A circular reverse logistics framework for handling e-commerce returns

Global e-commerce sales are growing rapidly adding complexities to their supply chains. There are an increasing trend of product returns along with the growth of global e-commerce platforms, placing a huge significance on reverse logistics management. E-commerce being a competitive industry, factors such as environmental con-cerns, customer awareness, and legal pressure have led the firms to pay attention to the circular economy and sustainability concepts while managing their reverse logistics. Considering the above factors, this paper proposes a three-stage, circular reverse logistics framework for handling e-commerce returns. We introduce a novel method of applying ward-like hierarchical clustering with geographical constraints on returns data to identify return patterns as the first stage. As the second stage, a circular economy network was introduced among different parties to commit towards the circular economy. We develop a mixed integer linear programming model upon the above circular economy network in the third stage to capture different facets of the reverse logistics in e-commerce and optimize the network. At the final stage, the model is validated with a case study based on an e-commerce firm engaged in consumer electrical and electronics. The decision support system which is an output of this study will help the decision makers in e-commerce firms to embrace circular economy and optimize the reverse logistics network, while handling product returns.

Automated summary

Global e-commerce sales are adding complexities to supply chains, specifically with the increasing trend of product returns. This paper proposes a three-stage circular reverse logistics framework to optimize the reverse logistics network in e-commerce, with a focus on identifying return patterns, introducing circular economy networks, and using a mixed integer linear programming model.