CAPITAL TAXATION AND ECONOMIC RESILIENCE: DECISION-MAKING PREDICTION THROUGH INFORMATION SYSTEMS IN THE NATIONAL SECURITY ARCHITECTURE
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Authors:
• Florentina-Loredana Dragomir, email: Dragomir.Loredana@unap.ro, Afiliation: National Defense University Carol I, Bucharest, RomaniaPages:
• 20|32 -
Keywords: information systems, adaptive decision, predictive modelling
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Abstract:
The rapid transformation of the global economic ecosystem requires states to intelligently adapt fiscal policies, where technology becomes a strategic ally. This study explores how advanced information systems and artificial intelligence algorithms can be used to model the relationship between capital tax pressure and gross fixed capital formation (GFCF), a key indicator of economic resilience. Using longitudinal data from EUROSTAT (2010–2022) and machine learning techniques (REPTree model), the research identifies critical fiscal thresholds and relevant decision configurations for stimulating investment. The findings reveal that investment levels are not solely influenced by the absolute tax burden, but rather by strategic combinations of taxation forms and macroeconomic context. In this regard, AI-powered information systems enable not only real-time risk monitoring but also the simulation of fiscal scenarios geared toward resilience and economic autonomy. The integration of these technologies into the national security architecture provides valuable operational support for the formulation of intelligent and adaptive fiscal policies aimed at strengthening economic autonomy.
