Supply chain risk management: A neural network approach

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. © 2008 Springer-Verlag Berlin Heidelberg.