Reverse channel selection in a dynamic stochastic closed-loop supply chain

This paper investigates reverse channel selection within a closed-loop supply chain, emphasizing the dynamic characteristics and potential stochastic disturbances inherent in the collection process. We construct three stochastic differential games to model scenarios where the manufacturer, retailer, and third-party each manage the collection of used products, deriving the corresponding equilibrium control strategies. Through comparative analysis, we investigate the impact of different collection channels on price, return rate, demand, and member profits. Our findings reveal that when the conditions across three collection channels are uniform, manufacturer collection emerges as the most effective reverse channel, challenging the conventional wisdom in static settings where retailer collection is typically considered optimal. Moreover, we extend our models to incorporate two critical factors: the collection cost coefficient and the collection logistics cost, which introduce differences across the collection channels. Under these differentiated conditions, our results suggest that third-party and retailer collections can also be optimal reverse channel solutions, particularly when the third-party collector has greater collection capacity, or the retailer benefits from lower reverse logistics costs.