HIGH-TECH ENTREPRENEURSHIP IN RUSSIAN REGIONS: CONDITIONS FOR NEW COMPANIES

2021 ◽  
pp. 132-159
Author(s):  
A.T. Yusupova ◽  
A.V. Ryazantseva
Keyword(s):  
High Tech ◽  
Russian Regions

scholarly journals Readiness of Regions for Digitalization of the Construction Complex

2020 ◽  
Vol 7 (1) ◽  
pp. 2
Author(s):  
Ekaterina Tereshko ◽  
Marina Romanovich ◽  
Irina Rudskaya
Keyword(s):  
Fuzzy Variable ◽  
High Tech ◽  
Russian Regions ◽  
Strategic Development ◽  
Saint Petersburg ◽  
Shell Analysis ◽  
Design Documentation ◽  
Digital Development ◽  
Triangular Membership Function ◽  
Very High

The construction industry is high-tech and is one of the key areas for the strategic development of regions in terms of their digitalization. The construction complex provides regions with infrastructure of various levels from design documentation to commissioning, as well as reconstruction and major repairs of buildings. The article adopts an isolated regional approach, which is due to the need to assess specific territories by the level of readiness for digitalization of the construction complex. The purpose of the research is to determine the level of readiness of Russian regions for the digitalization of the construction complex by forming a rating of regions according to the indicator “the level of readiness of the region for digitalization of the construction complex”. To build the rating, the fuzzy sets method was applied using a triangular membership function, which allows to describe the influence of various processes on the formation of digitalization processes in the construction complex of the region. When forming the rating, a scale of fuzzy variable values is set which allows one to classify regions by levels, namely very low, low, medium, high, and very high. The generated rating is illustrated according to the specified scale. Based on the rating, the leading regions and outsider regions are identified by the formed indicator. It was determined that Moscow and Saint Petersburg are highly prepared for the digitalization of their construction complexes, and 53 regions of Russia are potentially prepared. In the future, it will be possible to create a rating of Russian regions on the level of readiness for digitalization of the construction complex with a two-year lag. Then, using the DEA shell analysis method, a quantitative assessment will be carried out that allows you to form performance boundaries and, against the background of four years, adjust the data to identify the most realistic picture. Also, the rating methodology considered by the authors allows us to scale this research to the international level, which will allow us to assess the level of digital development of construction complexes in other countries. The proposed rating algorithm is suitable for other sectors and complexes of the economy. It is enough to determine the main aggregate indicator and select groups of factors.

scholarly journals Pandemic Challenges for the Technological Startups in the Russian Regions

2021 ◽  
Vol 15 (4) ◽  
pp. 61-77
Author(s):  
Stepan Zemtsov ◽  
◽  
Alexander Chepurenko Chepurenko ◽  
Alexander Mikhailov ◽  
◽  
...  
Keyword(s):  
Metropolitan Areas ◽  
Market Access ◽  
Resource Curse ◽  
High Tech ◽  
Russian Regions ◽  
Business Climate ◽  
Start Up ◽  
Birth Factors ◽  
Knowledge Intensive ◽  
High Level

Technological startups help to adapt to the global risks and allow one to track future trends. This paper identifies the main trends and birth factors of new high-tech companies in the Russian regions during 2013-2020. In 2020, fewer than 10,000 startups were created, this number has been steadily declining (by 40% since 2015), especially during the pandemic (-21%). Most of the startups are concentrated in Moscow, the Moscow region, St Petersburg, and the largest metropolitan areas. The share of the Leningrad, Belgorod, Kaliningrad, Lipetsk, Ulyanovsk, and Kaluga regions is growing due to the proactive policies of local authorities. Most startups are associated with knowledge-intensive services for business (B2B) and digital technologies. In 2020, their number increased in pharmaceuticals (about 100%) and in the production of medical devices (by about 30%).Based on the results of econometric analysis, start-up activity in Russia, analogous to countries with an established market economy, depends upon human capital concentration, market access, and a favorable business climate. Universities, through attracting students, especially those in STEM specialties, stimulate startup creation; although the share of university startups does not exceed one third of a percent. Budgetary and university expenditures on R&D are ineffective in terms of creating new companies. The influence of development institutions on start-up activity was not found, while clusters and technology parks have a weak effect. The growth of startups is lower in regions with a predominance of large organizations, as well as in resource centers. The latter may be one of the manifestations of the “resource curse”. Startup activity is stable over time and depends on the situation in neighboring regions, which limits the chances to change the situation by means of entrepreneurship support policy. During the pandemic, start-up activity decreased minimally in regions with large metropolitan areas and a high level of education. Recommendations include tools for establishing a more balanced cross-regional situation by implementing the model of an entrepreneurial university, an expansion of start-ups’ access to capital and markets, and the regionalization of entrepreneurship policies.

scholarly journals Potential High-Tech Сlusters in Russian Regions: From Current Policy to New Growth Areas

2016 ◽  
Vol 10 (3) ◽  
pp. 34-52 ◽  
Author(s):  
Stepan Zemtsov ◽  
◽  
Vera Barinova ◽  
Alexey Pankratov ◽  
Evgeny Kutsenko ◽  
...  
Keyword(s):  
High Tech ◽  
Russian Regions ◽  
Current Policy

scholarly journals Efficiency Analysis of Regional Innovation Development Based on DEA Malmquist Index

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 294 ◽  
Author(s):  
Anna Firsova ◽  
Galina Chernyshova
Keyword(s):  
Innovation Policy ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Innovation Activity ◽  
High Tech ◽  
Innovative Development ◽  
Russian Regions ◽  
Regional Innovation ◽  
Innovation Development ◽  
Average Growth

The aim of the work was to evaluate the dynamics of regional innovation development and compare the Russian regions according to their innovation efficiency, used resources, and achieved results. To estimate direct and indirect innovation effects, this study used the data on Russian regions according to variables of the innovative product volume, the share of high-tech products in the gross regional product (GRP) structure, the number of used patents, and investment in innovation activity for 2006–2017. To obtain a representative sample, a cluster analysis was applied as a preliminary step, which made it possible to select a group of regions that were most advanced in terms of their innovative development. Output-oriented data envelopment analysis models were applied for Malmquist Productivity Index calculation. The obtained results indicate the average growth of total factor productivity of regional innovation development over time. The main source of innovative development is largely derived from the economy of scale, while the effectiveness of regional innovation systems is basically increasing through broader resource bases, rather than through its effective utilization. The research findings can be applied to diagnose regional innovation effectiveness, justify public investment in research and development (R & D), and identify the priorities of regional innovation policy for specific regions.

scholarly journals The structural factor of regional economic stability in Russia during the coronacrisis period

R-Economy ◽  
2021 ◽  
Vol 7 (3) ◽  
pp. 158-169
Author(s):  
Olga A. Romanova ◽  
◽  
Alena O. Ponomareva ◽  
Keyword(s):  
Global Economy ◽  
Regional Economy ◽  
Research Literature ◽  
High Tech ◽  
Russian Regions ◽  
Economic Stability ◽  
Regional Economic ◽  
The Government ◽  
The Times ◽  
Role Of The Government

Relevance. The coronavirus pandemic has lead to one of the most serious crises in the global economy. The significant disparities between Russian regions influenced the levels of morbidity and their strategies of containing the crisis. Research objective. The aim of this paper is to identify the factors of regional development which, during the pandemic and in the post-pandemic period, affected and will affect the economic stability of Russian regions. Materials and Methods. The research is based on the Rosstat data, industry reviews, materials from analytical and consulting firms, Russian and international research literature. The research methodology is based on the structuralist approach and the provisions of the new structural economics put forward by J. Lin. The methods of comparative, statistical, and structural analysis were also used. Results. The most significant factors in regional economic development are the structure of the economy and the quality of public administration at the national and regional levels. The high-tech sector in the structure of a regional economy plays a pivotal role in ensuring its stability in the times of crisis. The study shows the need for a transition to independent national value chains. It is also necessary to develop a long-term national strategy aimed at stimulating the structural transformation of regional economies. Conclusions. The study has demonstrated the importance of the two key factors in shaping the regions’ responses to the pandemic and the speed of their recovery – the structure of regional economy and the role of the government. These factors should be taken into account by the Strategy of the State Regional Industrial Policy.

scholarly journals Scaling the dual model of secondary vocational education as a factor of economic development of Russian regions

2020 ◽  
Vol 18 (5) ◽  
pp. 810-828
Author(s):  
V.A. Teslenko ◽  
R.M. Mel'nikov
Keyword(s):  
Economic Development ◽  
Vocational Education ◽  
High Tech ◽  
Dual Model ◽  
Russian Regions ◽  
Successful Development ◽  
Economic Relations ◽  
Secondary Vocational Education ◽  
Level Of Economic Development ◽  
High Level

Subject. This article deals with the issues of improving economic relations between different structures in the implementation of the dual model of secondary vocational education. Objectives. The article aims to develop recommendations for scaling the dual model of secondary vocational education in Russian regions. Methods. For the study, we used a regression analysis. Results. The article defines that the development of the dual model of secondary vocational education creates certain prerequisites for successful development of high-tech companies in the region. It justifies the need for federal financial support for the regional chambers of commerce and industry. Conclusions. At present, the spread of the dual model of secondary vocational education in Russia is local and limited to regions with a fairly high level of economic development. Further expansion of the model requires the implementation of a new target programme.

scholarly journals Ecosystem Approach to Innovation Management in Russian Regions

2021 ◽  
Vol 17 (4) ◽  
pp. 1346-1360
Author(s):  
I.M. Golova ◽  
Keyword(s):  
Innovation Management ◽  
Ecosystem Approach ◽  
The State ◽  
Sustainable Growth ◽  
High Tech ◽  
Moscow Oblast ◽  
Innovative Development ◽  
Russian Regions ◽  
Regional Innovation ◽  
Innovation Ecosystem

Russia’s transition to innovative development is required to ensure the sustainable competitive growth. At the same time, the share of the high-tech sector in innovation costs today is about 15 %. The study suggests ways to improve the system of innovation management in Russian regions. Analysis of modern theories on the organisation of regional innovation processes confirmed a hypothesis that innovation management should consider the regional innovation ecosystem as one of the key sustainable growth institutions. A proposed ecosystem approach states that regional innovation ecosystems in the context of globalisation depend on the coordinated goals of socio-economic and innovative development, differentiated approaches to their construction, sustainable flows of knowledge and technology, diversity and competition of participants. The research determined such priority directions of the state policy as the recognition of the lack of alternative to innovative development; creation of conditions for high-tech industries outside the established business structures; increase in budget research and development (R&D) expenditures; strengthening of self-organisation of science; stimulation of horizontal interactions between science and business. The presented differentiated approach to innovative strategies of Russian regions considers their production and technological specialisation, as well as the state of science and higher education. A described methodology for selecting the most promising regions for innovative transformations is based on a comparison of the values of the author’s indices for the development of scientific and educational space and high-tech industries. The calculations show that, in addition to Moscow, Moscow oblast and Saint Petersburg that are already at the centre of the country’s innovation system, regions occupying the first 10–15 positions in the constructed rating (Nizhny Novgorod, Sverdlovsk, Novosibirsk oblasts, Republic of Tatarstan, etc.) can also become local innovation centres. The obtained results can be used in the state innovation management of the constituent entities of the Russian Federation.

scholarly journals The Impact of Advanced Industry 4.0 Technologies on Unemployment in Russian Regions

2021 ◽  
Vol 17 (1) ◽  
pp. 182-196
Author(s):  
Olga A. Koropets ◽  
Evgeniya Kh. Tukhtarova
Keyword(s):  
Labour Market ◽  
Digital Economy ◽  
University Education ◽  
Regional Differentiation ◽  
High Tech ◽  
Russian Regions ◽  
Economic Relations ◽  
Econometric Methods ◽  
Advanced Technologies ◽  
The Impact

The introduction of advanced technologies requires restructuring the labour market and redistributing the workforce. Therefore, the study of the demand for workers in the digital economy is necessary for preventing unemployment. We examine the impact of advanced technologies on unemployment in Russian regions. The transition to a new technological wave and the development of advanced technologies will differently affect the unemployment among various categories of population depending on their educational level. Using the combination of spatial analysis, statistical and econometric methods, we identified clusters of high-tech, medium-tech, and low-tech regions of the Russian Federation, described the impact and confirmed the proposed hypothesis. We have discovered that most Russian regions have a low potential to transition to a new technological wave. Simultaneously, in high-tech regions with sufficient potential to develop a new technological wave, digital economy does not require a large number of employees with university education. Moreover, such regions are experiencing an acute shortage of people with vocational education. Currently, selected Russian regions have resources, potential and reserves to develop the sixth technological wave, while others provide human resources. This situation leads not only to deepening regional differentiation but also to severance of economic relations between regions, hindering their interaction in the new conditions. The obtained results can be used to support proposals and measures for regulating labour market processes to develop scientific, technological and economic potential of the country.

scholarly journals The substance and opportunities to implement innovative import substitution in Russian regions

2020 ◽  
Vol 19 (8) ◽  
pp. 1388-1408
Author(s):  
I.M. Golova ◽  
A.F. Sukhovei
Keyword(s):  
Russian Federation ◽  
Import Substitution ◽  
Global Market ◽  
High Tech ◽  
Russian Regions ◽  
Mathematical Methods ◽  
Global Trends ◽  
Technological Gap ◽  
Production Development ◽  
The Russian Federation

Subject. The article addresses the innovative import substitution as a timely socio-economic policy direction of the Russian Federation. Objectives. The purpose is to reveal the essence and justify the specifics of approach to innovative import substitution in Russian regions in the face of Russia's growing technological gap and the global economic crisis triggered by the coronavirus pandemic. Methods. We employ methods of comparative analysis, statistical, economic and mathematical methods, including our own method of assessing the Russian regions based on the level of high-tech production development. Results. The study unveils the bottlenecks of the routine approach to import substitution. It underpins the need for innovative import substitution, which is built on serious technological modernization of the economy with a special emphasis on the areas crucial for security and development of the country. Based on the comparative assessment of Russian regions by the level of high-tech production development, we identified fifteen the most promising regions to implement innovative import substitution. The paper offers a set of measures aimed at successful completion of innovative import substitution, paying particular attention to the key role of science in implementing the import substitution strategy. Conclusions. It is crucial to strengthen the innovation dimension in the import substitution strategy of Russian regions. This approach will help overcome the technological backwardness of the Russian Federation by creating modern production facilities, which ensure competitive products on the global market, considering the global trends in the development of science and technology.

scholarly journals Preparation of Innovative Development Rating of Russian Regions by the Level of University Involvement

2021 ◽  
Vol 18 (4) ◽  
pp. 35-47
Author(s):  
Irina Yu. Vygodchikova
Keyword(s):  
Performance Indicators ◽  
Processing System ◽  
Theoretical Research ◽  
Innovation Activity ◽  
High Tech ◽  
Innovative Development ◽  
Russian Regions ◽  
Regional Universities ◽  
University Performance ◽  
Russian Universities

The paper presents method of clustering and grouping the university performance indicators to prepare an integral rating of Russian regions by the level of university involvement in innovative development of Russian regions. The following problems that require the management influence of state structures are considered: the role of the research base of regional universities in strengthening the innovative potential of regions, the degree of involvement of universities in the innovative regional space.The aim of the study is to develop a rating system for Russian regions according to the degree of university involvement in innovative development using mathematical tools and an intelligent data processing system. The main hypothesis of the article is the existence of a link between regional innovative development and the effectiveness of university contributions. The mathematical approach involves the consideration and multidimensional ranking of the main groups of university performance indicators in order to obtain cluster classifications within each of the problems posed. The solution to the problems is to build a barometer of innovation activity in the form of a multi-purpose problem-oriented rating.Materials and methods. An approach is applied that includes the assessment and multidimensional ranking of the contribution of universities using groups of integral indices created on the basis of aggregation of several important indicators of the university’s activity. Computational experiments were conducted according to the data of the Ministry of Education and Science for the regions of Russia and regional universities. 16 indicators of Russian regions for 2016 are considered.Results and discussion. The ranking and comparison of universities according to the degree of involvement in the innovative development of the region was performed using an indicator model and aggregation depending on the target problem. Quantitative indicators of the quality of university’s activities by regions are obtained, which allow us to obtain an integral rating of Russian regions by the level of university involvement. Unlike other approaches, the author’s method includes three components, which are independent integral indexes and indicate the level of involvement of universities in regional innovative development. Statistical data on the leading indicators of Russian universities for 2016 were processed. The methodology Science-model with three factors - the model with regrouping, named by the author A-B-C, showed the high potential of Russian universities to balance their regional demand as management research centers.Conclusion. The results of the study are compared with the ratings of the well-known agencies. The author hopes that soon Russia will have a reliable scientometric system at the level of rating universities on their involvement in the innovative development of Russia, such a rating will be an indisputable argument in favor of financing regional universities. The author laid down a high requirement: compliance with the three models, only in this case, regional universities can receive funding from the municipality, after redistribution from the center. At the same time, it is necessary to carefully choose universities in which projects will receive development and perspective. Regional authorities must meet the requirements to receive the necessary investments in promising projects. The scientific potential and demand for theoretical research for their full application at all enterprises, the combination of theoretical science and practical implementation will reduce the cost of stabilizing outdated technologies in all areas of knowledge and use the experience of older generations and the strength of young people for high-tech production growth in Russia. Therefore, the results of the study will be useful to federal authorities and financial and credit organizations that provide financing.

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