The article is devoted to the development of a multi-level decision support system (DSS) aimed at optimizing the research infrastructure of innovative organizations through managing migration flows of scientific human capital (SHC). The DSS is based on a comprehensive methodology that integrates system-dynamic modeling of internal interregional migration of scientists, scenario analysis of regulatory impacts, assessment of return migration factors and modeling of migration benefits. The mathematical apparatus includes the construction of cause-and-effect diagrams (CLD), formalization of a dynamic model with level (number of employed/unemployed SHC) and flow (migration) variables described by a system of differential equations, where the annual migration volume is an endogenous function of gaps in wages, unemployment, consumer spending and rental costs. Scenario analysis examines the impact of changes in wage imbalances and support measures (rent subsidies) on migration flows and alignment of regional labor markets. To analyze return migration, logistic regression models of the probability of return are used. Additionally, the distribution of migration benefits and the dynamics of the global qualification premium are studied. At the organizational level, a motivational model for managing the risks of SHC outflow was developed, based on an indicative analysis of KPIs and establishing a polynomial correlation between the achievement of indicators and compensation. The results confirm the high efficiency of targeted support measures (rent subsidies) for the rapid alignment of regional imbalances, identify the key determinants of return migration (integration, security, family ties) and the paradox that improving conditions for highly qualified personnel does not guarantee a decrease in emigration. The proposed DSS provides a scientifically substantiated toolkit for management bodies and the leadership of innovative organizations to form a balanced research infrastructure.
DOI: 10.1007/978-3-032-13612-1_26
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Deviatkyn, D. A., Pronyshyn, S. V. (2026). A Multi-Level Decision Support System for Optimizing Research Framework of Innovative Organizations // Proceedings of the Ninth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’25), Volume 2, pp. 292–300.