A hybrid mining approach for optimizing returns policies in e-retailing

The returns policy has long been considered as a critical yet controversial issue in the development of supply chain and marketing strategies. Up-stream manufacturers or distributors may offer returns policies to the down-stream retailers or customers to increase order and sales quantities. There are trade-offs between returns policies and customer satisfaction, product sales, and operating costs. The goal of this paper is to use a hybrid mining approach for analyzing return patterns from both the customer and product perspectives, classifying customers and products into levels, and then for adopting proper returns policies and marketing strategies to these customer classes for sustaining better profits. A multi-dimensional framework and an associated model for the hybrid mining approach are provided with a demonstrated example for validation. It is expected that by adopting suitable returns policies, benefits can be created and shared by both e-retailers and customers.