Threat assessment tools: building the competitiveness of agricultural enterprises to ensure sustainable development

Анотація

The primary objective of the research is to improve scientific and methodological tools for diagnosing and assessing threats to the sustainable development of agricultural enterprises, serving as the system-forming basis for food security, and to identify priority vectors for managing their competitiveness. The research methods include a complex of modern economic and mathematical techniques: critical analysis for systemizing determinants, the method of integral rating assessment (taxonomic indicator of development level by Z. Hellwig) for the quantitative measurement of vulnerability, the principal component analysis (PCA) for structural verification, and cluster analysis (k-means, Ward’s method) for enterprise differentiation. Research results: The study developed a comprehensive four-stage methodology. Initially, a representative aggregated system of indicators was formed, encompassing 13 key indicators distributed across four strategic blocks: macroeconomic, financial and investment, ecological and climatic, and production and technological threats. Subsequently, an integrated assessment of the vulnerability of business entities was conducted, enabling the ranking of enterprises by adaptability. Using PCA, the initial data array was transformed. Furthermore, the cluster analysis differentiated the agricultural enterprises into homogeneous classes with low, medium, and high threat levels, confirming that no single enterprise resides in a safe zone across all parameters. The scientific novelty of the research consists in improving the scientific and methodological tools for diagnosing and classifying threats to the sustainable development and food security of agricultural enterprises using multivariate analysis methods. Unlike existing approaches, this methodology eliminates indicator multicollinearity and justifies the allocation of five specific latent destructive factors: 1) threats related to assets and liquidity; 2) institutional and regulatory threats; 3) financial and market threats; 4) ecological and climatic threats; and 5) production and technological threats. This forms a robust spatial typology of enterprises to identify targeted management vectors. The practical significance of the obtained results lies in the possibility of using the proposed algorithm by agricultural management to objectively assess competitiveness, neutralize threats, and formulate strategic plans for sustainable development. The prospects for further research include developing specific, targeted management measures and preventive mechanisms for each identified cluster of enterprises to enhance their long-term competitiveness. Keywords: competitiveness, agricultural enterprises, sustainable development, threat assessment, principal component analysis, cluster analysis, food security, vulnerability.

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