Advertisement

Introduction

  • Jian Li
  • Jia Chen
  • Shouyang Wang
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 165)

Abstract

In recent years, the adopting of some supply chain practice such as outsourcing and lean production helps in smoothing the operations, but it also results in little buffer inventory in a supply chain which may lead to increased vulnerability of the chains.1 At the same time, the business environment has evolved to be an increasingly complex scenario characterized by high uncertainty and rapid and frequent changes. For example, supply chains are subject to many potential external sources of disruption, e.g., natural disasters, terrorist attacks, and industrial actions, etc. The disruption in one firm can rapidly result in a significant adversary impact on the entire chain. Due to such changes, firm managers not only concern profit maximization but also pay much attention to risk containment or loss minimization for their firms. Motivated by the requirements of real world practice, supply chain risk management attracts more and more attention from academia (Chen et al. 2007; Shi 2004; Tang 2006a;Wu and Wang 2004a,b;Wu et al. 2006a; Zhou et al. 2006).

Keywords

Supply Chain Supply Chain Coordination Supply Chain Model Disruption Management Newsvendor Problem 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of Economics and ManagementBeijing University of Chemical Technology (BUCT)BeijingChina, People’s Republic
  2. 2.Personal Banking DepartmentBank of ChinaBeijingChina, People’s Republic
  3. 3.Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina, People’s Republic

Personalised recommendations