Abstract
Effective supply chain risk management (Hallikas et al. 2002; Harland et al. 2003; Henke et al. 2006) requires the identification, assessment and monetization of risks and disruptions, as well as the determination of the probability of their occurrence and the development of alternative action plans in case of disruptions (cf. Zsidisin 2003; Zsidisin et al. 2004; Zsidisin et al. 2000; Vidal a. Goetschalckx, 2000). Companies traditionally use multiple sources for material procurement and/or hold safety stocks to avoid vulnerability. However, these strategies can negatively impact the supply chain performance, leading to higher purchase and logistics costs. The aim of this chapter is to illustrate how the implementation of the supply chain risk management concept can be improved by using a neural network approach.
Keywords
- Supply Chain
- Hide Layer
- Supply Chain Management
- Supply Network
- Neural Network Approach
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Teuteberg, F. (2008). Supply Chain Risk Management: A Neural Network Approach. In: Ijioui, R., Emmerich, H., Ceyp, M. (eds) Strategies and Tactics in Supply Chain Event Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73766-7_7
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DOI: https://doi.org/10.1007/978-3-540-73766-7_7
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