Zhongzheng Liu, Feng Chu, Feifeng Zheng, Chengbin Chu, Ming Liu
Dual-channel supply chain (DC-SC), which integrates both traditional offline and online channels, has significantly improved its performance. However, the increasing frequency of disruptions in DC-SCs, compounded by ripple effects, poses severe challenges to SC resilience. In response, one manufacturer has recently adopted exclusive stores in offline channels, which is operated solely by the manufacturer to sell its own products. There is no literature dedicated to DC-SC resilience that considers exclusive stores under ripple effects. Thus, we study a novel DC-SC resilience building problem with exclusive stores under ripple effects. The problem consists of (i) making pricing decisions, and (ii) planning on inventory redundancy, production and distribution. A conditional value-at-risk (CVaR)-oriented stochastic programming model with a dynamic Bayesian network (DBN)-based scenario set is established. Then, a novel scenario reduction (SR)-based method combined with probabilistic distance is designed. Numerical experiments indicate that the SR-based method guarantee solution quality relative to sample average approximation (SAA) benchmark while maintaining shorter running time, and the sensitivity analysis yields managerial insights.