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Russian Journal of Industrial Economics

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Software product in the system of management of state-owned corporation

https://doi.org/10.17073/2072-1633-2021-3-309-316

Abstract

The authors present their methodological recommendations for choosing a software complex to make managerial decisions within a corporation’s activity. They study the system of management in state-owned corporations and give reasons for its improvement by means of implementing IT-decisions. Digitalization is transforming managerial decision making process in corporations in accordance with the speed of decision-making, timely maintenance of production process, ways and forms of information transmission. The authors prove that top-management’s responsibility for a company’s competitive positions in the market is growing fast due to the more intensive implementation of information technology and continuous development of innovative decisions. As state-owned enterprises have a complicated interdependent structure, the system of their management becomes a process which should conform with conceptual basis and principles of transformation of a company’s activity within digital economics. The authors prove that suggested recommendations for using big data technologies, determining and implementing IT-decisions make it possible to increase the efficiency of the management system by means of optimizing business process.

About the Authors

O. V. Danilova
Financial University under the Government of the Russian Federation
Russian Federation

Olga V. Danilova – Dr. Sci. (Econ.), Professor

49 Leningradsky Ave., 125167 Moscow, Russian Federation



D. N. Zhuravleva
Financial University under the Government of the Russian Federation
Russian Federation

Daria N. Zhuravleva – Graduate Student

49 Leningradsky Ave., 125167 Moscow, Russian Federation



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Danilova O.V., Zhuravleva D.N. Software product in the system of management of state-owned corporation. Russian Journal of Industrial Economics. 2021;14(3):309-316. (In Russ.) https://doi.org/10.17073/2072-1633-2021-3-309-316

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ISSN 2072-1633 (Print)
ISSN 2413-662X (Online)