Enhancing food supply chain management through big data technologies and strategies

Purpose – This paper explores the enhancement of Food Supply Chain Management (FSCM) through Big Data Technologies and Strategies. It assesses current key challenges, identifies areas of underutilization, and evaluates technology advancements aimed at optimizing the existing Food Supply Chain. Design/Methodology – The systematic literature review analyzed 324 documents indexed in Scopus, Web of Science, and Google Scholar. The review covers peer- reviewed articles, published between 2015 to 2024. Selecting these sources helps to understand diverse challenges in the industry and a reasonable timeframe helps in capturing the evolution and recent advancements. The selection criteria include relevance to the Big Data applications, industry challenges, and technical advancements where the keywords are related to Big Data and Food Supply Chain (FSC) that guided the research and then were screened for quality and relevance. Data extraction focused on key themes such as technologies used, benefits observed, and challenges identified. The goal was to capture a holistic view of the research landscape and identify gaps and future opportunities. Findings – The review highlights increased scholarly attention on Big Data in FSCM, using technologies such as Data analytics, Machine Learning, Artificial Intelligence, Blockchain, Internet of Things (IoT), and Smart Agriculture to improve traceability, efficiency, and sustainability. The identified gaps include regional concentration of studies and limited adoption of technologies by Small and Medium Enterprises (SMEs). The study addresses these gaps and provides guidance to apply new technology, minimize food wastage and improve food quality at each stage of the Food Supply Chain process. Practical implications – This research underscores the disparity in the adoption of these technologies between large and SMEs, particularly due to resources constraints. Large firms typically have better access to the expertise and infrastructure necessary for deploying Big Data solutions effectively. Despite these limitations, the review identified the current gap and offered actionable recommendations for implementing effective Big Data strategies in the industry. Social Implications – The focus of studies to specific countries/regions limits the analysis of the global Food Supply Chain due to restrictions to fully capture the challenges and opportunities in developing regions and their applicability to diverse socioeconomic contexts. However, understanding Big Data adoption in the (Food Supply Chain) FSC Management, will contribute in significant reductions in food wastage. This can support farmers to grow crops and improve export accessibility in global regions. Originality/value – This study reviews existing literature on Big Data applications in the Food Supply Chain. It identifies benefits, challenges, implementation frameworks and future research opportunities. Its unique contribution lies in highlighting gaps, such as selection of tools and techniques for using Big Data and managing food wastage by applying these tools at each phase of the supply chain. Future research should address these gaps by exploring inclusive strategies for technology adoption in SMEs and conducting globally representative studies. This review serves as a valuable resource for both academics and practitioners, guiding future research and implementation efforts for an efficient FSCM.