Risk analysis is crucial in stochastic supply chain models. Over the past few years, research has accelerated in exploring risk analysis issues in supply chain management problems, while most recent papers focus on conceptual frameworks or computational numerical analysis. Pioneered by Nobel laureate Markowitz in the 1950s, the mean-risk (MR) formulation became a fundamental theory for risk management in finance. Despite the significance and popularity of MR-related approaches in finance, their applications in studying multi-echelon supply chain management problems have only been seriously explored in recent years. While the MR approach has already been shown to be useful in conducting risk analysis in stochastic supply chain models, there is no comprehensive reference source that provides the state-of-the-art findings on this important model for supply chain.