An increasing number of manufacturers have started to pursue a strategy that promotes inventory sharing among the dealers in their distribution network. In this paper we analyze a decentralized dealer network in which each independent dealer is given the flexibility to share his inventory. We model inventory sharing as a multiple demand classes problem in which each dealer faces his own customer demand with high priority, and inventory-sharing requests from other dealers with low priority. Assuming that each dealer uses a base-stock and threshold-rationing policy for his inventory-stocking and inventory-sharing decisions, we explicitly model the interactions between the dealers through inventory sharing and obtain a closed-form cost function for each dealer based on the steady-state distribution of the inventory levels at the two dealers. We then provide a detailed supermodularity analysis of the inventory-sharing and inventory-rationing game in which each dealer has a two-dimensional strategy set (stocking level and rationing level). We show that the full-sharing game (in which dealers precommit to sharing all of their on-hand inventory) and the fixed-sharing-level game (in which dealers precommit to sharing a portion of their on-hand inventory) are supermodular, and thus a pure-strategy Nash equilibrium is guaranteed to exist. For the rationing game (in which dealers precommit to their stocking levels), we show that there exists a dominant strategy equilibrium on the dealers' sharing (rationing) levels. Finally, a comprehensive computational study is conducted to highlight the impact of the manufacturer's incentives, subsidies, and/or transshipment fees on the dealers' sharing behavior.inventory sharing and rationing, inventory competition, decentralized supply chains, noncooperative games

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Retail shopping establishments in the West have evolved through many different stages, in close association with Western lifestyles. The growth of supermarkets has been an important part of this trend, and in the 1980s, they were introduced in China. With their distinctive business environment, it is significant to study the success of the distribution technology transfer and how the Chinese consumers have received the Western shopping approach. This study examines supermarket shoppers in Beijing. The results provide an insight into the shopping patterns of Chinese consumers and identify potential problems for international retailers.

Drug shortages have been a major challenge facing the US pharmaceutical industry and government in recent years. Although the problem has drawn tremendous attention from the government and media, limited academic research has been devoted to this problem, and few solutions have been proposed based on rigorous research. This study addresses the drug shortage problem from a supply chain perspective, a key aspect missing in the literature, and proposes to mitigate shortages through drug purchase contracts. By modeling the drug supply chain, we capture the objectives of various supply chain parties, and investigate Pareto‐improving contracts that mitigate drug shortages, improve drug manufacturer's and group purchasing organization (GPO)'s profits, and cut government spending and healthcare providers’ costs. We explore structural properties of key supply chain decisions and the Pareto‐improving contracts, and conduct scenario analysis with realistic industry data to evaluate shortage mitigation solutions. Our analysis shows that increasing drug prices only, a solution advocated by many, is not very effective in shortage mitigation. Price increases must be paired with strengthened failure‐to‐supply clauses (called the IPS approach) to achieve consistent and significant shortage reduction as well as Pareto improvement. Across all scenarios tested, a 30% price increase under IPS can lead to a minimum, average, and maximum shortage reduction of 25%, 53%, and 70%, respectively. Our analysis also shows the impacts of IPS on different parties in the supply chain and the impacts of various model parameters on shortage mitigation. The IPS approach rewards reliability of drug supply, which is in line with the FDA's strategic plan to reward quality, but is easier to achieve in this regulation‐based industry. Interactions with the government and industry practitioners indicate that IPS also challenges the current mindset in pharmaceutical contracting.

Inventory sharing through transshipment has attracted a great deal of attention from researchers and practitioners due to its potential for increasing service levels while simultaneously decreasing stock levels. In this paper, we analyze the optimal production and transshipment policy for a two-location make-to-stock queueing system with exponential production and interarrival times. A key feature of our model is that we allow transshipments to be triggered by both demand arrivals and production completions. Thus, transshipment is used to achieve production flexibility through inventory reallocation, as well as to fill emergency demands. We also consider capacity issues in transshipment by modeling each location as a single-server, make-to-stock queueing system. In this setting, we prove that the optimal production policy for each location belongs to the “hedging point” family of policies, while the optimal demand filling policy belongs to the “state-dependent rationing” family of policies. We analyze the structural properties of the optimal policy and provide conditions under which the optimal policy can be simplified. Given the complex nature of the optimal policy, we develop three easy-to-implement heuristics that work very well for a large range of cost parameters.