Interregional Innovation Research Articles

Guangdong’s New R&D Institutes

In pursuit of technological development, China has created new organizations to promote innovation. This brief examines New Research and Development Institutes (NRDIs), which are designed to foster knowledge transfer to industry. NRDIs were pioneered in Guangdong province in the 1990s, and have gained prominence in China’s national science, technology, and innovation policies since the 13th Five-Year Plan (2016–2020). NRDIs are defined by their market orientation and extremely flexible organizational form. They work by establishing “innovation platforms” with local governments and private knowledge actors to carry out research and development (R&D), commercialize scientific and technological achievements, incubate local technology industries, and cultivate high-end talent. NRDIs have been instrumental to regional development in Guangdong, and especially Shenzhen, where they have succeeded in attracting talent from outside the region. NRDIs have important policy implications for international competition for talent. Understanding NRDIs is crucial for other countries that want to improve their own inter-regional innovation resources and respond to the challenge of China’s drive to attract global talent and knowledge resources.

Spatial differentiation and driving factors of scientific and technological innovation efficiency under the background of the digital economy

Scientific and technological innovation (STI) activities are facilitated under the influence of the digital economy and depend on digital elements to support innovation activities. This study measures digital element inputs and outputs using data related to the digital economy and estimates STI efficiency in 29 provincial regions in mainland China from 2010 to 2021 employing the global super-efficiency slacks-based measure (SBM) model. Then, spatial characteristics and driving forces of STI efficiency are quantified using spatial autocorrelation and geographic detectors. The results reveal that STI efficiency exhibits a fluctuating, W-shaped pattern, and the spatial correlation effect shows a gradually declining trend from 2010 to 2021. The findings reveal that the core drivers of STI efficiency are digital financial development, e-commerce development, digital access level, and related factors. Therefore, strengthening inter-regional innovation links, promoting the construction of 5 G mobile internet and accelerating the integration of digital industries into traditional industries are recommended.

Exploration and future trends on spatial correlation of green innovation efficiency in strategic emerging industries under the digital economy: A social network analysis

With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with ω-order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011–2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE.

Access to the European cultural heritage of settlements and towns in the Danube macro-region through interoperable strategies digital transformation

Tangible cultural heritage is a strategic resource for the development of rural and urban settlements. Cooperation with stakeholders from EU countries and regions within the Danube macro-region, such as cultural heritage institutions and competent authorities, allows to agree on the preparation and adaptation of compatible digital innovation strategies in local initiative groups in the Republic of Moldova and Ukraine, as well as on impact mapping through a set of pan-European socio-economic indicators. Objectives of the study: to analyse the available European best practices and methodology for adaptation in the integration of the regions of the Republic of Moldova and Ukraine in the interregional innovation partnership on the smart specialisation "Cultural and Creative Regional Ecosystems" (CCRE-S3) [1]. The overall horizontal objective of the integration into the platform should be to add value to the common characteristics of the cultural and creative sector and to create a permanent discovery mechanism that will carry out activities to identify strategic investments and the use of innovation transfer tools. Previous works: previous concept, research and experience are described in the articles [2] and [3]. Approach: European benchmarking, comparative analysis, bibliographic research. Outcome: recommendations aimed at stimulating new ideas and opportunities related to cultural and creative experiences for local communities and residents by involving several groups of professions that use, apply and implement new technologies in the cultural and creative industries sector. The European Programmes provide resources to support their implementation. In this way, the Danube Strategy participating States [4], by supporting partnerships between the cultural heritage sector and other sectors such as higher education and vocational education and training, creative industries and sustainable cultural tourism, will be able to stimulate innovation for new services and applications in their regions.

Neighbourhood or beggar-thy-neighbour: the spatial effect of regional green credit development on green technology innovation

Green credit is an innovative financial instrument that aims to promote environmentally friendly innovations. However, financial institutions, as carriers of green credit, exhibit noticeable regional differences in the effects of implementation, leading to disparities in the distribution of green credit across regions, which will have a differentiated impact on inter-regional innovation. Unfortunately, the existing literature overlooks the impact of inter-regional differences in green credit distribution on technological innovation. Therefore, this study utilized panel data from 30 provinces and cities in China from 2012 to 2021, and adopted the spatial Durbin model to study the impact of regional differences in green credit development on green technology innovation. Additionally, this paper explores the moderating effect of green credit on the spatial impact of green innovation from the perspectives of environmental regulation and digital finance. The results of this paper indicate that the development of green credit promotes green technology innovation at the local level but has a negative impact on neighboring regions. And the negative spatial spillover effect is more significant in the central and western regions and polluting industries. Through mechanism testing, this study finds that the negative spatial spillover effect on green technology innovation is primarily driven by the migration of polluting industries across regions and the turnover of green technology R&D staff in response to the pressure of green credit. Furthermore, this paper finds that marketization and public participation in environmental regulation, as well as the presence of digital finance, significantly enhance the promotion of local green technology innovation and mitigate the negative spatial spillover effect. This study provides valuable insights for the Chinese government in implementing a regional linkage strategy for green credit within the context of the green economy transition.

Linkage‐ and structure‐based technological proximity and interregional spillovers of innovation growth

AbstractThis paper explores the roles of different types of technological proximity on the interregional spillovers of innovation growth. Using a panel dataset containing Chinese province patents and R&D inputs from 2002 to 2019, this paper estimates a knowledge production function with the spatial weight matrices constructed based on the linkage‐based and structure‐based technological proximity. We find that the two types of technological proximity are significantly different and their contributions to interregional innovation spillovers differ. The structure‐based proximity shows a lower influence on spillovers and its effect in the process of interregional innovation spillovers is affected by the regional development level. This paper originates to clarify two conceptualizations of technological proximity, compare their influences on innovation spillovers, and explore their regional differences.

The Sustainability of Regional Innovation in China: Insights from Regional Innovation Values and Their Spatial Distribution

As the continuous improvement of the quality of innovation becomes increasingly significant for balanced regional development in China, it is critical to provide insights into the sustainability of regional innovation in China from the viewpoint of value. This study estimates regional innovation values based on an improved regional innovation value model incorporating patent values and a regional innovation indicator system. Data for invention patents as well as regional innovation indicators in 282 cities from 1987 to 2019 in China are utilized for estimation. Based on the estimated parameters and Monte Carlo simulation, city-level innovation values are calculated as benchmarks, along with provincial and regional innovation values, to analyze the patterns of the spatial distribution and agglomeration of regional innovation value. The findings are as follows. (1) The regional innovation value model provides an effective way to measure regional innovation in terms of value. (2) The regional innovation values are unevenly distributed; cities with higher innovation values are clustered in Eastern China, while most other cities have much lower innovation values. (3) The innovation values in Eastern China are notably higher, and the differences in innovation values between Eastern China and other regions are large and show a trend of first widening and then narrowing during the sample period. (4) The sustainability of regional innovation is not widely achieved, since highly concentrated innovation value is found in only a few regions in the eastern coastal areas. These findings suggest that promoting China’s innovation capacity and the sustainable development of technological innovation requires continually implementing innovation-driven development strategies, cultivating high-value innovation, optimizing industrial transfer, improving the layout of the national research infrastructure, giving full play to spatial spillover effects, and promoting interregional innovation information exchange in order to achieve the balanced and sustainable development of regional innovation.

INNOVATION AGENDA OF COHESION POLICY: CONTRADICTIONS IN IMPLEMENTATION AND THE WAYS TO RESOLVE THEM

Topicality. The aim of the Cohesion Policy, founded by the European Union (EU) in the 1980s, is to help peripheral regions lagging in terms of economic development to achieve higher growth rates than developed regions to establish economic balance. As specified by the Organization for Economic Co-operation and Development, the key factor for economic growth in a globalized, competitive environment is the ability to innovate. The EU's Lisbon Agenda, announced in 2000 in response to the challenges of globalization, aims to increase social and economic cohesion by making Europe the world's most dynamic and competitive knowledge-based economy. Since then, the innovation component has become a key element of EU cohesion policy, strengthening its competitiveness in a globalized environment.The formation of a cohesive state in the social, humanitarian, economic, environmental, security, and spatial dimensions is the first strategic goal of the State Strategy for Regional Development of Ukraine for 2021-2027. According to it the formation of regional economic systems should be based on “cohesion”, “competitiveness” and building effective “multilevel governance” principles. Stimulation of innovation should become a key direction in building competitive regional economic systems.At the same time, the practice of implementing EU cohesion policy on an innovation basis has revealed some "tension between competitiveness and cohesion goals", increasing the competitiveness of more developed regions, which is conditioned by their ability to benefit more from innovation than peripheral regions.Aim and tasks. The article aims to investigate the innovation agenda of cohesion policy, the contradictions of its implementation, and to substantiate the ways to solve them in Ukrainian realities.Research results. The innovation component of EU cohesion policy has evolved from measures to stimulate the production and cooperation activities of firms, including the establishment and innovation (2000-2006 budget period), the formation of regional innovation systems (2007-2013), the elaboration of smart specialization strategies for research and innovation, which have become a prerequisite for receiving financial support from the European Structural and Investment Funds for each region (2014-2020 and 2021-2027).Ukrainian regions show significant differences in levels of innovation development compared to European regions, as well as compared with each other within Ukraine. The achievement of “cohesion” and “competitiveness” goals outlined in the State Strategy for Regional Development of Ukraine for 2021-2027, on our opinion, may become possible only by moving away from the linear models and methodology that are based on redistribution mechanisms of cohesion policy and substantiation of policy mechanisms grounded on interactive models, such as activation of interregional innovation cooperation and formation of regional innovation ecosystems.Instruments to ensure the cohesion of Ukrainian regions with EU regions are considered. Particular attention is paid to the smart specialization platform instrument with an emphasis on the interregional innovation cooperation mechanism.Conclusion. Today, the thematic area of innovation is a key priority of the Cohesion Plan. The implementation of the innovation agenda in cohesion policy is a crucial and at the same time quite difficult task. The conflict between the goals of cohesion and competitiveness can be resolved only based on abandoning linear redistributive mechanisms in favor of interactive tools, one of which is to stimulate interregional innovation cooperation. Joining the regions of Ukraine to the EU's Smart Specialization Platform can be one of the effective tools for cohesion with European regions on an innovative basis.

Toward interregional innovation systems in PeruHacia los sistemas de innovación interregional en el PerúPara sistemas inter-regionais de inovação no Peru

ObjetivoA colaboração baseada no conhecimento entre atores de regiões transfronteiriças poderia ajudar a conceber um melhor processo de regionalização no Peru. Os resultados de um apoio financeiro governamental à inovação dão provas de uma concepção política orientada para a missão de sistemas de inovação inter-regionais.Concepção/metodologia/abordagemSistemas de inovação, análise de redes sociais e políticas orientadas para missões contribuem para analisar as ligações entre territórios subnacionais fronteiriços e para construir estratégias para sistemas de inovação inter-regionais.ConclusõesCinco das 18 interações regionais possíveis são suficientemente fortes para serem consideradas sistemas de inovação inter-regionais. Assim, as políticas orientadas para a missão podem ser concebidas para reforçar os laços entre regiões.Limites da investigaçãoUma vez que a quantidade de dados observada não é suficientemente grande, este estudo e os seus resultados devem ser considerados como um exercício exploratório.OriginalidadeA concepção de políticas de inovação com base no contexto peruano e nas provas abre oportunidades para repensar os processos de regionalização no país.

Оптимальные пространственные форматы межрегионального экономического сотрудничества в рамках инновационной экономики

Domestic cooperation of companies in the field of innovative economy seems to be a promising research area in Russia, especially considering recent macroeconomic events caused by sanctions, in particular, restrictions on the import of high-tech goods. Thus, the present study examines the optimal spatial scale of interregional innovation cooperation. The article presents an analysis of approaches to determining the optimal number of k-matrices of relations between innovation active regions. It is hypothesised that the innovative activity of the business sector in one region does not influence the innovative activity of its neighbours and vice versa. Stepwise regression was applied to identify the core explanatory variable. Based on the spatial weights matrices, a spatial econometric model was constructed using the least squares method. Further, the global Moran’s I was employed to test the spatial correlation, in particular, local indicators of spatial association (LISA) using the queen criterion of contiguity were utilised to determine the dependencies of innovative activity between neighbouring regions. The analysis used panel data from all Russian regions for the period from 2010 to 2019, as well as spatial econometric modelling to identify the side effects of the optimal spatial scale. As a result, the study revealed the presence of spatial correlation in the levels of regional innovative activity, the size of markets, as well as institutional support for enterprises in individual regions. Additionally, the research identified factors positively affecting the scale of innovative activity of the regions and adjacent territories, such as regional domestic income, the number of participants in innovation processes and infrastructure facilities. It has been established that the neighbourhood of regions characterised by the presence of many participants in innovation processes (at least 100 units), as well as innovation infrastructure facilities (at least 810 units) will be seen as the optimal scale of regional cooperation.

АНАЛІЗ ТА ТЕНДЕНЦІЇ РОЗВИТКУ ІННОВАЦІЙНОЇ АКТИВНОСТІ ПРОМИСЛОВИХ ПІДПРИЄМСТВ У ІВАНО-ФРАНКІВСЬКІЙ ОБЛАСТІ

The article is devoted to topical issues of innovation development of industrial enterprises in Ivano-Frankivsk region. An analysis of their innovation activity, which is characterized by indicators of implemented innovations, quantitative indicators of innovative products and the volume of their sales. It was also analyzed that the number of operating entities in Ivano-Frankivsk region tended to decrease, as well as the number of innovative enterprises. It is noted that in the vast majority of innovative enterprises of the region made investments in internal research and development, purchase of machinery, equipment and software, other investments, as well as insignificant investments in the acquisition of other external knowledge. Investments in external research were very small, while domestic research and investment in other areas were slightly higher, but had an uneven trend. The largest share of investments was the purchase of machinery, equipment and software. The main indicators of innovation activity of industrial enterprises of Ivano-Frankivsk region are analyzed. It is determined that the main source of funding for innovation is the own funds of enterprises, and the most significant expenditures on innovation activities were made by enterprises for the production of chemicals and chemical products. The interregional innovation activity of enterprises in the regions of Ukraine is studied. Positive dynamics in the region are enterprises that implement new technological processes in production. The number of new or significantly low-waste resource-saving processes introduced into production has a steady upward trend throughout the study period. The main factors hindering the development of investment and innovation activities in the region are instability dependence on organizational changes at the governmental level; lack of competitive advantages in attracting foreign investment due to high tax rates; low purchasing power of the population and the factor of public distrust; increased competition from foreign manufacturers and insufficient competence of specialists to ensure the success of investment and innovation activities.

The Role of Proximity in Developing an Inter-Regional Innovation System

Abstract While most innovation collaboration projects consist of partners who are located at close proximity, recent literature has explored the development of innovation collaboration in the context of non-spatial proximity. Using a longitudinal mixed methods design, this article explores the inter-regional collaboration of triple helix partners from four non-contiguous European regions (Bucharest-Ilfov, Romania; Central Hungary, Hungary; Castilla-La Mancha, Spain; and South East, Ireland) which worked together to develop an inter-regional innovation system. The results from the study identified three non-spatial forms of proximity (social, cognitive and organisational) that were key determinants for developing the successful inter- regional innovation collaboration studied in this research. Based on the findings derived from this research, an inter-regional innovation system framework was developed to facilitate collaboration between stakeholders based in non-contiguous regions without them having to depend on geographical proximity. The major contributions of this research to theory and practice are the development of a novel framework for inter-regional innovation systems (iRIS) which can be applied by stakeholders in regions that want to collaborate from a distance. Furthermore, the research suggests that the substitution mechanism of geographical proximity consists of not just one non-spatial form, but it consists of the three non-spatial forms identified in this research.

STRUCTURAL MODERNIZATION OF THE REGIONAL ECONOMY OF THE NCFD SUBJECTS: PROBLEMS, PROSPECTS AND FEATURES OF DEVELOPMENT

Structural transformations of the regional economy today are the primary necessity and driving force behind the transformation of the country's economy. In connection with constant external and internal threats and the need to overcome their consequences, the regional economy needs structural modernization and the definition of its essential features, which are the key to the formation of regional policy priorities, mechanisms for its implementation, improvement of tools and methods for the implementation of modernization measures. The above determines the theoretical and methodological essence of the structural modernization of the regional economy and is one of the most pressing and debatable issues of regional development and management. The study presents the scientific approaches of a number of Russian scientists to understanding the content of the definition of “structural modernization of the regional economy”. We believe that in order to improve the system of interregional management of the socio-economic potential of the subjects of the North Caucasus Federal District, it is necessary to develop interregional economic clusters, interregional innovation centers capable of more comprehensively using the resources of regional economies. In this case, the priority tasks of interregional organizational structures include strengthening competitive growth points, real building up and effective use of socio-economic potential, both of the macroregion as a whole and of its individual regional entities. Among other things, the article substantiates the need to modernize the structure of the national economy of the North Caucasian regions. A mechanism for managing the modernization of the economy of the regions of the North Caucasus Federal District is proposed.

Strengthening the Role of Academic Institutions and Innovation Brokers in Agri-Food Innovation: Towards Hybridisation in Cross-Border Cooperation

Existing research suggests that regions can develop their long-term competitive advantage through well-functioning interregional innovation cooperation. In this article, we use the example of innovation in small and medium-sized agri-food enterprises (SMEs) to scrutinise and compare regional innovation approaches on each side of the Dutch-German border and explore how they can converge into a cross-border innovation space. Particular attention is paid to the role of academic institutions and innovation brokers in creating a common innovation space. We explore how differences between two cross-border regions can be harnessed to enhance the impact of innovation, and how this may lead to what we describe as hybridisation effects. In the empirical analysis, we apply the concept of hybridisation to a cross-border innovation space, something that, as far as we are aware, has not been done before. We empirically ground the concepts of a cross-border innovation space and hybridisation and illustrate how relative regional strengths can lead to hybridisation effects. We conclude that differences in economic structures, institutional set-ups, visions and identities inherent in cross-border spaces are not only hindrances, but also opportunities, and we highlight the importance of these complementary strengths and the potential for their strategic use by regional innovation actors. Our findings are highly relevant for the further development of the Interreg Europe programme and the implementation of the EU’s Territorial Agenda 2030.

Determining factors of cities’ centrality in the interregional innovation networks of China’s biomedical industry

This study analyzed the determinants of regions’ degree centrality as well as their variation over time in interregional innovation networks and compared the differences in factors between developed and less developed regions(core and periphery). Focusing on China’s biomedical industry, we used the prefecture-level invention co-patents data (2012–2017) to construct intercity networks and related cities’ centrality to sector-region-specific factors. We found: (1) A “convergence” process of regional embeddedness exists in innovation networks among cities. (2) The volume of national public funding for fundamental researches in the biomedical industry plays the most important role in cities’ centrality, regardless of developed or undeveloped cities. (3) For the developed cities’ centrality position, the intensity of intraregional collaboration in the biomedical industry is the secondary influencing factor, besides, other positive factors involve innovation performance, industrial market application, and cluster competitiveness, but it does not affect peripheral cities. (4) The second most influential factor in peripheral cities’ centrality is the number of biomedical firms. We concluded that despite the influence of path dependence, in the field of the analytical industry, China’s public funding for basic research has narrowed the gap in networking capability between the developed and backward cities.

ЦИФРОВАЯ ДИФФЕРЕНЦИАЦИЯ РЕГИОНОВ СЕЛЬСКОХОЗЯЙСТВЕННОЙ СПЕЦИАЛИЗАЦИИ: ПРОБЛЕМЫ И ПУТИ ИХ РЕШЕНИЯ

According to global trends, the growing level of technological equipment of agricultural production requires a reduction in the chain of introduction of all newly created or improved technologies by reducing the territorial imbalances of digital development. An analysis of the regulatory framework of the EU member states confirms that for most regions of the EU, the transition from support to large agricultural organizations to the priority development of small and medium-sized businesses is seen as a key area of economic development. The Russian agrifood complex is characterized by technological heterogeneity and high differentiation of regions of agricultural specialization in terms of the level of innovation activity. Based on data from open sources, the subjects of the Russian Federation were compared in terms of the size and specific weight of the sown (planting) area, on which elements of precision farming are used. It was revealed that at the moment, in most constituent entities of the Russian Federation, digitalization means are used disproportionately to the size of their sown areas. It has been confirmed that the regional imbalance in the use of digital technologies is due to the predominance of small businesses in the structure of crop production. Proposals for reducing the digital inequality between the regions of the Russian Federation of agricultural specialization are substantiated. The analysis of the principles of building a European thematic platform for smart specialization, its impact on strengthening interregional cooperation in the field of digitalization of agriculture. The necessity of transferring the experience of the EU member states to reduce the digital divide between the regions of the Russian Federation and increase the innovative activity of enterprises of the national agri-food complex has been substantiated. It is concluded that the creation of an interregional innovation ecosystem will clearly identify the gaps in the value chains of each participant, identify the general directions of technical modernization of agricultural pro- duction and concretize areas for joint investment in projects with high potential returns.

ПРОМЫШЛЕННАЯ ПОЛИТИКА В АРКТИКЕ:НОВЫЕ ПРИОРИТЕТЫ ФЕДЕРАЛЬНОГО УРОВНЯ

The most important drawback of the modern Federal industrial policy in the Arctic is its narrow character, focused on serving the interests of large resource corporationsand attracting private investmentыin the Arctic. The task is to radically reformatethe industrial policy to make it a real factor in the innovative modernization of the Arctic and the entire Russian economy. For the innovative development of the economy of the country and the Arctic, it is not enough to attract new investments in the Arctic, it is necessary for the state to act as an active coordinator, uniting resource corporations, the scientific and educational complex of logistics development bases, machine-building enterprises of the main settlement zone, and forming an innovative “triple helix” system. In this case, the effects of new resource projects will work for economic benefits of domestic manufacturing enterprises and the entire Russian economy rather than for foreign subcontractors.The concept of an interregional innovation system is introduced as an object of the new industrial policy in the Arctic. Its core is the mining platform of the new resource project, integrated into local and national research and production networks.The essence of the new Federal industrial policy in the Arctic is determined by the need to accelerate positive structural changes in the mining sector of the Arctic economy and in the manufacturing sector of the Russian industry.Keywords:Arctic industrial policy, interregional innovation system, subcontracting of resource company with small businesses of the major development bases of the Arctic, intersectoral relations of the Arctic resource companies and manufacturing enterprises of the developed zone of Russia.

Structural heterogeneity and proximity mechanism of China’s inter-regional innovation cooperation network

ABSTRACT Based on the cooperation patent data between 31 provinces in China from 1985 to 2017, this paper portrays the topological structure, spatial pattern and proximity mechanism of China’s inter-regional innovation cooperation network by the graph theory, spatial statistical methods and the quadratic assignment procedure model. The conclusions are as follows: (1) the topological structure of China’s inter-regional innovation cooperation forms a hierarchical network with Beijing as the core and it exhibits a typical small-world property and ‘core–periphery’ structure. (2) In terms of spatial distribution characteristics, the ‘quadruple’ with the Beijing–Tianjin region, Yangtze River Delta, Pearl River Delta and Sichuan as the peaks has become the backbone of the inter-regional innovation cooperation network in China. At the same time, the spatial differentiation of the three indicators of degree centrality, median centrality and intensity centrality is obvious. (3) In terms of proximity mechanism, geographical, institutional and cognitive proximity exert a significant effect on China’s inter-regional innovation cooperation network linkage. However, there are significant differences in the effects of various proximity elements on China’s regional innovation network.

Кластерный анализ инновационного потенциала субъектов РФ

One of the main directions of economic development of the Russian Federation is the increasing of the role of innovative production and reorganization of the economic system needed to accelerate the pace of formation of the innovative economy. Despite the tasks set by the strategy of innovative development of the Russian Federation for the period up to 2020, the pace of innovative development of the state economy, and accordingly regional economies, is extremely low, and the share of foreign technologies in production processes exceeds 60%. The reformation of the vision of strategic development of innovation economy in Russia is directly connected with defining the actual level of innovative development of regions and formation of mechanisms for the creation of regional and interregional scientific-technical research and innovation infrastructure, which in the long term will provide the current trends of innovative development. Today, the vast majority of regional economies have a high need for new technologies and the formation of the domestic base of scientific and technical production. The needs of the regions are determined not only by the obsolescence of production bases and technological resources, but also by the growing imbalance between the levels of development of regional economies and their isolation. One of the possible options for strategic management of innovative development is the creation the mechanisms of formation regional and interregional innovation and scientific and technical clusters, and, as a consequence, production clusters. However, in order to apply the advantages of cluster development, it is necessary to study the innovative potential of the subjects of the Russian Federation, which will ensure an effective combination of regional economies. This article presents the results of the cluster analysis of the subjects of the Russian Federation on one of the indicators of the innovative potential of the regional economy, as well as the key trends of innovative development of the subjects of the Russian Federation included in the identified clusters.

Варианты организации межрегионального инновационного нефтегазохимического кластера

A general characteristic of innovative territorial clusters of federal significance in the field of oil and gas processing and petrochemistry is given. All of them are located in the Volga Federal District, which ranks first in the country in terms of the number of participants in innovative activities. Based on the study of the structure of oil and gas processing in the Volga Federal District, an assumption was made that the interregional innovative oil refining cluster will be more economically efficient than the regional one due to the development of intra-cluster competition and synergistic effects of mutually beneficial interregional management, which are absent in a cluster located on the territory of one region. On the basis of simplex optimization methods, options for organizing interregional innovation clusters in the field of oil and gas processing and petrochemistry are presented