Supply chain · Resilient Agri-Food Supply Chains: A Data-Driven Approach

The COVID-19 Pandemic, the Russian-Ukrainian War and other global crises have caused significant global disturbances in supply networks, especially in the agri-food industry. These events have greatly changed the traditional supply chain models, making it apparent that innovative approaches are needed to increase the resilience of Agri-food supply chains (AFSC). To overcome the major hurdle of shocks to which AFSCs tend to be vulnerable, this study attempts a holistic framework that integrates supply chain resilience (SCR) with sustainability objectives aligned with United Nations Sustainable Development Goals (SDGs), particularly: SDG 8 Decent Work and Economic Growth; and SDG 9 Industry, Innovation and Infrastructure. The project aims to bridge the knowledge gap regarding the intricate impacts of global crises on AFSCs by focusing on key areas like assessing AFSC transitions following a disruption, analysing diversification strategies, assessing workforce readiness, developing a solid framework for risk management, and leveraging the full potential of data-driven technologies like blockchain and data analytics. The study will assess how these components can work together to improve resilience, which will ultimately result in a robust AFSC framework. By analysing AFSC in Eurozone countries, the study will identify significant potential and issues, leading to the development of actionable policies and solutions. This interdisciplinary and multidisciplinary research integrates data science, supply chain management, economics, information technology, and agriculture science to address a complex global challenge. The fellowship will expand the researcher's supply chain management knowledge and give the host institution useful research results that can influence industry standards. The research is expected to contribute substantially to the potential influence on global food security, AFSC management improvement and sustainable economic practices.