization activities of PRIs.
The paper highlights recent trends and approaches related to knowledge and technology transfer from public research and education to industry. It considers legislative initiatives to target industry engagement and research personnel, new technology transfer office models, collaborative intellectual property (IP) tools, and initiatives to facilitate access to public research results. The authors stress that the quality of research has a strong influence on knowledge and technology transfer. In turn, contrary to the widespread belief that knowledge and technology transfer activities might negatively impact scientists’ academic work several studies found evidence that the engagement of scientists in technology transfer and commercialization activities does not have negative impacts on the quality and quantity of academic research. In fact, scientists who are actively engaged in technology and knowledge transfer, i.e. through patenting, also enjoy a high scientific reputation and in most cases do excellent scientific work.
Ces derniers temps, le nombre et la qualité des clusters ont pris une expansion visible en Russie. Avant l’adoption d’une politique de clusters au niveau fédéral, à la fi n de la décennie 2000, seules quelques régions avaient fait part de leur intention de contribuer au développement de ceux qui existaient sur leur territoire et dont peu marchaient vraiment. La situation, en outre, a radicalement changé au cours des dernières années.
The Global Innovation Index (GII) aims to capture the multi-dimensional facets of innovation and provide the tools that can assist in tailoring policies to promote long-term output growth, improved productivity, and job growth. The GII helps to create an environment in which innovation factors are continually evaluated. In 2016, the theme for this year’s edition of the GII is: ‘Winning with Global Innovation’. Science and innovation are more internationalized and collaborative than ever before. The GII 2016 explores global innovation as a win-win proposition; a rising share of innovation is carried out through collaborative networks, leveraging talent worldwide.
.The most recent innovation models increasingly postulate external relationships of innovators in many different shapes including the acquisition and incorporation of knowledge and technology from outside the organization. Such knowledge and technologies can be either publicly accessible or privately owned by other companies, individuals or research institutions. Furthermore, external knowledge and technologies are available either in a codified and published or personal and unpublished, undisclosed, form. R&D service providers and public and private research institutions, and increasingly training institutions contribute much to build, develop and diffuse existing, publicly available “knowledge and technology pools.”
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.