Sustainability assessment has become central to production systems, but existing tools often provide fragmented, product-oriented, static, or poorly interpretable evaluations. Current assessment methods rarely integrate production functions with territorial characteristics, ecosystem services and dynamic data flows. Moreover, many tools depend on proprietary databases, specialised users and delayed outputs, limiting their practical usefulness for all potential users. This study proposes a new sustainability assessment framework designed to evaluate complex systems as agricultural and agro-livestock systems at farm level. The method aims to provide objective, transparent and decision-relevant information, while supporting policy guidance, farm management and communication along the supply chain. The method organises sustainability into three domains: environmental, territorial and social-economic. Relevant clusters are selected for each domain and assessed through farm-level indicators and territorial-context indicators. Drawing on risk assessment theory, each cluster is evaluated by combining the frequency of farm functions with the magnitude of their contextual effects. Indicators are normalised into a four-level matrix to obtain four grades for farm functions (lacking, rare, probable, highly probable), and environmental, territorial and social-economic vulnerability (light, medium, heavy, very heavy) of the farm settlement area. This evaluation results in sixteen values, which are then classified into four classes (negligible; medium; relevant; very relevant), aggregated into a sustainability composite index and, where appropriate, weighted according to policy priorities. The framework offers a dynamic, system-oriented and potentially semi-automated tool for routine on-farm assessments. It can support benchmarking, ex-ante evaluations, sustainable intensification, policy incentives, circularity strategies and consumer communication through a sustainability classification or label.

Sustainability evaluation of complex systems (Part 1): a new operational, strategic and communication tool

Biagini, D.
2026-01-01

Abstract

Sustainability assessment has become central to production systems, but existing tools often provide fragmented, product-oriented, static, or poorly interpretable evaluations. Current assessment methods rarely integrate production functions with territorial characteristics, ecosystem services and dynamic data flows. Moreover, many tools depend on proprietary databases, specialised users and delayed outputs, limiting their practical usefulness for all potential users. This study proposes a new sustainability assessment framework designed to evaluate complex systems as agricultural and agro-livestock systems at farm level. The method aims to provide objective, transparent and decision-relevant information, while supporting policy guidance, farm management and communication along the supply chain. The method organises sustainability into three domains: environmental, territorial and social-economic. Relevant clusters are selected for each domain and assessed through farm-level indicators and territorial-context indicators. Drawing on risk assessment theory, each cluster is evaluated by combining the frequency of farm functions with the magnitude of their contextual effects. Indicators are normalised into a four-level matrix to obtain four grades for farm functions (lacking, rare, probable, highly probable), and environmental, territorial and social-economic vulnerability (light, medium, heavy, very heavy) of the farm settlement area. This evaluation results in sixteen values, which are then classified into four classes (negligible; medium; relevant; very relevant), aggregated into a sustainability composite index and, where appropriate, weighted according to policy priorities. The framework offers a dynamic, system-oriented and potentially semi-automated tool for routine on-farm assessments. It can support benchmarking, ex-ante evaluations, sustainable intensification, policy incentives, circularity strategies and consumer communication through a sustainability classification or label.
2026
32
1
18
Cluster-based sustainability indicators; Farm sustainability index; Risk matrix assessment; Sustainability dimensions; Sustainability label classification
Biagini, D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2157690
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