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Liburkina L. M.

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Methods for Forecasting Trends in the Development of the Information Potential of Energy Sector Enterprises
Shepelenko S. M.

Shepelenko, Svitlana M. (2025) “Methods for Forecasting Trends in the Development of the Information Potential of Energy Sector Enterprises.” Business Inform 7:499–507.
https://doi.org/10.32983/2222-4459-2025-7-499-507

Section: Management and Marketing

Article is written in Ukrainian
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UDC 330.4:620.9:004.9

Abstract:
The relevance of this study is driven by the need to improve the management efficiency of energy enterprises in the context of digital transformation, where the ability to timely forecast the development of information potential plays a crucial role in ensuring digital coherence, optimizing resources, and reducing information risks. Methods for forecasting trends in the development of information potential are presented, including analytical, deterministic, stochastic, and fractal-cluster methods. It is shown that deterministic models are based on the analysis of historical data and patterns, stochastic models consider probabilistic fluctuations and process uncertainty, and fractal-cluster analysis allows for identifying patterns in complex and large information datasets. The integration of these methods ensures a more accurate assessment and forecast of the development of information potential, which is a prerequisite for improving management efficiency and digital coherence in energy enterprises. Methods for forecasting trends in the development of the information potential of energy enterprises are examined as a key tool for enhancing management efficiency and ensuring digital coherence in the context of global digital transformation. Modern forecasting methods, including analytical, deterministic, stochastic, and fractal-cluster models, are analyzed, with an emphasis on their application in assessing the dynamics of information resources, technological platforms, and personnel competencies. Particular attention is paid to an integrated approach that combines various forecasting methods to provide a more precise and comprehensive evaluation of the development of information potential. The proposed systematization of forecasting methods provides a scientific foundation for developing practical recommendations on managing information potential, promotes the enhancement of decision-making efficiency, and the integration of digital tools into enterprise operations.

Keywords: information potential, energy enterprises, energy sector, forecasting methods, digital coherence, deterministic models, stochastic models, fractal-cluster analysis, information resources, management.

Bibl.: 15.

Shepelenko Svitlana M. – Doctor of Sciences (Economics), Associate Professor, Department of Marketing and Trade Entrepreneurship, V. N. Karazin Kharkiv National University (4 Svobody Square, Kharkіv, 61022, Ukraine)
Email: [email protected]

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