A hybrid approach for risk-informed decision-making in supply chain projects

Supply Chain Projects (SCPs) are essential ways to boost supply chain resilience. Making sound Risk Response Decisions (RRDs) for SCPs matters for business growth. However, SCPs are mainly managed in Project Portfolios (PPs). Decision Interdependency (DI) between projects and dependent uncertain events hinder determining risk response budgets and project success degree. Existing studies cannot effectively resolve them. Thus, this paper proposes a novel three-stage method. First, Monte Carlo Simulation (MCS) is applied to calculate the occurrence probabilities of scenarios formed by dependent uncertain events. In the second stage, considering the DI, the Stackelberg game is utilized to find the optimal risk response budget under each scenario. The final budget is determined by the conception of stratification theory. Third, a fuzzy RRD optimization model is constructed to select strategies within budgets. Finally, an illustrative case is given to prove the feasibility of the proposed method. Its advantages and reliability are validated by sensitivity and comparison analyses, which show: (1) optimal budgets exist; (2) the performance of the proposed method is better than the methods ignoring DI and dependent uncertain events; (3) the dependency of uncertain events affects RRDs; (4) focusing on DI can provide win–win situations for SCPs. This paper offers theoretical and managerial insights on RRDs.