An analytical approach to risk assessment in agri-food supply chains using fuzzy inference systems

This study presents a structured, quantitative risk assessment framework for agri-food supply chains (AFSCs), aligned with the guidelines of ISO 31000:2018. The approach integrates Fuzzy Inference Systems (FIS) to quantify and mitigate risks, offering an effective tool to reduce subjectivity, manage uncertainty, and enhance decision-making accuracy. A FIS based risk assessment model was developed using the Probability of Failure (PoF), Consequence of Failure (CoF) and Potential Failure Risk (PFR). Employing the developed FIS models, three disruption scenarios in AFSCs in developing economies were evaluated. The scenarios include: (1) lack of quality farm inputs, (2) lack of logistics infrastructure, and (3) supply-demand mismatches. As per the results, lack of farm inputs results in very high risk in price volatility, high risk in farmer revenue loss and food availability, and moderate risk in post-harvest waste. Logistics inefficiencies are leading to moderate risk in farmer revenue loss while posing low risk in food availability, price volatility, and post-harvest waste. Systemic risks due to supply-demand mismatches result in high risks in price volatility, farmer revenue loss, food availability and post-harvest waste. The proposed risk assessment framework provides the blueprint to develop a risk assessment software for AFSCs in developing economies, which can provide insights on how to combine risk assessment in policy development for supply chain modernisation. Findings of the study suggest that there is a need for a policy-driven systematic approach through market intelligence to manage this volatile supply chain. • Develop a fuzzy logic model for agri-food supply chain risk assessment. • Quantify the impacts of disruptions using a structured analytical approach. • Provide a foundation for developing risk assessment software tools. • Integrate ISO 31000:2018 principles into supply chain risk management. • Support policy development for supply chain modernization efforts.