Policies adoption for supply disruption mitigation based on customer segmentation

Qinglu Gao, De Xia, Yangyan Shi, Ji Quan

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Supply chain disruptions resulted from various disasters may cause awesome loss; therefore, corresponding operational policies should be designed to mitigate the negative effect. In industrial goods supply chain, customers are segmented and have different contributions and significances to manufacturers, which have to be considered when adopting mitigation policies. From the customer heterogeneity perspective, the models of a three-stage supply chain with a single supplier and two suppliers are established, and sensitivity analysis is carried out to investigate scenario parameters' impact on optimal mitigation policies. The numerical experiments find that safety stocks are suitable for low disruption probability situation. Meanwhile, strategic reserves with lower holding cost are attractive and efficient to handle a fairly highly disruptive situation or high key customer loss. The results also indicate backup supplier should be adopted if there is a low disruption probability or the backup supplier's price is not significantly higher. This paper extends the supply disruption research and leads some managerial implications and insights that might be useful for disruption mitigation in industrial goods supply chain.

LanguageEnglish
Article number8676219
Pages47329-47338
Number of pages10
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019

Keywords

  • Supply disruption
  • mitigation policies
  • customer segmentation
  • strategic reserves
  • backup supplier

Cite this

Gao, Qinglu ; Xia, De ; Shi, Yangyan ; Quan, Ji. / Policies adoption for supply disruption mitigation based on customer segmentation. In: IEEE Access. 2019 ; Vol. 7. pp. 47329-47338.
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Policies adoption for supply disruption mitigation based on customer segmentation. / Gao, Qinglu; Xia, De; Shi, Yangyan; Quan, Ji.

In: IEEE Access, Vol. 7, 8676219, 2019, p. 47329-47338.

Research output: Contribution to journalArticleResearchpeer-review

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