Work

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

Year: 2025

Type: article

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.

Source: Sustainability

DOI: 10.3390/su17209242

Authors: Richard Li, Rosemary Seva, Anthony Chiu

Institution: De La Salle University

Language: English

Topic: Supply Chain and Inventory Management

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Responsible consumption and production

Open Access status: gold

Estimated APC paid: $2,896