Agri-food systems face multifaceted challenges across political, environmental, social, technological, economic, and legal dimensions. For stakeholders, advisors, and policymakers striving for sustainability, understanding and prioritising the most urgent systemic challenges is essential. This paper presents an exploratory proof-of-concept study utilising a mixed-methods approach to identify and prioritise these challenges, and to provide an operational tool to inform targeted interventions aimed at building resilient food systems. The research integrates an initial literature review with a multiple case study of three Dutch agri-food organisations: an applied research centre, an alternative food network, and a blockchain technology provider. Primary data collected via semi-structured interviews and follow-up surveys were evaluated using content analysis alongside a fuzzy-based Severity-Likelihood Assessment Matrix. Unlike conventional risk assessment methods, this approach applies Triangular Fuzzy Numbers (TFN) to mathematically model and quantify the uncertainty and ambiguity inherent in subjective expert judgements within complex, multi-stakeholder settings. The results identify 19 high-level challenge categories. Biodiversity loss, financial costs, market dynamics, and consumer behaviour emerged as the most critical issues from the perspective of the participating organisations. Furthermore, findings demonstrate that while many challenges are shared across institutions, their severity and likelihood remain context-dependent. The primary contribution of this work is a replicable, proactive methodology that equips decision-makers with a structured foundation for strategic planning and intervention design. Ultimately, this systems-oriented approach provides the clarity needed to navigate operational complexity and advance sustainable agri-food transitions.
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Burgess et al. (2026) studied this question.
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