Mean-variance analysis of sourcing decision under disruption risk

This study considers a mean-variance (MV) framework for managing disruption risk in a two-echelon supply chain with a risk-averse buyer and multiple unreliable suppliers under newsvendor (NV) setting. An MV objective function is designed to maximize the buyer's expected profit while minimizing its variance. Study of the structural property of the problem proves the existence of a global maxima and a set of efficient portfolios consisting of dominating mean-variance pairs. We demonstrate the effect of model parameters through comparative statics analysis. An algorithm is developed to overcome the computational complexity of the higher dimensional problem. Numerical studies on model behavior show that the proposed algorithm gives the exact optimal solution while being tractable.

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