Multiplicity in Product Expiration Dates and Food Waste in Grocery Retail Stores
研究了杂货店中同一产品多个过期日期并存时导致的过期浪费，提出了量化其占比的方法，发现平均占过期浪费的25%-52%。
Problem definition: A grocery retailer incurs expiration waste (EW) at its store when a perishable product crosses its expiration date without being sold. One frequent scenario accounting for EW occurs when units of a given product with multiple expiration dates are simultaneously available on store shelves. In such situations, a consumer is likely to purchase a later-to-expire unit, which in turn increases the likelihood of EW of a sooner-to-expire unit. To mitigate the occurrence of such multiple-dates-led expiration waste (MDEW), retailers undertake a variety of interventions, including a price markdown of sooner-to-expire units and in-store inventory rotation. Most retailers, however, are often unaware of the extent of MDEW in their stores and thus are constrained in mitigating its occurrence. Methodology/results: We provide the first large-scale evidence of the MDEW share of EW. We collaborate with a grocery retailer to compile a multicategory-multistore data set ([Formula: see text]15.3 million sales transactions) on grocery products with 3–14 days of shelf life. Across these products, at the product-store-week level, EW as a percentage of sales is 23% on average. To quantify MDEW’s share, we propose a novel and easy to implement methodology for computing its lower and upper bounds. In our retailer’s context, the MDEW’s lower and upper bounds equal 25% and 52% on average of the generated EW, respectively. Managerial implications: Our study highlights MDEW’s material share in generating EW; thus, it provides a solid premise for future in-depth academic investigation on MDEW management. Furthermore, for practitioners, it provides an immediately actionable methodology to measure MDEW in their store operations. Empowered with such a measurement ability, retailers can better plan their EW waste management interventions. Funding: The authors gratefully acknowledge financial support. A. Kabra received support from the University of Maryland, College Park and the Nanyang Technological University Business School [Start Up Grant 025540-00001]. V. Karamshetty received support from the National University of Singapore School of Computing [Seed Fund A-8003889-00-00]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.0607 .