METHODOLOGICAL APPROACHES TO ASSESSING AND MANAGING RISKS IN BUSINESS ACTIVITIES OF ENTERPRISES

Abstract

The article substantiates, conceptualizes, and enhances the theoretical, methodological, and applied foundations for the comprehensive assessment and management of operational risks faced by enterprises within the grain product subcomplex amidst high economic uncertainty, market volatility, supply chain disruptions, severe security threats, and martial law conditions. It is demonstrated that conventional risk assessment techniques – which rely strictly on retrospective statistical data, simple financial loss records, or isolated performance indicators – are structurally inadequate for maintaining the operational resilience, strategic adaptability, and long-term competitiveness of agricultural businesses facing modern systemic shocks. To address these limitations, the study formulates an original combined methodological approach that strategically synthesizes statistical analysis, expert judgments, matrix prioritization, scenario modeling, and fuzzy logic tools. A multi-tiered system of indicators is established, rigorously categorizing parameters into quantitative metrics (including crop yield, cost of production, profitability, financial liquidity, and logistics-related expenses) and qualitative dimensions (such as managerial efficiency, counterparty dependence, institutional and regulatory shifts, security vulnerabilities, and technological infrastructure standards). The authors construct an adapted risk management cycle structured around eight sequential, interconnected stages – progressing from contextual environment analysis and source identification to indicator normalization, integral scoring, functional response implementation, and continuous monitoring feedback loops. Furthermore, a conceptual model for risk assessment is proposed to process fragmented internal accounting data and external market intelligence into a unified evaluation of the enterprise’s integral risk level (categorized as low, moderate, high, or critical). This decision-support framework establishes a direct operational transition from multidimensional risk diagnostics to the selection of economically justified risk treatment strategies – such as avoidance, mitigation, structural diversification, resource buffering, or risk retention – across key operational, financial, logistics, and marketing functional domains of agribusiness.