Abstract—
The article examines the model of the supply of innovations and their further diffusion in various sectors of the economy through research and comparative analysis of the evolution of innovation systems and their relationship with the sectors of the economy, based on the cluster (network) system of innovation policy in the EU countries in 1970–2018. Empirical results show that the properties of a cluster innovation network can be strictly predicted due to the network stimulation of both forward and reverse flows, while there are several other elements that have a significant and more complex impact on the formation of these nodal connections: these are primarily competencies, knowledge, and economic interdependences.
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The Erdős–Rényi model on the evolution of random graphs allows one to solve two problems: to construct a graph similar in properties to the data obtained experimentally, and to study its properties. The main advantage of the model is that it allows you to test and compare the quality of various algorithms on entire families of random graphs and compare the results obtained with those predicted theoretically. The theory of random graphs began to develop actively after the publication in the late 1950s of joint articles by P. Erdős and A. Rényi.
REFERENCES
F. C. Gómez-Merino, L. I. Trejo-Téllez, M. E. Méndez-Cadena, and A. S. Hernández-Cázares, “Education, science and technology in Mexico: Challenges for innovation,” Int. Educ. Stud. 10 (5), 115–128 (2017).
L. Sveikauskas, R&D and Productivity Growth: A Review of the Literature Bureau of Labor Statistics Working Paper 408 (2007). https://doi.org/10.2139/ssrn.1025563
M. Ugur, E. Trushin, E. Solomon, and F. Guidi, “R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis,” Res. Policy 45, 269–286 (2016). https://doi.org/10.1016/j.respol.2016.08.001
S. Johnson, “The genius of the tinkerer,” Wall Street J., Sept. 28 (2010). https://www.wsj.com/articles/SB10001424052748703499604575512751348816216.
C. Freeman, “Networks of innovators: A synthesis of research issues,” Res. Policy 20 (5), 499–514 (1991). https://econpapers.repec.org/RePEc:eee:respol:v:20:y: 1991:i:5:p:499-514.
M. E. J. Newman, Networks: An Introduction (Oxford Univ. Press. 2010). https://doi.org/10.1162/artl_r_00062
R. Cowan, and D. Foray, “Evolutionary economics and the counterfactual threat: On the nature and role of counterfactual history as an empirical tool in economics,” J. Evol. Econ. 12 (5), 539–562 (2002). https://doi.org/10.1007/s00191-002-0134-8
F. Malerba, R. Nelson, L. Orsenigo, and S. Winter, Innovation and the Evolution of Industries: History Friendly Models (Cambridge Univ. Press, Cambridge, 2016), pp. 7–27. https://doi.org/10.1017/CBO9781107280120
D. C. Mowery and R. R. Nelson, Sources of Industrial Leadership: Studies of Seven Industries (Cambridge Univ. Press, Cambridge, 1999). https://doi.org/10.1017/S0022050700430263
J. L. Solleiro, R. C. Katya Luna, A. Herrera, and M. Montiel, “A comparative analysis of innovation policy in Mexico, Spain, Chile and Korea,” in PICMET '07 - 2007 Portland International Conference on Management of Engineering & Technology (2007). https://doi.org/10.1109/PICMET.2007.4349353
S. Johansen, “Identifying restrictions of linear equations with applications to simultaneous equations and cointegration,” J. Econom. 69 (1), 111–132 (1995). https://doi.org/10.1016/0304-4076(94)01664-L
M. Capdevielle, and J. M. Natera, “Innovation, absorptive capacity and growth heterogeneity: Development paths in Latin America 1970–2010,” Struct. Change Econ. Dyn. 37, 27–42 (2016).
D. Archibugi and A. Coco, “A new indicator of technological capabilities for developed and developing countries (ArCo),” World Dev. 32 (4), 629–654 (2004).
R. R. Nelson, National Innovation Systems: A Comparative Analysis (Oxford Univ. Press, Oxford, 1993).
J. Fagerberg, “Technology and international differences in growth rates,” J. Econ. Liter. 32 (3), 1147–1175 (1994).
J. A. Schumpeter, Capitalism, Socialism and Democracy (Taylor & Francis e-Library, London, 2003).
R. M. Solow, “A contribution to the theory of economic growth,” Q. J. Econ. 70 (1), 65–94 (1956).
P. Erdős and A. Rényi, “On the evolution of random graphs,” Magyar Tud. Akad. Mat. Kutató Int. Közl. 5, 17–61 (1960).
E. Ravasz and A. L. Barabási, “Hierarchical organization in complex networks,” Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 67 (2), 026112 (2003). https://doi.org/10.1103/PhysRevE.67.026112
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Matrizaev, B.D. A Study of Ways for Determining the Structure and Evolution of Innovation Systems. Stud. Russ. Econ. Dev. 32, 549–554 (2021). https://doi.org/10.1134/S1075700721050087
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DOI: https://doi.org/10.1134/S1075700721050087