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Non-Linear Nature of the Impact of Digital Transformation on Strategic Management Models of Agricultural Enterprises

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Non-Linear Nature of the Impact of Digital Transformation on Strategic Management Models of Agricultural Enterprises

Serhii KhomovyiBila Tserkva National Agrarian University, Bila Tserkva, UkraineORCID 0000-0001-7483-7426
ConferenceInternational Scientific Conference "Advances in Science, Technology and Social Development"
Date26.10.2026
Pages34–38
OrganizerAcademia Publishing Hub

Abstract

The paper substantiates the non-linear nature of the relationship between the depth of an agricultural enterprise’s digital transformation and the performance of its management. Three levels of this non-linearity are identified: the trajectory level (U-shaped dynamics of returns on digital investment), the security level (growing dependence on energy and communication infrastructure as digitalisation deepens) and the population level (stratification of enterprises in the industry by adaptation strategy). It is established that the wartime shock deepens and prolongs the phase of negative returns but, once this phase is overcome, raises the value of the enterprise’s analytical capabilities. Three phases of the digital transformation trajectory (cost accumulation, turning point and returns) are proposed, and priority management tasks are defined for each of them. It is concluded that digital transformation should be managed at the strategic rather than the project level, and information and analytical support should show where on the transformation trajectory the enterprise currently stands.

Keywords

digital transformation; non-linear relationship; strategic management; agricultural enterprises; information and analytical support; digital resilience.

How to cite (DSTU 8302:2015)

Khomovyi S. Non-Linear Nature of the Impact of Digital Transformation on Strategic Management Models of Agricultural Enterprises. Advances in Science, Technology and Social Development : Proceedings of the International Scientific Conference / Academia Publishing Hub (Rotterdam, 26 October 2026). Rotterdam, 2026. P. 34–38. DOI: 10.64076/ap261026.01.

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