Hau L. Lee

Information distortion and incentive misalignment often undermine supply chain performance. In response, many firms adopt a “control tower” approach, whereby one party assumes responsibility for replenishment decisions across the supply chain. Industry examples showed that this role may be assigned to the customer, Customer-Managed Inventory (CMI), or to the supplier, Supplier-Managed Inventory (SMI). This paper investigates when one governance structure is preferable. We study a two-echelon, one-to-many supply chain consisting of a single supplier and a customer operating multiple warehouses. We characterize optimal base-stock policies and equilibrium holding-cost-sharing parameters under CMI and SMI and benchmark them against decentralized operations and a fully centralized system. Two primary forces shape the choice between CMI and SMI: the relative shortage penalty costs of the two parties and the structure of the customer’s distribution network. Specifically, CMI is preferred when the customer faces relatively higher shortage penalties and operates in a more asymmetric environment—for example, when demand is concentrated in a subset of its warehouses or when replenishment lead times vary substantially across these locations. In contrast, SMI is favored under opposite conditions. We further examine how intertemporal and interspatial demand correlations affect this comparison. A key finding is that, although neither CMI nor SMI achieves the first-best outcome, their efficiency loss relative to full centralization is typically small. Calibrated numerical studies based on four industry cases disentangle the incremental value of information sharing, decision-right transfer, and cost sharing, showing that most performance gains stem from decision-right transfer supported by appropriate holding-cost sharing. This paper was accepted by Jayashankar Swaminathan, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.02137 .

The recent elimination of the United States de minimis exemption for import tariffs has been reported to have a significant impact on ultra-fresh fashion companies such as Shein and Temu. This article develops a game-theoretic model to investigate the impact of such tariffs. Specifically, we consider a model for a global ultra-fresh fashion supply chain with economies of scale under tariff hikes. Our model analysis reveals the following main insights. First, the ultra-fresh fashion firm would price in such a way to pass the entire import tariff onto customers in the tariff-imposing market, and tariff hikes in one market would reduce the firm’s product launch frequency and total product variety in all markets due to the supply chain scale economy effect. As a result, tariff hikes reduce the firm’s profit, with the loss amplified under greater supply chain scale economies. However, a higher demand from outside the tariff-imposing market helps soften the blow from tariff hikes, signifying the importance of the demand-side market diversification (a strategy termed as the “US Plus One” in this article). Moreover, we find that the firm would relocate its production for the tariff-imposing market if and only if the tariff rate exceeds a certain threshold, with supply chain scale economies serving as an “efficiency barrier” to counter-balance the supply-side production diversification. We also find numerically that the demand-side market diversification strategy can serve as a potential substitute for the supply-side production diversification strategy. Implications of tariff hikes for consumer surplus and the environment are further examined along with production relocation. Finally, we offer a general discussion regarding market competition and other relevant modeling considerations.

Using agile supply chains, fast fashion companies have been viewed as best practice examples in industries. Prior research focuses on how agility can equip such companies with strong sense-and-respond capabilities to identify and fulfill unpredictable customer demands. There is another powerful dimension of agility—the ability to create new products frequently—that has enabled recent market success of companies such as Shein and Temu, labeled by some industry press as ultra-fast fashion. These companies, relying on end-to-end digital technologies, have pushed this dimension of agility to unprecedentedly high levels, launching new products with great frequency and variety. The frequent product launches create freshness, stimulating latent demands of consumers and making these companies “ultra-fresh” fashion, a term we adopt in this paper. We seek to model this dimension of agility as an operational strategy for demand creation. Our model enables us to explore the effects through the lens of profit to the firm, consumer surplus, and environmental impact. Our analysis reveals that frequent product launches, high variety, and low prices—the three salient features of ultra-fresh fashion—are driven by both the product design agility and the customers’ interest for product freshness. The ultra-fresh strategy allows steady profit increase for the firm and benefits consumers in aggregate but may cause negative environmental impact if left unchecked. This paper was accepted by Jay Swaminathan, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06249 .

In recent years, there has been an increasing trend in supply chains to employ a “control tower” approach to improve supply chain performance. One such strategy is customer-managed inventory (CMI) in which the customer (the downstream party) controls the inventory of the supplier (the upstream party). However, the optimal design of the inventory control policy and the required incentive structure for CMI has not been fully explored in the related literature. In this paper, we develop a two-echelon model consisting of a supplier and a customer that captures the interaction between both decision makers. Analysis of this model indicates that achieving the potential benefits of CMI requires suitable incentive mechanisms to be put in place. The two-echelon inventory system model, however, does not give closed-form solutions, which are required to generate an optimal solution to the inventory control and incentive problem. To address this challenge, we propose an approximate model, which decouples the two-echelon model into two newsvendor-type models with each party operating a single-echelon system. This approximate model requires the introduction of additional cost parameters so that the decoupled model captures the cost implications of supplier shortages in the original two-echelon model. By developing appropriate values for these cost parameters, the approximate model yields near optimal results. Analysis of the solution reveals important operational factors that determine which environments are conducive for CMI and conditions for Pareto improvement of all stakeholders. This paper was accepted by Jayashankar Swaminathan, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.03658 .

JD.com utilizes advanced analytical techniques to strengthen its supply chain capability. The end-to-end inventory management model, intelligent risk management system and consumer-to-manufacturer system are implemented to attain agility, resilience and shared value. These efforts have led to significant revenue increases, cost savings, and value creation across the retail ecosystem, benefiting consumers and business partners.