• supply chain risk;
  • risk mitigation strategies;
  • simulation;
  • data envelopment analysis;
  • nonparametric statistical methods

Mitigating supply chain risk is a critical component of a company's overall risk management strategy. Drawing upon Contingency Theory, we posit that the appropriateness and effectiveness of risk mitigation strategies are contingent on the internal and external environments and that there is no one-size-fits-all strategy. While literature on risk management has proposed a variety of tools and techniques for effectively evaluating and managing supply chain risks, comprehensive assessment of the efficiencies of alternative risk mitigation strategies has not been addressed in the literature. Such an assessment will help managers select the appropriate mitigation strategy for a given decision-making environment. To this end, this study is first of its kind in evaluating and proposing efficient supply chain risk mitigation strategies in the presence of a variety of risk categories, risk sources, and supply chain configurations. We combine an empirically grounded simulation methodology with data envelopment analysis and nonparametric statistical methods to analyze and rank alternative mitigation strategies. We find that the more efficient strategies focus on flexibility rather than on redundancy for supply chain failures. Our research presents several interesting and useful managerial insights for deciding what strategies are most capable of mitigating risks in a variety of contexts.