Incentivizing resilient supply chain design to prevent drug shortages: policy analysis using two- and multi-stage stochastic programs

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Abstract

Supply chain disruptions have caused hundreds of shortages of medically-necessary drugs since 2011. Once a disruption occurs, the industry is limited in its ability to adapt, and improving strategic resiliency decisions is important to preventing future shortages. Yet, many shortages have been of low-margin, generic injectable drugs, and it is an open question whether resiliency is optimal. It is also unknown what policies would be effective at inducing companies to be resilient. To study these questions, we develop new supply chain design models that consider disruptions and recovery over time. The first model is a two-stage stochastic program which selects the configuration of suppliers, plants, and lines. The second is a multi-stage stochastic program which selects the configuration and target safety stock level. We then overlay incentives and regulations to change the market conditions and evaluate their effects on two generic oncology drug supply chains. We find that profit-maximizing firms may maintain vulnerable supply chains without intervention. Shortages may be reduced with: moderate failure-to-supply penalties; mandatory supply chain redundancy; substantial amounts of inventory; and/or large price increases. We compare policies by evaluating the societal costs to reduce the expected shortages to 2% and 5% of demand.

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Tucker, E. L., Daskin, M. S., Sweet, B. V., & Hopp, W. J. (2020). Incentivizing resilient supply chain design to prevent drug shortages: policy analysis using two- and multi-stage stochastic programs. IISE Transactions, 52(4), 394–412. https://doi.org/10.1080/24725854.2019.1646441

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