Dynamic Modeling of Innovative Knowledge Production Processes

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Abstract

The report describes the process of constructing a dynamic model of a socio-economic system, the agents of which are intellectually and emotionally involved in the production of new knowledge and its transformation into technology. The dynamic model of the organizational system is formalized as a system of four differential equations and describes the dynamics of interrelated factors: emotional involvement, personal tacit knowledge, corporate technology and material incentives. Numerical methods were used to find a particular solution to the system of differential equations. Bifurcation analysis methods were used to study and interpret the phase portraits of the system when changing the parameter responsible for the dissipation of the emotional resource of workers into the environment. The report is part of a fundamental study, the applied part of which will provide project managers of modern enterprises with a tool for planning and managing production processes that require high emotional involvement of workers - emotional labor. Such planning should solve the problem of preventing and preventing the syndrome of emotional burnout of employees. Methods of quantitative accounting and dynamic modeling of production phenomena associated with the positive manifestation of the human factor are part of the import-substituting technology of flexible management PRACa.

General Information

Keywords: management in organizational systems, bifurcation diagram, strange attractor, emotional labor, flexible management, Scrum, PRACa

Publication rubric: Data Modeling and Analysis for Digital Education

Article type: theses

For citation: Kiselevski O.S. Dynamic Modeling of Innovative Knowledge Production Processes [Elektronnyi resurs]. Digital Humanities and Technology in Education (DHTE 2025): Collection of Articles of the VI International Scientific and Practical Conference. November 13-14, 2025 / V.V. Rubtsov, M.G. Sorokova, N.P. Radchikova (Eds). Moscow: Publishing house MSUPE, 2025,., pp. 488–503.

Information About the Authors

Oleg S. Kiselevski, Candidate of Science (Engineering), Associate Professor, Department of Machine Design Fundamentals, Belorussian-Russian University, Associate Professor of the Department of Management, Belarusian State University of Informatics and Radioelectronics, Mogilev, Belarus, ORCID: https://orcid.org/0009-0006-0546-6653, e-mail: kiselevskioleg@gmail.com

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