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Supply Chain Risk Management

Authors: Thomas Yew Sing Lee;

Supply Chain Risk Management

Abstract

The existing models utilise a mean value approach with deterministic failure cost to determine the optimal number of suppliers in the presence of supplier failure risks. The mean value approach assumes, the firm has a linear utility function with respect to the supply disruptions. For major disruptions that could threaten the survival of the firm, the linearity assumption is questionable. Furthermore, the operating cost of working with the suppliers and the financial loss cause by failure of suppliers are subject to uncertainty. This article utilises the mean-variance approach to determine the optimal set of suppliers in the presence of supplier failure risks. The importance of cash-flow variability in the supplier selection/planning process is considered explicitly. Our methodology allows us to balance the two desirable, but conflicting objectives of cost minimisation and service levels achieved. Furthermore, traditional risk management tools like insurance are incorporate into the optimal suppliers' selection process.

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    popularity
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    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Average
Top 10%
Top 10%
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