Too Good To Go: Combating Food Waste with Surprise Clearance

This paper studies surprise clearance as an innovative business model to increase store profit and reduce food waste. A store holding surprise clearance sells “surprise bags” composed of surplus food that would otherwise go to waste. At the time of ordering, consumers are uncertain about the quantity of food items included in a surprise bag. We model surprise clearance and compare it with both no clearance and transparent clearance, which sets a transparent unit clearance price based on the amount of surplus food after regular sales. We find that surprise clearance achieves the highest store profit and induces the most store production among the three selling schemes. Although both clearance schemes have the ability to eliminate store waste, the store effectively does so under surprise clearance but deliberately does not under transparent clearance. In fact, transparent clearance may generate even more store waste than no clearance. Further, both clearance schemes exacerbate the problem of consumer waste compared with no clearance, and despite zero store waste, surprise clearance generates the most consumer waste among the three schemes. If clearance sales target a consumer segment with a sufficiently low valuation of consumption, both clearance schemes reduce total waste, and surprise clearance is a win-win-win solution that maximizes store profit and social welfare and minimizes total waste among the three schemes. However, there are circumstances under which both clearance schemes fail to reduce total waste, and surprise clearance may generate the most total waste. This paper was accepted by Jeannette Song, operations management. Funding: L. Yang gratefully acknowledges financial support from the University of California Berkeley’s Spark Grant Award. The work of M. Yu was supported by the Hong Kong Research Grant Council [Grant 16502822] and the National Natural Science Foundation of China [Grant 72022023]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03001 .