A Markov model of liquidity effects in reverse logistics processes: The effects of random volume and passage

Firms at various levels of the supply chain are implementing reverse logistics systems to maximize the value captured from products flowing backwards from customers to suppliers. However, due to the sporadic and unpredictable cash outflows associated with returns, firms must take care to avoid liquidity problems. Previous work addressing reverse logistics liquidity issues has considered long-term expectations, uncertainty, and shock potential inherent in the retail reverse logistics process, but the impact of the expected returns volumes and random return quantities within fixed-scale systems has yet to be explored. The current paper addresses these concerns.