The spread of the regional intellectual capital: the case of the Russian Federation

Keywords: regional intellectual capital, percolation, propagation

Abstract

Research background: The positive relationship between the availability of intellectual capital and the ability of the state, region or firm to develop economically stimulates an increase in the intellectual capital. In order to manage intellectual capital, it is necessary to have a clear idea of its availability, capacity, features, growth reserves, as well as concentration in certain territories and ability to spread. Many studies are devoted to the measurement of intellectual capital, its diffusion and impact on the economic efficiency of the organization, region, and nation. However, in the case of the Russian Federation there is a gap in the study of the spread of intellectual capital over the country.

Purpose of the article: The purpose of the article is to evaluate intellectual capital in the federal districts of the Russian Federation and to model the spread of intellectual capital.

Methods: Data on 8 Russian federal districts for the 2017 year from Unified Inter-departmental Information and Statistical System (EMISS) of the Russian Federation were taken as a basis for the research. Based on three-component model (human capital, structural capital, and relational capital), we formed a set of indicators for assessing regional intellectual capital, relevant to the Russian Federation. This allowed us to evaluate the integrated indicators of intellectual capital in federal districts and to determine the probability of intellectual capital spreading from each federal district to neighboring federal districts. We used percolation theory methods to model the spread of intellectual capital.

Findings & Value added: The study contributes to the Russian regional knowledge on intellectual capital. Intellectual capital in the Russian Federation is disproportionately distributed, concentrating closer to the capital, and has a lower level in remote territories. It spreads unevenly, flowing from the Central Federal District to neighboring federal districts, however, other federal districts develop almost in isolation.

Downloads

Download data is not yet available.

References

Acemoglu, D., Makhdoumi, A., Malekian, A., & Ozdaglar, A. (2017). Privacy-constrained network formation. Games and Economic Behavior, 105(C). doi: 10.1016/j.geb.2017.08.001.

Amini, H., Cont, R., & Minca, A. (2016). Resilience to contagion in financial networks. Mathematical Finance, 26(2). doi: 10.1111/mafi.12051.

Andrei, D., & Cujean, J. (2017). Information percolation, momentum and reversal. Journal of Financial Economics, 123(3). doi: 10.1016/j.jfineco.2016.05.012.

Asparouhova, E., & Bossaerts, P. (2017). Experiments on percolation of information in dark markets. Economic Journal, 127(605). doi: 10.1111 /ecoj.12464.

Autant-Bernard, C., Fadairo, M., & Massard, N. (2013). Knowledge diffusion and innovation policies within the European regions: challenges based on recent empirical evidence. Research Policy, 42(1). doi: 10.1016/j.respol.2012.07.009.

Autant‐Bernard, C., Mairesse, J., & Massard, N. (2007). Spatial knowledge diffusion through collaborative networks. Papers in Regional Science, 86(3). doi: 10.1111/j.1435-5957.2007.00134.x.

Bottazzi, L., & Peri, G. (2003). Innovation and spillovers in regions: evidence from European patent data. European economic review, 47(4). doi: 10.1016/S0014-2921(02)00307-0.

Bretschger, L. (1999). Knowledge diffusion and the development of regions. Annals of Regional Science, 33(3). doi: 10.1007/s001680050104.

Broadbent, S. R., & Hammerslay, J. M. (1957), Percolation process. I. Crystals and mazes. Mathematical Proceedings of the Cambridge Philosophical Society, 53(3).

Buenechea-Elberdin, M. (2017). Structured literature review about intellectual capital and innovation. Journal of Intellectual Capital, 18(2). doi: 10.1108/jic-07-2016-0069.

Caragliu, A., & Nijkamp, P. (2016). Space and knowledge spillovers in European regions: the impact of different forms of proximity on spatial knowledge diffusion. Journal of Economic Geography, 16(3). doi: 10.1093/jeg/lbv042.

Cassi, L., Corrocher, N., Malerba, F., & Vonortas, N. (2008). The impact of EU-funded research networks on knowledge diffusion at the regional level. Research Evaluation, 17(4). doi: 10.3152/095820208x364535.

Demigha, S. (2015). Knowledge management and intellectual capital in an enterprise information system. In M. Massaro & A. Garlatti (Eds.). Proceedings of the 16th European conference on knowledge management. Reading: Academic Conferences Limited.

Dettori, B., Marrocu, E., & Paci, R. (2012). Total factor productivity, intangible assets and spatial dependence in the European regions. Regional Studies, 46(10). doi: 10.1080/00343404.2010.529288.

Duffie, D., Malamud, S., & Manso, G. (2014). Information percolation in segmented markets. Journal of Economic Theory, 153(C). doi: 10.1016/j.jet. 2014.05.006.

Duffie, D., & Manso, G. (2007). Information percolation in large markets. American Economic Review, 97(2). doi: 10.1257/aer.97.2.203.

EMISS (2018). State Statistics. Retrieved form: http://fedstat.ru/ (01.10.2018).

Golichenko, O. G., & Malkova, A. A. (2017). The analysis of processes of new knowledge production in key world regions and Russia. Journal of the Knowledge Economy, 8(4). doi: 10.1007/s13132-016-0424-2.

Golichenko, O., & Samovoleva, S. (2015). The balance of externalities and internal effects in national innovation systems. In 10th European conference on innovation and entrepreneurship (ECIE). Reading: Academic Conferences Limited.

Gunther, J., & Meissner, D. (2017). Clusters as innovative melting pots? – the meaning of cluster management for knowledge diffusion in clusters. Journal of the Knowledge Economy, 8(2). doi: 10.1007/s13132-017-0467-z.

Hohnisch, M., Pittnauer, S., & Stauffer, D. (2008). A percolation-based model explaining delayed takeoff in new-product diffusion. Industrial and Corporate Change, 17(5). doi: 10.1093/icc/dtn031.

Kaneva, M., & Untura, G. (2017). Innovation indicators and regional growth in Russia. Economic change and restructuring, 50(2). doi: 10.1007/s10644-016-9184-z.

Kireeva, V., & Galiakhmetov, L. (2015). The assessment of the intellectual capital as a factor of investment attractiveness of the region. Procedia Economics and Finance, 27. doi: 10.1016/s2212-5671(15)00997-1.

Kotenkova, S., & Korablev, M. (2014). Evaluation of intellectual capital in regions of Volga Federal District of Russian Federation. Procedia Economics and Finance, 14. doi: 10.1016/s2212-5671(14)00722-9.

Lopes, I. T. (2014). The drivers of intellectual capital in an agriculture, cattle and forest farmstead. In D. Caganova & M. Cambal (Eds.). Proceedings of the 6th European conference on intellectual capital. Reading: Academic Conferences Limited.

Matricano, D. (2016). The impact of intellectual capital on start-up expectations. Journal of Intellectual Capital, 17(4). doi: 10.1108/jic-04-2016-0040.

Medina, A. J. S., Gonzalez, A. M., & Falcon, J. M. G. (2007). Intellectual capital and sustainable development on islands: an application to the case of Gran Canaria. Regional Studies, 41(4). doi: 10.1080/00343400600928327.

Miguelez, E., & Moreno, R. (2013). Do labour mobility and technological collaborations foster geographical knowledge diffusion? The case of European regions. Growth and Change, 44(2). doi: 10.1111/grow.12008.

Nitkiewicz, T., Pachura, P., & Reid, N. (2014). An appraisal of regional intellectual capital performance using Data Envelopment Analysis. Applied Geography, 53. doi: 10.1016/j.apgeog.2014.06.011.

Pedro, E., Leitao, J., & Alves, H. (2018). Intellectual capital and performance: taxonomy of components and multi-dimensional analysis axes. Journal of Intellectual Capital, 19(2). doi: 10.1108/jic-11-2016-0118.

Population of the Russian Federation by sex and age (2018). Federal State Statistics Service. Retrieved form: http://www.gks.ru/wps/wcm/connect /rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1140095700094 (01.10.2018).

Silverberg, G., & Verspagen, B. (2005). A percolation model of innovation in complex technology spaces. Journal of Economic Dynamics & Control, 29(1-2). doi: 10.1016/j.jedc.2003.05.005.

Singh, J. (2005). Collaborative networks as determinants of knowledge diffusion patterns. Management science, 51(5). doi: 10.1287/mnsc.1040.0349.

Stam, C., & Andriessen, D. (2009). Intellectual capital of the European Union 2008. In Proceedings of the European conference on intellectual capital. Reading: Academic Conferences Limited.

Stewart, T. A. (1997). Brain power – who owns it ... how they profit from it. Fortune, 135(5).

Trequattrini, R., Lombardi, R., Lardo, A., & Cuozzo, B. (2018). The impact of entrepreneurial universities on regional growth: a local intellectual capital perspective. Journal of the Knowledge Economy, 9(1). doi: 10.1007/s13132-015-0334-8.

Tsertseil, J. & Ordov, K. (2017). The role of Intellectual capital in the development of the regional cluster. International Journal of Organizational Leadership, 6(3), 416-424. doi: 10.19236/ijol.2017.03.09.

Wee, J. C. N., & Chua, A. Y. K. (2016). The communication of intellectual capital: the “whys” and “whats”. Journal of Intellectual Capital, 17(3). doi: 10.1108/jic-01-2016-0007.

Ziff R.M. (1986), Test of scaling exponents for percolation-cluster perimeters. Physical review letters, 56(6).

Published
2019-03-31
How to Cite
Markhaichuk, M., & Zhuckovskaya, I. (2019). The spread of the regional intellectual capital: the case of the Russian Federation. Oeconomia Copernicana, 10(1), 89-111. https://doi.org/10.24136/oc.2019.005
Section
Articles