A multidimensional evaluation of sustainability performance in Slovak family farming

Purpose. As the European agricultural sector navigates the “green transition” under the Common Agricultural Policy (CAP), understanding the drivers of farm sustainability has become imperative. The aim of this study is to determine the extent to which management philosophies categorised as conventional, organic, or regenerative influence the sustainability performance of Slovak family farms. Methodology. To achieve comprehensive diagnostics across 13 dimensions of systemic health, the research utilises the Indicateurs de Durabilité des Exploitations Agricoles (IDEA) framework, representing its first application within the empirical context of Slovak agriculture. The novelty of this approach lies in combining this first-of-its-kind national implementation with an advanced quantitative validation pipeline tailored for high-dimensional farm data. The study employs hierarchical cluster analysis using Ward’s method, validated structurally via silhouette analysis and multidimensional scaling. Data were normalised using Min-Max scaling to ensure variable comparability. To address data uncertainty and test spatial and systemic stability, the methodology introduces probabilistic Monte Carlo simulations (1,000 iterations). Comparative statistical significance between management systems was evaluated using the non-parametric Kruskal-Wallis test accompanied by post-hoc Wilcoxon rank-sum tests. Results. The results of the assessment and analysis of the sustainability level of Slovak family farms, categorised according to three farming philosophies (conventional, organic, and regenerative), indicate that management type is a statistically significant determinant of performance in 11 out of 13 dimensions (p < 0.01). Key findings reveal a profound mathematical convergence between organic and regenerative models, with the latter emerging as the most stable sustainability archetype. The analysis refutes the “viability paradox”, demonstrating that organic and regenerative systems achieve economic and financial viability medians identical to conventional models (0.43). Originality. The study provides a unique multidimensional synthesis of Slovak family farming through advanced unsupervised machine learning techniques. A key contribution is the use of silhouette analysis to identify a segment of “hidden sustainability” within conventional holdings – farms that mathematically align with agroecological profiles despite lacking formal certification. This reveals that the boundaries between management philosophies are more fluid than traditionally assumed in policy frameworks. Practical implications. These findings suggest that Slovak agricultural policy should prioritise targeted “eco-scheme” interventions for transitional farms, leveraging existing latent sustainability to meet European Green Deal objectives. The study offers a pragmatic diagnostic framework for policymakers to identify farms with high agroecological potential, facilitating a more effective and data-driven implementation of CAP strategic plans.