This paper aims to investigate the uncertainty factors that impact the collection strategy of a remanufacturing closed-loop supply chain. The basis of this type of supply chain is the collection of used products, without which the remanufacturing of new products would be out of the question. In this paper, we considered the effect of stochastic disturbance on the collection process in a closed-loop supply chain consisting of a manufacturer and a retailer, in which the manufacturer is responsible for collecting the used products. Considering stochastic disturbance, in this research, we proposed a stochastic collection model, and derived the feedback control strategies for both the manufacturer and retailer. Next, we investigated the evolutionary path and probability distribution of the stochastic return rate. Finally, we proposed a contract to coordinate the decentralized closed-loop supply chain. The results showed that the manufacturer would improve the level of return effort as the intensity of stochastic disturbance increases. However, the disturbance would not affect the pricing strategies of the supply chain members. As a result of the stochastic disturbance, the return rate always hovered around the expected return rate, while the expectation and variance of the return rate remained stable from a long-term perspective. The expected value and variance of the return rate could decrease or increase with time, depending on the value of the initial return rate of the system.

With the rapid development of the internet, many WEEE (Waste Electrical and Electronic Equipment) online recyclers have emerged and developed. They improve recycling efficiency significantly and bring hope for sustainable development. Unfortunately, few works in the literature are concerned about it, with many questions still unanswered. The WEEE online recyclers always face a challenge with regard to how to strategically design their reselling channel structure in fact. In this paper, we examined this challenge by two decision models: agency and self-run. We derived the performance of the self-run model and agency model by backward induction and then examined the desirability from different stakeholders’ perspective. The results suggested that WEEE online recyclers prefer the self-run model to the agency model when the unit recycling cost is low and a conflict exists between the WEEE online recycler and e-retailer for the resale channel preference. Interestingly, the manufacturer shows consistent resale channel preference with the WEEE online recycler when the unit recycling cost is low. Our further analysis revealed that all players can agree on the agency model in a certain case. In addition, we found that the consumer surplus and the recovery ratio in the self-run model are always better than that in the agency model. Our work provides insight into the promotion of the WEEE online recycling industry and into the resale channel selection for online recyclers. The study also generates managerial insights for environmental sustainability.