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Preparedness with a system integrating inventory, capacity, and capability for future pandemics and other disasters
Production and Operations Management ; 2022.
Article in English | Web of Science | ID: covidwho-2088311
ABSTRACT
The chaotic response of the US Strategic National Stockpile to COVID-19 during 2020 highlighted the inadequacy of the inventory-based approaches to disaster response. This paper examines the integration of stockpile inventory, backup capacity, and standby capability to meet the disaster-related surge in demand in the future. We present a two-period model of such an integrated system for consumable items with uncertain demand that follows a general probability distribution. Our model incorporates standby capability in period 1 that can be converted to additional capacity for use in period 2, with the conversion yield being deterministic or stochastic. Our main results are (1) Adding capacity in addition to inventory is beneficial only when the capacity reservation-related costs are relatively lower than the inventory-related costs. In this case, adding capacity will decrease the inventory needed in both periods, the shortfall probability, and the total expected cost. (2) Adding capability in period 1 is cost-effective only when the ratio of capability-development cost to conversion yield is lower than the capacity reservation cost. In this case, investing in capability results in less inventory and less reserved capacity in period 2. (3) Higher uncertainty in capability conversion yield reduces the attraction of developing capability in period 1. Consequently, less capability would be developed in period 1, while more inventory and capacity would be needed in period 2 in the face of a higher shortfall probability.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Production and Operations Management Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Production and Operations Management Year: 2022 Document Type: Article