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The article provides a theoretical and methodological substantiation and systematization of a comprehensive framework of analytical approaches for assessing the levels and multidimensional efficiency of innovative development in the agricultural sector under digital transformation, climate instability, and macroeconomic shock conditions. The study proves the necessity of conceptual differentiation and subsequent synthesis among “innovative potential”, “innovative activity”, and “innovative receptivity”. The study establishes a three-dimensional indicator matrix across these core functional blocks, along with a minimax normalization algorithm to derive an integrated index of innovative development level. The paper highlights the limitations of strictly financial metrics when evaluating agricultural innovations and proposes an integrated “economy — ecology — society” framework. The paper formalizes an optimization model to calculate the economic effect of local technological innovations (drones, precision farming), accounting for saved crop areas and reduced agrochemical use. The paper introduces a modified Net Present Value criterion (cap N cap P cap V sub cap A. g r i. ) that incorporates probabilistic parameters for catastrophic agroclimatic events, severe yield fluctuations, and military risks. The study also validates non-parametric Data Envelopment Analysis (DEA) combined with the Malmquist Productivity Index (MPI) to decompose total factor productivity into managerial efficiency gains and technological frontier shifts. The study identifies strategic directions for adapting the European framework of Agricultural Knowledge and Innovation Systems (AKIS), the composite AKIS Index, and ADI EU metrics to Ukrainian practice. This alignment harmonizes national diagnostics with the Common Agricultural Policy (CAP 2023–2027) and the European Green Deal. The study recommends establishing a digital innovation monitoring hub to reduce technology-adoption lags and integrating ecological capital valuation into state support mechanisms.
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Ю.А. Мярковський (2026) studied this question.
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