4.5 Article

Disaster resilient proactive and reactive procurement models for humanitarian supply chain

期刊

PRODUCTION PLANNING & CONTROL
卷 33, 期 6-7, 页码 576-589

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/09537287.2020.1834124

关键词

Humanitarian supply chain; disaster; resilience; procurement; reactive; proactive; cost analysis; mathematical models

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Global supply chains are vulnerable to disruptions caused by disasters, making it necessary for businesses to design resilient supply chains. This paper proposes a disaster resilient procurement framework, which includes a proactive supplier selection process and mathematical models for both proactive and reactive situations.
Global and complex supply chains are being increasingly exposed to the disruptions caused by disasters occurring in any part of the world. As a result, the business firms are facing a challenge to design resilient supply chains which could avoid or at least minimise the effect of disruptions caused by natural or manmade disasters. Procurement being one of the initial supply chain activity ensures undisrupted supply of raw material. In global business operations, especially in global sourcing, any disaster is likely to effect the entire supply chain. Therefore, the procurement planning of a business organisation must consider the disaster resilience aspect. The paper proposes disaster resilient procurement framework. The framework involves resilient supplier selection process as a proactive approach to disaster resilient supply chain. The paper also proposes two mathematical models for disaster resilient procurement for both proactive and reactive situations. In proactive situation, the model preferably allocates orders to disaster resilient suppliers. However, in disruptions, the proposed reactive model considers disruptions and reallocate orders to minimise penalties incurred on any shortages. Hence, the proposed framework aims to achieve operational excellence by minimising the risk/effect of disruptions and cost at the same time which is also demonstrated using different case scenarios.

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