Measuring Circular Economy Index in Agriculture at the Farm Level by using the Fuzzy Analytical Hierarchy Process
DOI:
https://doi.org/10.47654/v29y2025i1p112-144Keywords:
Circular economy index, agriculture, farm level, fuzzy analytic hierarchy process (FAHP), sustainability assessmentAbstract
Purpose: The Circular economy has emerged as a vital framework for achieving sustainable agriculture in the face of global climate change, environmental degradation, and rising food demand. However, most existing indicators measure circularity from isolated aspects, resulting in biased or incomplete assessments. To get a solution to the issue, this study develops a comprehensive Circular Economy Index (CEI) for agriculture at the farm level by using the Fuzzy Analytical Hierarchy Process (FAHP), and by providing a multidimensional and consistent approach to evaluate circular performance.
Design/methodology/approach: The study integrates expert judgments and farm-level data to assess circularity across the technical and impact dimensions—covering environmental, economic, and social aspects. The FAHP method enables systematic weighting of multiple indicators under uncertainty, offering a robust framework for both empirical analysis and policy evaluation.
Findings: The results demonstrate that impact-related criteria account for 61% of the total CEI weight, underscoring the dominance of environmental and social factors in assessing circularity. Among six agricultural models examined, the integrated VAC (Vuon-Ao-Chuong) system achieved the highest CEI score (42.2), highlighting its superior performance in nutrient recycling, biodiversity conservation, and overall sustainability.
Originality/value: This study is the first to design and implement a comprehensive, multi-dimensional CEI tailored to farm-level agriculture in Vietnam, overcoming the limitations of conventional single-aspect measures. It contributes to the literature of decision sciences by demonstrating how FAHP can operationalize complex and multi-criteria evaluations in uncertain contexts. For academics, the study offers a replicable model for quantitative CE assessment; and for policymakers and practitioners, it provides an evidence-based tool to identify, benchmark, and scale up circular agricultural systems that promote both economic efficiency and environmental stewardship.
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