Abstract—
The article summarizes the results of research into analysis and modeling of interregional value chains (IRVCs). The necessity of developing state policy aimed at IRVC development is substantiated. The existing analytical and modeling tools for improving the quality of management of these processes are systematized and tested. The primary directions and instruments of IRVC regulation are presented.
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Notes
And also in “zones of confidence,” primarily the EAEU.
Note that in the Spatial Development Strategy, significant importance for the task of eliminating imbalances in the economy and territorial development is given to the macroregional level, to strengthening interregional ties, i.e., essentially, to IRVC development.
According to Web of Science data, 13.5 thousand publications that mention “value chain” have been published globally since 1987, in recent years about 1300–1500 new publications on the topic appear per year; in Russia, according to RSCI data, 329 publications have been published since 2008.
Source: EDB Integration barometer—2017, St. Petersburg: Eurasian Development Bank Center for Integration Studies, 2017.
Applied to industries of different regions involved in adding value, this decomposition turns into IRVCs.
By volume of final consumption of products.
By gross added value created by a given industry.
For reference: the global average value of D in 2011 was 2.15. The 2011 value of D in Russia, according to our estimate, was 1.90.
In 2011–2014 the average annual GDP growth rate decreased from 4.3% to 0.7%. Gross fixed capital formation slowed down from 109.1% in 2011 to 97.9% in 2014.
An early version of a regional model that recognizes only one spatial effect – the unilateral effect of changes in exogenous demand on the output of “national” and “regional” products identified in the region.
REFERENCES
R. Kaplinsky, “Globalisation and unequalisation: What can be learned from value chain analysis?,” J. Dev. Stud. 37 (2), 117–146 (2000). https://doi.org/10.1080/713600071
Yu. A. Kurganov, “Development of industrial cooperation in the Russian automotive industry under the sanctions,” Ross. Vneshneekon. Vestn., No. 1, 119–127 (2016).
A. V. Gavrilyuk, “Science-and-technology and industrial cooperation: development trends,” Gos. Upr. Elektron. Vestn., No. 56, 114–133 (2016).
G. Hanson, R. J. Mataloni, and M. J. Slaughter, “Vertical production networks in multinational firms,” Rev. Econ. Stat. 87 (4), 664–678 (2005).
A. R. Sayapova, “Quantitative parameters of global value chains in macrostructural forecasting,” Stud. Russ. Econ. Dev. 29, 617–624 (2018).
R. E. Miller and U. Temurshoev, “Output upstreamness and input downstreamness of industries/countries in world production,” Int. Reg. Sci. Rev. 40 (5), 443–475 (2017). https://doi.org/10.1177/0160017615608095
Yu. S. Ershov, “Regionalization of national economic input-output tables,” EKO, No. 6, 119–138 (2011).
E. V. Lukin, “Sectoral and territorial specifics of value chains in Russia: an intersectoral approach,” Ekon. Sots. Peremeny: Fakty, Tendentsii, Prognoz 12 (6), 129–149 (2019). .https://doi.org/10.15838/esc.2019.6.66.7]
T. Fally, On the Fragmentation of Production in the US (University of Colorado-Boulder, Boulder, CO, 2011).
E. Kutsenko, E. Islankina, and A. Kindras, “Smart by oneself? An analysis of Russian regional innovation strategies within the RIS3 framework,” Foresight STI Governance 12 (1), 25–45 (2018). https://doi.org/10.17323/2500-2597.2018.1.25.45
A. G. Granberg, et al., Optimization Interregional Intersectoral Models (Novosibirsk, 1989) [in Russian].
A. A. Shirov, A. R. Sayapova, and A. A. Yantovskii, “Integrated input-output balance as an element of analysis and forecasting in the post-soviet space,” Stud. Russ. Econ. Dev. 26, 7–14 (2015).
J. Oosterhaven and G. Hewings, Interregional Input-Output Models in Handbook of Regional Science (Springer-Verlag, Berlin, 2014), pp. 875–901. https://doi.org/10.1007/978-3-642-23430-9_43
D. B. Fuller, V. J. M. F. Filhoa, and E. F. de Arruda, “Oil industry value chain simulation with learning agents,” Comput. Chem. Eng. 111, 199–209 (2018). https://doi.org/10.1016/j.compchemeng.2018.01.008
C. Keramydas, D. Aidonis, and D. Bechtsis, “Agent-based simulation for modeling supply chains: a comparative case study,” Int. J. New Technol. Res. 2 (10), 36–39 (2016).
V. I. Suslov, et al., “Agent-based multi-regional input-output model of the Russian economy,” Ekon. Mat. Metody 52 (1), 112–131 (2016).
E. V. Lukin, et al., “Experience in agent-based modeling of interregional value chains,” Ekon. Sots. Peremeny: Fakty, Tendentsii, Prognoz 13 (6), 101–116 (2020). https://doi.org/10.15838/esc.2020.6.72.6
I. V. Naumov, “Investigation of interregional relationships in the formation of the investment potential of the territory by methods of spatial modeling,” Ekon. Reg. 15 (3), 720–735 (2019). https://doi.org/10.17059/2019-3-8
V. A. Kryukov, et al., “Problems of development of a unified complex of means of macroeconomic interregional intersectoral analysis and forecasting,” Ekon. Reg. 16 (4), 1072–1086 (2020). https://doi.org/10.17059/ekon.reg.2020-4-5
M. Matsui, “Management game theory: manufacturing vs. service enterprise type,” Int. J. Prod. Qual. Manage. 1 (1–2), 103–115 (2006). https://doi.org/10.1504/IJPQM.2006.008376
G. Keshelashvili, “Value chain management in agribusiness,” Int. J. Bus. Manag. 6 (2), 59–77 (2018). https://doi.org/10.20472/BM.2018.6.2.004
Á. Mesterházy, J. Oláh, and J. Popp, “Losses in the Grain Supply Chain: Causes and Solutions,” Sustainability 12 (2342), 1–18 (2020). https://doi.org/10.3390/su12062342
T. Kim, J. W. Cheong, J.-H. Lee, M. Shin, N. R. Park, and Y. Kim, “Strategies to strengthen industrial cooperation with major emerging countries in Southeast Asia,” World Econ. Update 4 (10), (2014). https://doi.org/10.2139/ssrn.2436804
T. Aronsson and E. Koskela, Optimal Income Taxation, Outsourcing and Policy Cooperation in a Dynamic Economy: CESifo Working Paper No. 2776 (CESifo, Munich, 2009).
A. V. Kotov, “Determining the smart specialization of Russian regions in the context of domestic and European experience,” Reg. Res. Russ. 11, 378–386 (2021). https://doi.org/10.1134/S2079970521030084
J. Paap, “Mapping the technological landscape to accelerate innovation,” Foresight STI Governance 14 (3), 41–54 (2020). https://doi.org/10.17323/2500-2597.2020.3.41.54
R. N. Roux, E. van der Lingen, and A. P. Botha, “A systematic literature review on the titanium metal product value chain,” S. Afr. J. Ind. Eng. 30 (3), 115–133 (2019).
E. Kutsenko and Y. Eferin, “Whirlpools” and “safe harbors” in the dynamics of industrial specialization in Russian regions,” Foresight STI Governance 13 (3), 24–40 (2019). https://doi.org/10.17323/2500-2597.2019.3.24.40
A. Bosch and N. Vonortas, “Smart specialization as a tool to foster innovation in emerging economies: lessons from Brazil,” Foresight STI Governance 13 (1), 32–47 (2019). https://doi.org/10.17323/2500-2597.2019.1.32.47
Funding
The study was supported by the Russian Foundation for Basic Research, project no. 20-110-50491 “Regulation of interregional value chains: problems of analysis and modeling.”
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Translated by A. Ovchinnikova
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Lukin, E.V. Regulation of Interregional Value Chains: Problems of Analysis and Modeling. Stud. Russ. Econ. Dev. 33, 11–21 (2022). https://doi.org/10.1134/S1075700722010117
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DOI: https://doi.org/10.1134/S1075700722010117
Keywords:
- interregional value chains
- analysis
- interindustry models
- input-output models
- agent-oriented models
- regulation
- smart specialization