Cost-Optimal Safety-Stock Levels for U.S. SME Importers under Tariff-Rate Volatility: A Distributionally Robust Optimization Approach - Chen, Xiangying (Economics and Management Innovation, 2025)
This study addresses the inventory management problem for U.S. small and medium-sized enterprises (SMEs) under U.S. import tariff policies. A distributionally robust optimization (DRO) approach is proposed to determine safety stock decisions. Considering that the tariff rate θ fluctuates within the interval the model aims to minimize the total cost, including tariff costs, inventory holding costs, and stockout costs, thereby establishing an (R, Q) inventory strategy framework. The study utilizes data from 3,400 HS-8 coded products in the 2018–2024 Section 301 tariff lists, complemented by a survey of 30 SMEs in New York and California. Numerical experiments indicate that the DRO method is more robust than stochastic programming (SP) in coping with tariff uncertainty, while being more flexible than robust optimization (RO), providing SMEs with actionable inventory decisions that balance cost and risk. The results also generate a downloadable "Tariff–Inventory Decision Table" for practical application and quantify the marginal impact of tariff uncertainty on SME cash flows, offering empirical evidence to inform policy making. This study provides both methodological and practical guidance for inventory management of SMEs under policy-induced uncertainty.