ADAPTIVE STRATEGY FOR SOCIO-ECONOMIC DEVELOPMENT OF ECONOMIC ENTITIES IN THE AGRICULTURAL SPHERE BASED ON DIGITIZATION AND I

Abstract

Introduction. The article highlights the critical need to rethink strategic approaches to managing business entities in the agricultural sector of Ukraine in the context of global macroeconomic instability in 2022–2026. It is substantiated that traditional static development strategies focused on quantitative production indicators are losing their effectiveness under the pressure of logistical disruptions, energy volatility, and changes in the institutional conditions of market functioning. There is an objective need to develop an adaptive strategy based on flexibility, resilience, and predictive management. Special attention is paid to the theoretical justification of how digitalization and innovation change the transactional environment of the enterprise, transforming information flows into a strategic resource for overcoming market uncertainty.

The purpose of the article is to scientifically substantiate the conceptual model of the adaptive strategy of socio-economic development of agricultural business entities based on digitalization and innovation, as well as to analyze the mechanisms for leveling information asymmetry through the use of Big Data technologies and artificial intelligence within the framework of neo-institutional theory.

Materials and methods. The methodological basis of the study was the fundamental provisions of modern economic theory, in particular D. North's [1] institutional theory (regarding transaction costs and information asymmetry), J. Schumpeter's [2] concept of innovative development, and the theory of human and social capital. In the process of work, a complex of general scientific and special methods was used: system-structural analysis (to build the architecture of an adaptive strategy); abstract-logical generalization (to form theoretical conclusions); statistical-economic comparison (to assess the effectiveness of digital tools); methods of predictive modeling and scenario analysis.

Results. Based on the analysis, it is proven that adaptive strategy in the agricultural sector is a multi-level system that integrates technological, social and institutional modules. It is established that the use of Big Data and artificial intelligence (AI) for predictive analytics allows entities to level information asymmetry in markets, which is consistent with D. North's institutional theory of reducing transaction costs. The author substantiates that digitalization plays the role of an “institutional filter” that minimizes information distortions and opportunistic behavior of counterparties. The results of the study confirm that entities that have implemented adaptive digital models demonstrate 15–20% lower production costs and 12% higher social resilience (shareholder loyalty) compared to traditional enterprises. A mechanism for transforming the transaction environment has been formed, where digital assets are transformed into “digital capital” — a key factor of stability in conditions of polycrisis.

Prospects. Further scientific developments will be aimed at creating applied tools for assessing the "digital divide" between domestic agricultural entities and the requirements of the EU single digital market, as well as at developing algorithms for automated strategic risk management in the context of post-war restoration of the agricultural sector.