STRATEGIC IMPERTATIVES OF DIGITALIZATION OF SCIENTIFIC PROJECT MANAGEMENT SYSTEMS IN CONDITIONS OF INSTABILITY

Abstract

The article explores the strategic aspects of digitalization of the scientific project management system in conditions of instability of the socio-economic environment. Theoretical approaches to the digital transformation of management are analyzed, in particular, systemic, process, innovative and data-driven approaches, which form the basis of modern management decisions in the scientific sphere and ensure the integration of resources, processes and results of scientific activity. It is determined that their comprehensive application contributes to the formation of adaptive, flexible and result-oriented models of scientific project management. An analysis of the macroeconomic prerequisites for the development of science based on the dynamics of gross domestic product was carried out, which allowed to determine the general trends in the functioning of the economy in conditions of instability and assess their impact on the financing of scientific activity. It is established that economic fluctuations caused by external and internal factors directly affect the volume of investments in science and determine the possibilities of its digital transformation. The structure of science financing in Ukraine was studied, which made it possible to identify priority areas of state support, as well as existing imbalances in the distribution of resources between human capital, infrastructure development and innovative activities that require optimization. Particular attention was paid to assessing the level of digitalization of the scientific sphere, in particular, the implementation of electronic platforms for managing scientific projects, analytical data processing systems, scientometric tools and digital information resources. It was determined that the use of modern digital technologies ensures increased transparency of management processes, contributes to the optimization of the use of financial and human resources, and also improves the quality of management decision-making based on data analysis. At the same time, it was established that the level of development of digital infrastructure remains insufficient, which limits the potential for a full-fledged digital transformation of scientific activity.