1 A Simulation Model for Sensor-based Management of Perishable Goods

Our study is based on a research project with a major Swiss retailer. We use the example of strawberries in Switzerland to investigate the value of sensor information for profit increase and carbon footprint reduction in retail supply chains. The simulation parameters have been elicited in several discussions and were validated with industry experts. The Swiss consume approximately 16,500t of strawberries per year. As the domestic crop yield is only able to satisfy a demand of 5,500t and due to seasonality of the product, the resulting gap of 66 percent needs to be filled by imports from neighbor and other countries. Suppliers and distribution routes change frequently and therefore quality drops are likely to occur between the supplier to retailer link. While strawberries are famous to consumers for their delicious taste, retailers perceive them as a difficult product class with high loss rates. Sensors can be used to reduce these high loss rates by tracking the fluctuations in environmental parameters on a case level. In this context, the order of which items are depleted from stock or shelf, defined by the so-called issuing policy, is important to minimize the number of perished items. Studies show that the use of a sensor based First-Expire-First-Out (FEFO) issuing policy can increase a retailer’s profit tremendously [1, 2]. However, the use of sensors in a supply chain introduces not only additional costs, but also additional emissions required for manufacturing