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Methodological approaches to the identification and assessment of risks of agricultural enterprises
The article examines the issues of identifying and assessing risks faced by agricultural enterprises under conditions of high uncertainty, particularly under the influence of full-scale military aggression. It is proven that the modern operating environment of the agricultural sector is characterized by profound cascading threat effects, including the destruction of logistics chains, partial or complete loss of production capacities, large-scale mining of agricultural land, and high price volatility. It is concluded that such circumstances make it impossible to rely exclusively on the traditional risk management algorithms. The study analyzes the application of foreign methodological approaches to rapid damage and needs assessment (RDNA3) for determining direct and indirect losses in the agricultural sector. The necessity of implementing a comprehensive risk management algorithm directly at the micro level is substantiated, based on the practical integration of ISO 31000 and COSO ERM standards, as well as the World Bank’s concept of «risk layering.» The differences between qualitative and quantitative methods of uncertainty assessment are generalized. It is emphasized that qualitative expert tools (the Delphi method, SWIFT analysis, and synectic’s) are effective for primary screening and identification of threat sources; however, they remain vulnerable to subjectivity. On the other hand, the application of purely quantitative mathematical algorithms is insufficiently effective due to the lack of relevant historical data sets under extreme conditions. To overcome these methodological gaps, a systematic transition toward the application of hybrid (semi-quantitative) models is proposed, capable of mathematically formalizing subjective expert knowledge and converting it into precise numerical indicators. The peculiarities of applying the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) for multicriteria weighting of heterogeneous factors using triangular fuzzy numbers are considered. The implementation of a stochastic hybrid Monte Carlo method with the direct involvement of expert judgment for modeling ranges of financial losses is proposed. Particular attention is paid to the application of Bayesian probabilistic networks and weighted barrier protection diagrams for the spatial visualization of cause-and-effect relationships and the diagnosis of cascading effects. It is substantiated that the integration of these hybrid methods into a unified information and analytical system of the enterprise enables management to avoid inefficient use of investments, optimize budgets for strengthening the weakest areas of activity, increase overall resilience, and provide a basis for planning reserve funds during the post-war recovery period. Keywords: risk identification, risk assessment, risk management, agricultural enterprises, qualitative methods, quantitative methods, hybrid models.
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