Leveraging food supply chain structure and technologies to reduce food loss and waste

Abstract

Food loss and waste (FLW) is an environmental, economic, and ethical challenge of global proportion, yet very little research has been conducted into FLW reduction in Finnish food-service operations such as student restaurants and small commercial restaurants. This thesis provides insights about how the design and structure of food supply chains, combined with digital technologies, may contribute to the reduction of FLW in these contexts. Two key questions are described that are (1) how the design and structure of the food supply chain structure prevent food loss and waste (FLW) reduction at different stages, and (2) how AI, big data analytics, IoT, and other digital means are used, or could be used, to monitor and reduce FLW. This research uses a qualitative and interpretive approach. Further, data was gathered through six written semi-structured interviews with food-service employees in various positions, including manager, supervisor, kitchen helper, and restaurant worker. The interviews were analysed using thematic analysis supported by NVivo software for identifying patterns across the interviews.

The findings indicate that FLW is shaped both by structural and operational factors. Demand uncertainty, procurement practices, delivery frequency, and storage constraints create conditions where food is put at risk of being wasted. Everyday routines, such as stock rotation, batch cooking, menu planning, and the handling of leftovers, determine how much of that risk becomes actual waste. Customer plate waste remains a visible problem, especially in buffet-type environments. The study shows that digitalization is uneven: while a few units make use of tools, including waste-tracking systems and basic inventory or temperature-monitoring software, others rely entirely on manual practices. Across all cases, participants perceive strong potential for AI-based demand forecasting, digital inventory and expiry tracking, and IoT-based temperature and waste monitoring in support of more accurate planning, real-time control, and learning. This thesis contributes to an improved understanding of FLW in Finnish food-service operations by combining supply chain structure, daily practices, and digital capabilities. It also provides practical recommendations for managers and policymakers who seek to reduce FLW in line with circular economy and sustainability goals.