Concept to recognize crisis of organizational and institutional separation by Artificial Intelligence System

Keywords: Artificial Intelligence, classification of crises, crisis; economy, machine reasoning, organizational and institutional separation.

Abstract

The sphere of anti-crisis management is highlighted in relation to the open variety of organizational and institutional separations that are typical for the higher forms of industrial and post-industrial economies. This article shows the typicity and relevance of critical management situations associated with the emergence of crises. Furthermore, it justifies the objective orientation to a dense (not sparse) stream of crisis situations requiring identification, ranking, and classification. A strict management interpretation of the separation crisis is given through an assessment of the nature of the dynamics of the separation state indexes. Also, the document presents a generalized typological classification of crises. This article shows the necessity of using a high-level Artificial Intelligence System for this purpose, an indispensable component of which is the classification component.

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Author Biographies

Oleg N. Dmitriev, Moscow Aviation Institute (National Research University), Moscow, Russia.

Doctor in Economic Sciences, PhD in Engineering Sciences, Professor, Moscow Aviation Institute (National Research University), Moscow, Russia.

Veronika A. Zolotova, Moscow Aviation Institute (National Research University), Moscow, Russia.

Senior Lecturer, Moscow Aviation Institute (National Research University), Moscow, Russia.

References

Badalova, A. G. (2006). Risk-management of production systems: theory, methodology, implementation mechanisms. Moscow: Yanus-K.

Bazhutin, A. S. (2009). Anti-crisis management of enterprise development (Dissertation abstract of PhD in Economics). State Educational Institution of Professional Higher Education "State of Udmurt University" Izhevsk.

Biryukov, A. N. (2015). Methods of neural network modeling to rank taxpayers to determine credit risks. Economic Analysis: theory and practice, 12(411), 58-66.

Bloshenko, A. A. (2009). Technology of integral estimation of stability of financial and economic condition of the enterprise of the Russian industry (Dissertation of PhD in Economics). Moscow Aviation Institute (State Technical University) MAI, Moscow.

Butrova, E. V. (2021). Features of anti-crisis management of the enterprise in the conditions of digitalization. Journal of economics, entrepreneurship and law, 3(11), 579-590.

Cherner, N. V. (2020). Conceptual foundations of price management in the holding company. Monograph. Moscow: KnoRus.

Danilochkina, N. G. (2001). Controlling as enterprise management tool. Moscow: UNITY.

Delibašić, B, Radovanović, S., & Jayawickrama, U. (2021). Special Issue on AI for Intelligent Decision Support Systems. Guest Editorial Preface – IJDSST, 13(1). Retrieved at: https://www.igi-global.com/pdf.aspx?tid%3D267156%26ptid%3D254080%26ctid%3D15%26t%3DSpecial%20Issue%20on%20AI%20for%20Intelligent%20Decision%20Support%20Systems&isxn=null

Demchenko, O. F. (2011). Mathematical modelling methodology of organizational structures of the Russian Federation aviation industry. Moscow: KnoRus.

Dmitriev, O. N. (2005). System analysis in management. 5th edition. Moscow: Dobroe Slovo [Good Word].

Dmitriev, O. N. (2017). Strategic problems and directions of developing rehabilitation of managing systems of Russian high-tech complexes. Microeconomics, 6, 5-24.

Dmitriev, O. N. (2018). Conceptual system interpretation of conjuncture management situation in relation to market including operators in such form as high-tech enterprises. Microeconomics, 6, 29-44.

Dmitriev, O. N., & Dergunov, A. I. (2004). Intrafirm management concerning interdepartment and interpersonal competition within scope of enterprise. In English. Moscow: Gnome and D.

Dmitriev, O. N., & Novikov, S. V. (2017). Conception of managing of fuzzy-institutional meso-level organizational separations in a context of product projects internationalization. European Research Studies Journal, 20(4), 277-289.

Dmitriev, O. N., & Novikov, S. V. (2018a). Development of risk insurance area for Russian high-technology enterprises. European Research Studies Journal, 21(4), 386-399.

Dmitriev, O. N., & Novikov, S. V. (2018b). Economic assessment of federal scientific programs. Russian Engineering Research, 38(4), 326-329.

Dmitriev, O. N., & Novikov, S. V. (2019a). Verification of feasibility studies at high-technology enterprises. Russian Engineering Research, 39(9), 780-781.

Dmitriev, O. N., & Novikov, S. V. (2019b). Unification and convergence of hierarchic structures such as organizational separations and product projects at creation of recommending Decision Support Systems. International Journal of Economics and Business Administration, 7(1), 240-268.

Dmitriev, O. N., & Novikov, S. V. (2019c). Optimizing the economic information transparency level of high-tech enterprises in the post-industrial globalized economy. International Journal of Economics and Business Administration, 7(3), 25-56.

Dmitriev, O. N., & Zolotova, V. A. (2020). Formalized Conceptual Rule to Interpret Crisis State of Organizational and Economic Separation for Micro-level and Meso-level. Amazonia Investiga, 9(25), 327-336. https://amazoniainvestiga.info/index.php/amazonia/article/view/1076

Dmitriev, O. N., Yekshembiev, S. Kh., Lubaeva, J. I., Koval’kov, Ju. A., & Minaev, E. S. (2013). Strategic management concerning corporation (fundamental and applied problems). 2nd iss. (revised and expanded). Moscow: Dobroe Slovo [Good Word].

Fal’ko, S. G., & Boyko, V. P. (2019). Controlling innovative projects in the rocket and space industry: Monograph. Moscow: Russian Association of Controllers.

Fal’ko, S. G., Volochienko, V. A. & Vasiliev, S. V. (2019). Controlling: preparation of management decisions in real time: Monograph. Moscow: Russian Association of Controllers.

Forrestor, D. (1971). Fundamentals of Enterprise Cybernetics. Moscow: Progress.

Grishin, I. Yu., Timirgaleeva, R. R. (2016). The Application of artificial intelligence methods for forming industry management systems. Modern Information Technologies and IT-education, 1(12), 115-120.

Guruva, V. A. (2019). Provision of government support to the financial rehabilitation of enterprises using artificial intelligence technology. Scientific bulletin: finance, banks, investments, 2, 56-64.

Jons, M. T. (2018). All application programming. Moscow: DMK: Press.

Kanashchenkov, A. I., Dmitriev, O. N., Koval’kov, Ju. A., Dergunov, A. I. & Minaev, E. S. (2005). Management concerning interaction of enterprise with federated system of accessory subcontractors. Moscow: Dobroe slovo [Good Word].

Koval’kov, Ju. A., Dmitriev, O. N., Mel’nikov, M. K., & Cherkasov, Yu. M. (1981). Forecasting state indexes in ACS of quality and reliability. Methodical materials, series “Economics and management systems”, 4(48). Moscow: Central Research Institute “Electronics”.

Koval'kov, Ju. A., & Dmitriev, O. N. (1994). Effective Marketing Technologies. Moscow: Mashinostroenie [Mechanical engineering].

Kulikovskiy, K. L., & Petrov, D. V. (2008). Usage of artificial neural networks in management decision support systems of industrial enterprises. Bulletin of Samara State Technical University. Series: Technical Sciences, 2(22), 38-42.

Kuznetsova, A. V., Samigin, P. S., & Radionov, M. V. (2016). Artificial intelligence and information security of society. Monograph. Moscow: Ruscience.

Lapenkov, V. I. (2001). Management methodology of the current liquidity of a manufacturing enterprise (Dissertation of Full-doctor in Economics). Instituto de Aviación de Moscú, Moscow.

Malinetsky, G. G. (2001). Chaos. Structures. Computational experiment. Introduction to nonlinear dynamics. 3rd iss. Moscow: UPSS.

Minaev, E. S., & Panagushin, V. P. (1998). Anti-crisis management: Studies. Moscow: PRIOR.

Nagornov, M. A. (2008). Enterprise management in crisis situations (Dissertation abstract of full-doctor in Economics) Saratov State Social and Economic University, Irkutsk.

Novikov, S. V. (2019). Clusters in modern innovations of the economy of the Russian Federation. Espacios, 40(25), 7-14.

Pershina, E. S., & Daragan, S. V. (2018). From big data to advanced analytics in the tourism industry. Scientific Bulletin MSIIT, 2(52), 60-69.

Popov, A. (2005). Anti-crisis management. Moscow: High School.

Russell, S. J., & Norvig, P. (2018). Artificial Intelligence: A Modern Approach (AIMA). Translate by Ptitsyn К. А. 2nd iss. Moscow: Williams.

Solodukhin, D. N. (2008). Financial rehabilitation of industrial enterprises in the conditions of bankruptcy (Dissertation abstract of full-doctor in Economics). Academia de Administración Pública de Rusia bajo la presidencia de la Federación de Rusia, Moscow.

Tsvikilevich, N. G. (2009). The mechanism of overcoming economic crisis in the industrial sector of the region (Dissertation abstract of full-doctor in Economics). Udmurt State University, Izhevsk.

Wiener, N. (1983). Cybernetics. Moscow: Science.

Yankovskaya, N. G. (2009). Management of industrial enterprises in the conditions of economic crisis: innovative aspect (Dissertation abstract of full-doctor in Economics). Far Eastern State University of Transportation, Khabarovsk.

Zolotova, V. A. (2017). Management problems and tasks of the formation of management innovation anti-crisis program in the Russian high-tech industry. Monograph. Moscow: KnoRus.

Zolotova, V. A., & Dmitriev, O. N. (2018). Сonceptual interpretation of first and second kinds of errors at management mode selection under conditions of its possible crisis state. Russian Engineering Research, 38(4), 291-294.

Zykov, S. V. (2016). Crisis Management for Software Development and Knowledge Transfer. Springer Series in Smart Innovation, Systems and Technologies. Switzerland: Springer.

Zykov, S. V. (2018). Managing Software Crisis: A Smart Way to Enterprise Agility. Cham: Springer.
Published
2021-08-31
How to Cite
Dmitriev, O. N., & Zolotova, V. A. (2021). Concept to recognize crisis of organizational and institutional separation by Artificial Intelligence System. Amazonia Investiga, 10(43), 59-71. https://doi.org/10.34069/AI/2021.43.07.6
Section
Articles