Estimating agricultural sustainability: a multidimensional approach to a farm-level assessment tool

In response to the growing demand for practical and robust sustainability assessment tools, this study introduces a new method for evaluating agricultural sustainability at the farm level. The tool relies on indicators covering environmental, economic, and mixed dimensions of sustainability. The mixed dimension integrates environmental, economic, and social indicators. Indicators were selected based on the literature and empirical data from Hungarian farms. From 61 initial indicators, three groups were formed through factor analysis and clustering. The analysis revealed that environmental and economic factors contribute almost equally to sustainability scores, whereas the mixed dimension has a comparatively smaller impact. This suggests that immediate sustainability improvements might need to prioritize environmental and economic factors. The assessment tool allows the calculation of a complex agricultural sustainability index, which has been validated through case studies on Hungarian farms. This study is presented as a methodological pilot project to develop and test a farm-level sustainability assessment tool for agricultural enterprises. The results highlight the practical applicability of the tool for farmers and policymakers, as it offers a transparent, easy-to-use method for identifying sustainability strengths and weaknesses at the enterprise level. Limitations include a small, region-specific sample, which may restrict broader applicability. Additionally, there are challenges in integrating multidimensional indicators. Future research should focus on expanding the dataset, refining indicator weighting, and testing the tool’s applicability in a broader agricultural context. This enhances the robustness and guides stakeholders in sustainable agricultural development.

• Publication year

  2026

• Venue

  Frontiers in Environmental Science

• Publication date

  2026-01-12

• Fields of study

  Not labeled

• Identifiers
  DOI 10.3389/fenvs.2025.1704344
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

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