The optimal number of suppliers considering the costs of individual supplier failures
This paper utilizes the decision tree approach to determine the optimal number of suppliers in the presence of supplier failure risks. Previous proposed models have considered only two states of nature: all suppliers fail to deliver and not all suppliers fail to deliver. In practice, however, there is clearly a partial loss associated with the failure of any individual supplier. We present models that allow a more realistic decision-making process by taking into consideration the independent risks of individual supplier failures when the probability of failure for each of the suppliers is equal as well as the case where the probability of failure from each of the suppliers is not equal. We also consider various levels of supplier failure probability and possible procurement or operating cost savings gained from using less reliable suppliers. The results indicate that when suppliers are highly reliable, sole sourcing is the lowest cost approach under all experimental conditions. However, as the suppliers become less reliable, additional suppliers may be required to obtain the lowest cost. Finally, it was shown that only in the extreme conditions of unreliable suppliers, high loss to operational cost per supplier, and low ability to mitigate the failure from a partial set of suppliers, having a large number of suppliers is an effective strategy.
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Volume (Year): 35 (2007)
Issue (Month): 1 (February)
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- Berger, Paul D. & Gerstenfeld, Arthur & Zeng, Amy Z., 2004. "How many suppliers are best? A decision-analysis approach," Omega, Elsevier, vol. 32(1), pages 9-15, February.
- Crama, Y. & Pascual J., R. & Torres, A., 2004. "Optimal procurement decisions in the presence of total quantity discounts and alternative product recipes," European Journal of Operational Research, Elsevier, vol. 159(2), pages 364-378, December.
- Lee, Hau L. & Whang, Seungjin, 2005. "Higher supply chain security with lower cost: Lessons from total quality management," International Journal of Production Economics, Elsevier, vol. 96(3), pages 289-300, June.
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