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Developing the digital twin of the economic, financial, information and logistics inter-cluster cooperation mechanism

Vol. 26, Iss. 7, JULY 2020

Received: 1 June 2020

Received in revised form: 15 June 2020

Accepted: 29 June 2020

Available online: 30 July 2020

Subject Heading: INVESTING

JEL Classification: C63, E17, O21, O36

Pages: 1448–1468

https://doi.org/10.24891/fc.26.7.1448

Yashin S.N. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
jashinsn@yandex.ru

https://orcid.org/0000-0002-7182-2808

Trifonov Yu.V. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
kei@ef.unn.ru

https://orcid.org/0000-0002-4745-0004

Koshelev E.V. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
ekoshelev@yandex.ru

https://orcid.org/0000-0001-5290-7913

Subject. This article deals with the issues related to the use of digital twins in order to manage innovation and industrial clusters and the liaison between them.
Objectives. The article aims to develop a digital twin model of inter-cluster cooperation within a Federal district of Russia. The Volga (Privolzhsky) Federal District is considered a case study.
Methods. For the study, we used a multiple non-linear regression method and a fast simulated annealing (FSA).
Results. The article offers and describes a designed digital twin model of inter-cluster cooperation mechanism.
Conclusions and Relevance. When reallocating investment and human resources within one federal district, the interests of the population of innovation and industrial clusters should be taken into account, as only just an increase in fixed investment does not always lead to the growth of the region's population. The use of the digital twin model of inter-cluster cooperation mechanism will help avoid premature unreasonable management decisions of the public-policy level regarding the further development of innovation-industrial clusters.

Keywords: digital twin, inter-cluster cooperation, simulation modeling, simulated annealing

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