Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7998
Title: Supply chain risk analysis with mean-variance models : a technical review
Authors: Chiu, CH
Choi, TM 
Keywords: Mean-variance analysis
Review
Supply chain management
Issue Date: 2013
Publisher: Springer
Source: Annals of operations research, 2013, p. 1-19 How to cite?
Journal: Annals of operations research 
Abstract: Pioneered by Nobel laureate Harry Markowitz in the 1950s, the mean-variance (MV) formulation is a fundamental theory for risk management in finance. Over the past decades, there is a growing popularity of applying this ground breaking theory in analyzing stochastic supply chain management problems. Nowadays, there is no doubt that the mean-variance (MV) theory is a well-proven approach for conducting risk analysis in stochastic supply chain operational models. In view of the growing importance of MV approach in supply chain management, we review a selection of related papers in the literature that focus on MV analytical models. By classifying the literature into three major areas, namely, single-echelon problems, multi-echelon supply chain problems, and supply chain problems with information updating, we derive insights into the current state of knowledge in each area and identify some associated challenges with a discussion of some specific models. We also suggest future research directions on topics such as information asymmetry, supply networks, and boundedly rational agents, etc. In conclusion, this paper provides up-to-date information which helps both academicians and practitioners to better understand the development of MV models for supply chain risk analysis.
URI: http://hdl.handle.net/10397/7998
ISSN: 0254-5330
EISSN: 1572-9338
DOI: 10.1007/s10479-013-1386-4
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