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The effect of supply-chain disruption, quality and knowledge transfer on firm strategy

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  • Clemons, Rebecca
  • Slotnick, Susan A.

Abstract

We investigate the effect of supply-chain disruption on a firm's decisions to invest in quality, and on ordering decisions, when there is a variable rate of knowledge transfer and a choice between two suppliers. The current supplier produces components with acceptable quality, but deliveries are subject to random disruptions. The new supplier is not subject to disruption, but has a lower initial level of quality. Our analysis shows that supply chain disruption can be costly, but its effect can be mitigated by policies that sensibly allocate demand between two suppliers. When an alternative source of supply is desirable, a firm must consider the quality level of the supplier when choosing supplier development policies. We also find that the effectiveness of knowledge transfer between a firm and a supplier has a significant impact on profit and should be considered before implementing supplier development activities. This is the first paper to consider joint decision-making about order allocation and quality improvement investments, in the face of supply-chain disruption, when the effectiveness of investment is influenced by a variable rate of knowledge transfer.

Suggested Citation

  • Clemons, Rebecca & Slotnick, Susan A., 2016. "The effect of supply-chain disruption, quality and knowledge transfer on firm strategy," International Journal of Production Economics, Elsevier, vol. 178(C), pages 169-186.
  • Handle: RePEc:eee:proeco:v:178:y:2016:i:c:p:169-186
    DOI: 10.1016/j.ijpe.2016.05.012
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    References listed on IDEAS

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    2. Tse, Ying Kei & Zhang, Minhao & Zeng, Wenjuan & Ma, Jie, 2021. "Perception of supply chain quality risk: Understanding the moderation role of supply market thinness," Journal of Business Research, Elsevier, vol. 122(C), pages 822-834.
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    5. Svoboda, Josef & Minner, Stefan & Yao, Man, 2021. "Typology and literature review on multiple supplier inventory control models," European Journal of Operational Research, Elsevier, vol. 293(1), pages 1-23.

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