Dynamic expiration date-based discounting of fresh food products
Year: 2025
Type: article
Abstract: Many supermarkets discount food products that are close to the expiration date. In practice, this is done either by discount labels put on the product or by electronic shelf labels showing the price per expiration date. In this study, we derive by stochastic dynamic programming (SDP) optimal dynamic discount policies for a profit-maximizing retailer who sells a product with m periods (e.g., days) shelf life. We compare various discounting strategies, such as static last-day discounting, optimal dynamic last-day, and last-2-days discounting, against the no-discounting strategy.The model allows products of different expiration dates to be in stock simultaneously, as replenishment happens every period. In the last-day discounting policies, two selling prices may co-exist, in the last-2-days discounting policy three selling prices may co-exist. Demand and product withdrawal depend on both price and freshness. Consumers are divided into FEFO and LEFO consumers. FEFO consumers pick the oldest items first. LEFO consumer tend to take the freshest items available. In case discounted items are available a fraction of the LEFO consumer will pick these if the discount is large enough. Demand increases as long as discounted products are available. Numerical findings by simulation provide valuable insights into the impact of discounting on profit, waste, and fill rate. Various key factors, including shelf life, consumer picking behavior, inventory policy, discount sensitivity, price elasticity, and consumer demand, are analyzed. Static last-day discounting reduces food waste but often results in (much) lower profit. Dynamic discounting maintains, or improves, profit and reduces food waste. The highest profit level is achieved with last-2-days discounting. Averaged over 18 experiments, this policy demonstrates a 7.9% increase in profits and a 3.6% decrease in waste relative to no discounting. The effectiveness of discounting policies depend strongly on the consumer picking behavior and demand elasticity.
Institutions: Wageningen University & Research, Tilburg University
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,420
OpenAlex ID: W4415340568