Аннотация
Sustainable development of the agri-food sector in emerging economies requires the use of analytical tools capable of taking into account climate risks, environmental constraints, and investment flow instability when making management decisions. Given the fragmentary nature of statistical information and the high volatility of the external environment, traditional econometric methods for assessing investment attractiveness demonstrate limited effectiveness and low interpretability. This study proposes an agent-oriented modular fuzzy decision support framework for the comprehensive assessment of sustainable investments in the agricultural sector. The developed approach combines a modular data processing architecture that provides automated collection and preprocessing of heterogeneous statistical sources (OECD, FAO, and national statistics), with a fuzzy additive aggregation (Fuzzy-SAW) mechanism that allows for interpretable multi-criteria assessment of economic, environmental, and production-forecasting factors. The methodological novelty of the study lies in the integration of an automated data processing pipeline with an explainable fuzzy multi-criteria assessment model focused on conditions of data incompleteness and structural uncertainty. Empirical validation of the model was performed using statistical data from the agro-industrial complex of the Republic of Kazakhstan for the period 2010–2023. The results show that the proposed framework effectively smooths out short-term volatility in indicators and identifies long-term structural trends in investment attractiveness. In particular, in 2021–2023, the integral index of sustainable investment remained at around 0.37, despite adverse climate shocks, mainly due to the compensatory effect of growth in private investment flows, which indicates the formation of mechanisms for the adaptive sustainability of the agricultural sector. The proposed analytical framework is a scalable and interpretable decision support tool that can be used by government agencies, investors, and industry analysts in developing long-term strategies for sustainable agricultural development in emerging economies.