Modeling trends in economic digitalization based on the synthesis of empirical information: limitations and opportunities

DOI: 10.33917/es-6.204.2025.26-33

Conceptual approaches to modeling trends in information technology are discussed. It is shown that modeling IT trends solely based on technology interest data, such as Gartner’s Hype Cycle, is insufficient to predict the emergence of new technologies. Various IT examples demonstrate the need to analyze the connections between technologies, as success in some areas of economic digitalization creates the conditions for technological development in others. Furthermore, due to the high knowledge intensity of information technology, the depth of fundamental and applied scientific research must be taken into account. When modeling trends, the demand for technologies in specific economic sectors must also be considered. Simulations based on empirical data must identify simple and explainable relationships, and high-quality predictions must be achieved by synthesizing all the relationships of the technology under study. The proposed conceptual approach can also be applied to modeling other socioeconomic processes based on the synthesis of empirical data.

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