Improving the sustainability of a reverse supply chain system under demand uncertainty by using postponement strategies

In recent decades, issues of resource depletion and waste piling have grown at an alarming rate, which are happening in the cases of product wastes with significant residual values, such as e-waste. To address these issues, stakeholders have focused to develop a reverse supply chain (RSC) system that can sustain profitable takeback, reuse, and recycling operations in the long-term. Such a system requires efficiency in handling complex operations involving various players while being responsive to demand uncertainty and changes. One way in realizing these capabilities is by incorporating postponement concepts to the integrated RSC network, allowing the delay of operations susceptible to demand uncertainty. This study pioneers the formulation of a two-stage stochastic mixed-integer model of a multi-player RSC with speculation-postponement strategies. The sample average approximation method is used to solve and verify the proposed model that has an uncertain demand. Various speculation-postponement strategies, namely, disassembly, reconditioning, and reassembly strategies are developed to configure forecast and demand-driven RSC operations, including the purchasing, product takeback, production planning, inventory, and item speculation decisions. Numerical examples of the notebook computer RSC demonstrate that utilizing the right operation postponement can increase the network's flexibility, allowing better economic performances even under high demand uncertainty risks and stricter environmental regulations. In various cases, the RSC performs better with speculation-postponement strategies than without postponement strategy, demonstrating the proposed model's superiority. This study can provide insight to decision-makers to improve RSC sustainability through postponement. Moreover, the model is generic and can be applied to other products as well.