The Conception of Modeling the Impact of Risks on the Performance of Industrial Enterprises
Kornijenko A. M., Horal L. T.

Kornijenko, Andrij M., and Horal, Liliana T. (2025) “The Conception of Modeling the Impact of Risks on the Performance of Industrial Enterprises.” The Problems of Economy 3:193–201.
https://doi.org/10.32983/2222-0712-2025-3-193-201

Section: Economics and Enterprise Management

UDC 338.2:620.9

Abstract:
By examining scientific approaches to conceptions of modeling the impact of risks on the activities of manufacturing enterprises, their dualism was revealed, reflecting the development of the conception of systemic and integrated modeling in Ukrainian economic schools and the quantitative-probabilistic methodology among foreign researchers. This study proposes a foundation for developing an original conception of modeling the impact of risks on the activities of manufacturing enterprises, combining the systematic nature of domestic research with the analytical precision of international practices. The focus is on oil and gas enterprises (particularly geological exploration companies) that are currently in a high-risk zone. The article substantiates the need to develop an innovative conception for modeling the impact of risks on the operations of manufacturing enterprises, especially in the context of a BANI world, where traditional linear risk assessment methods are inadequate. Special attention is paid to geological exploration enterprises as a critical, high-risk element of the national economy. Based on the analysis of research in the field of risk studies, a multidimensional system of risk indicators is proposed, grouped into seven categories: from geological-technical and economic-financial to psychological, human, and digital aspects. The key element of the conception is integrated modeling, which involves the use of neural network methods (MLP, RBF, RNN/LSTM) to calculate a unified integral risk indicator. The application of Kohonen self-organizing maps (SOM) is substantiated for clustering risk profiles (“Neuro-maps”), visualizing nonlinear relationships, and substantiating weighting coefficients, which enhances the representativeness of the model. The practical significance of the conception lies in the formation of a risk zone matrix based on the integral indicator and the possibility of decomposing risk levels across business processes of enterprises to enable online monitoring and support targeted managerial decision-making.

Keywords: risk, modeling, neural networks, cluster analysis, integral indicator.

Fig.: 1. Tabl.: 3. Bibl.: 32.

Kornijenko Andrij M. – Postgraduate Student, Ivano-Frankivsk National Technical University of Oil and Gas (15 Karpatska Str., Ivano-Frankіvsk, 76018, Ukraine)
Email: kugr2014@gmail.com
Horal Liliana T. – Doctor of Sciences (Economics), Professor, Professor, Department of Finance, Vasyl Stefanyk Carpathian National University (57 Shevchenka Str., Ivano-Frankіvsk, 76018, Ukraine)
Email: liliana.goral@gmail.com

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