Chiu C.-H.TSAN MING CHOI2022-05-302022-05-302016https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877591275&doi=10.1007%2fs10479-013-1386-4&partnerID=40&md5=de0f5cd1305679ffbd209fea8d47d547https://scholars.lib.ntu.edu.tw/handle/123456789/612278Pioneered 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. ? 2013, Springer Science+Business Media New York.Mean-variance analysis; Review; Supply chain managementjournal article10.1007/s10479-013-1386-42-s2.0-84877591275