Li Shanshan, He Yong, Zhou Li
School of Finance, Nanjing Audit University, Nanjing, 211815 China.
School of Economics and Management, Southeast University, Nanjing, 210096 China.
Complex Intell Systems. 2022;8(6):4543-4555. doi: 10.1007/s40747-021-00520-9. Epub 2021 Sep 15.
This paper considers a make-to-order system where production gets disrupted due to a random supply failure. To avoid potential stock-out risk and responding price increase during disruption, customers might decide to stockpile extra units for future consumption. We investigate the contingent sourcing strategy for the manufacturer to cope with the disruption. To this end, we first discuss the optimal post-disruption stockpiling decision for customers. In view of expected disruption duration, price rise, and inventory holding cost, three types of stockpiling behavior are analytically provided for the customers: non-stockpiling, gradual stockpiling, and instantaneous stockpiling. Next, a model is formulated to optimize the joint decision of contingent sourcing time and quantity, with the objective of maximizing profit expectation. Finally, by conducting numerical analysis, we generate further insights into the role of relative factors and provide specific managerial suggestions on how to adapt dynamic contingent sourcing strategies to alleviate different disruptions, under different market environments and customer behaviors.
本文考虑一个按订单生产的系统，在该系统中，生产会因随机供应故障而中断。为避免中断期间潜在的缺货风险和应对价格上涨，客户可能会决定储备额外的产品以供未来消费。我们研究制造商应对中断的应急采购策略。为此，我们首先讨论客户中断后的最优囤货决策。考虑到预期中断持续时间、价格上涨和库存持有成本，从分析角度为客户提供了三种囤货行为：不囤货、逐步囤货和即时囤货。接下来，构建一个模型以优化应急采购时间和数量的联合决策，目标是使利润期望最大化。最后，通过进行数值分析，我们进一步深入了解相关因素的作用，并针对如何在不同市场环境和客户行为下采用动态应急采购策略以缓解不同中断提供具体的管理建议。
