Enhancing the knowledge spillover through the formation of the oligocentric national innovation system

https://doi.org/10.22146/ijg.53445

Yuri V. Preobrazhenskiy(1*), Anna A. Firsova(2)

(1) Saratov State University, Russian Federation
(2) Saratov State University, Russian Federation
(*) Corresponding Author

Abstract


The processes of spatial polarization of economic activity and potential of regional innovation systems are an important area of study of the innovation transfer in the global world. The present study continues the scientific discussion on the ratio of concentration and uniform innovation development. The objective of the study is to analyze indicators of spatial concentration of innovation activity and the knowledge spillover between regions in the national innovation system. The main methods are the application of the Herfindal-Hirschman index, as well as cartographic analysis. The analysis of the concentration degree of the following indicators of innovation activity was carried out: patents, developed and used advanced technologies, R&D costs, output of innovative products in these regions of Russia using the Herfindal-Hirschman index. A graphical method was used to identify the main regions of the centers and peripheries, and a map of fragmentation of the country's innovative cores was constructed. The results of the study confirmed the hypothesis of a greater spatial concentration of knowledge in comparison with the release of innovative products. Analysis of potential knowledge spillover between regions showed that the indicators associated with the generation of knowledge, focused on the Russian regions is significantly stronger than the indicators for innovative output: spatial concentration of developed advanced technologies are higher than that used advanced technologies, and the concentration of expenditure on technological innovations ahead of the release of innovative products. This indicates an unbalanced nature of the effects of the innovative spillover, when the use of technologies is more widespread than their development and implementation. Recommendations are also presented on a more efficient organization of the innovation space and on the transition from a monocentric model of organizing a socio-economic space to an oligocentric model to reduce excessive polarization and increase the efficiency of knowledge spillover.


Keywords


knowledge spillover; national innovation system; oligocentric model

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References

Aldieri, L. (2011). Technological and geographical proximity effects on knowledge spillovers: evidence from the US patent citations. Economics of Innovation and New Technology, 20(6):597–607. doi:10.1080/10438599.2011.554632

Asheim, B. T. & Isaksen, A. (2002) Regional Innovation Systems: The integration of local ‘sticky’ and global‘ubiquitous’ knowledge. The Journal of Technology Transfer, 27(1):77–86

Asheim, B. T., Boschma, R., & Cooke, P. (2011). Constructing Regional Advantage: Platform Policies Based on Related Variety and Differentiated Knowledge Bases. Regional Studies, 45(7):893–904. doi:10.1080/00343404.2010.543126

Autant-Bernard, C. (2001) Science and knowledge flows: evidence from the French case. Research Policy, 30(7):1069–1078

Boschma, R. (2005) Proximity and innovation: a critical assessment. Reg Stud, 39:61–74

Brenner, T. & Broekel, T. (2011) Regional factors and innovativeness: an empirical analysis of four German industries. The Annals of Regional Science, 47 (1), 169-194.

Chelnokova, O. Yu. & Gritsak, L. E. (2013) Development of the integration of education, science and production in the form of technology transfer in the modern phase of the innovation cycle of the Russian Federation. Izv. Saratov Univ. (N.S.), Ser. Economics. Management. Law, 13(1): 8-14.

Costantini, V. & Liberati, P. (2014) Technology transfer, institutions and development. Technological Forecasting and Social Change. 88: 26–48. doi:10.1016/j.techfore.2014.06.014

Country features of the national innovation system formation in the face of increasing uncertainty of the global economy ( based on examples of countries: China, Republic of Korea, South Africa, Russia): monograph (2019) Edited by N.P. Gusakov. - Moscow: Econ-Inform Publishing House.

Davids, M. & Frenken, K. (2018). Proximity, knowledge base and the innovation process: Towards an integrated framework. Regional Studies,52(1), 23–34. doi:10.1080/00343404.2017.1287349

Dudzevičiūtė, G. & Tvaronavičienė, M. (2011) Measurement framework of innovation activity: theoretical approaches’ analysis, Journal of Security and Sustainability Issues 1(1): 63-75. http://dx.doi.org/10.9770/jssi.2011.1.1(6)

Firsova, A. A., Ogurtsova, E. V. & Tugusheva, R. R. (2019) Innovation spillover effects of information and communications technology in higher education. Perspektivy nauki i obrazovania – Perspectives of Science and Education, no. 42 (6), pp. 409-421. DOI: 10.32744/pse.2019.6.34

Firsova, A. A. & Makarova, E. L. (2017) Factors Affecting the Innovative Development of the Region. Izv. Saratov Univ. (N.S.), Ser. Economics. Management. Law,17( 2):141–14. DOI: 10.18500/1994-2540-2017-17-2-141-147.

Kijek, A. & Kijek, T. (2019) Knowledge Spillovers: An Evidence from The European Regions. J. Open Innov. Technol. Mark. Complex. 5, 68.

Kopczewska, K. (2018). Cluster-based measures of regional concentration. Critical overview. Spatial Statistics, 27: 31–57. doi:10.1016/j.spasta.2018.07.008

Krugman, P. (1996) Urban Concentration: The Role of Increasing Returns and Transport Costs. International Regional Science Review, 19:5–30.

Makarova, E.L. & Firsova, A.A. (2017) Computer Cognitive Modeling of the Innovative System for the Exploration of the Regional Development Strategy. Computer Modelling in Decision Making / Ed. by A. Althonayan, T. A. Belkina, V. S. Mkhitaryan, D. Pavluk, S. P. Sidorov. – Aachen.

Maskell, P. (2001) Towards a knowledge-based theory of the geographical cluster, Industrial and Corporate Change, 10(4): 921 – 943.

McCann, P. & Ortega-Argilés, R. (2013) Modern regional innovation policy. Cambridge Journal of Regions. Economy and Society, 6(2):187-216.

Monteiro, P., Noronha Vaz, T. & Neto, P. (2011) The Importance of Clusters for Sustainable Innovation Processes: The Context of Small and Medium Sized Regions. CEFAGE-UE Working Papers 2011_24, University of Evora, CEFAGE-UE (Portugal)

Morettini, L., Perani, D., & Cirilli, D. (2013) The concentration of knowledge activities in Italy: an analysis at the local level, Forsythe, 7(2): 28-39.

Neffke, F., Henning, M., & Boschma, R. (2011). How Do Regions Diversify over Time? Industry Relatedness and the Development of New Growth Paths in Regions. Economic Geography, 87(3), 237–265. doi:10.1111/j.1944-8287.2011.01121.x

Newman, C., Rand, J., Talbot, T. & Tarp, F. (2015) Technology transfers, foreign investment and productivity spillovers, European Economic Review 76: 168–187. doi:10.1016/j.euroecorev.2015.02.005

Nordensvard, J., Zhou, Y., & Zhang, X. (2018). Innovation core, innovation semi-periphery and technology transfer: The case of wind energy patents. Energy Policy, 120: 213–227. doi:10.1016/j.enpol.2018.04.048

Pottier, P. (1963) Axes de communication et développement économique. Revue Économique, 14:58-132. DOI: 10.2307/3499503

Preobrazhenskiy Yu. V. (2016) Approaches to the identification of the Center and Periphery. Izv. Saratov Univ. (N. S.), Ser. Series: Earth Sciences, 16(4):216-221.

Preobrazhenskiy, Yu. V. & Firsova, A. A. (2019) Inequality of Spatial Development of Higher Education in Russia. Advances in Social Science, Education and Humanities Research. 2nd International Conference on Contemporary Education, Social Sciences and Ecological Studies (CESSES 2019), volume 356: 76-79. DOI: 10.2991/cesses-19.2019.18.

Rastvortseva, S. N., & Ternovsky, D. S. (2016) Factors of concentration of economic activity in the regions of Russia, Economic and social changes: facts, trends, forecast, 2 (44): 153-170. DOI: 10.15838/esc.2016.2.44.9

Rogers, E.M. (2003) Diffusion of innovations, 5th edn. Free Press, New York.

Torre, A., & Darly, S. (2013). Land use and soils disposal: From competition to territorial governance (examples from land use conflicts in the greater Paris region). Renewable Agriculture and Food Systems, 29(3): 206–217. doi:10.1017/s1742170513000379

Venables, A. J. (1994) Economic Integration and Industrial Agglomeration. Economic and Social Review, 26:1–17.

Wang, J. & Zhang, L. (2018) Proximal advantage in knowledge diffusion: The time dimension. Journal of Informetrics, 12:858-867. DOI: 10.1016/j.joi.2018.07.006.



DOI: https://doi.org/10.22146/ijg.53445

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