Reducing Waste in Retail: A Mixed Strategy, Cost Optimization Model for Sustainable Dead Stock Management

Richard Li (), Rosemary Seva and Anthony Chiu
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Richard Li: Department of Industrial and Systems Engineering, De La Salle University, Manila 1004, Philippines
Rosemary Seva: Department of Industrial and Systems Engineering, De La Salle University, Manila 1004, Philippines
Anthony Chiu: Department of Industrial and Systems Engineering, De La Salle University, Manila 1004, Philippines

Sustainability, 2025, vol. 17, issue 20, 1-45

Abstract: The retail sector is the most demand-sensitive echelon in the supply chain, where non-moving items accumulate and become dead stock. Existing inventory management studies focus on fast-moving products and income generation. This paper focuses on dead stock management and proposes a mixed strategy solution using a pure integer non-linear programming model that minimizes the dead stock management cost of a retail chain operator. The number of products and volume of product-related data in a retail chain system require big data analysis to ensure sustainable inventory practices that reduce waste generated from dead stock inventory. Through hypothetical data sets, the 3-store, 10-product run showed that discount percentage, expected sales success probability of a product in a store location, and disposition of unsold products were the main drivers of the decisions made by the model. The most significant cost contributors arising from these decisions were the unrecovered product cost (UPC), disposed product cost (PC), and salvage value from the successful sale of dead stock. Inventory managers must balance the effect on these cost components when they choose the strategies to use in managing dead stock.

Keywords: dead stock; dead stock management; inventory management; mixed strategy approach; single strategy approach; sustainable practices (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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