Value recovery network design for product returns

Abstract

Purpose The purpose of this paper is to use a conceptual model from literature for designing value recovery (VR) networks for three categories of post‐consumer product returns. Design/methodology/approach A bi‐level optimization model is developed to determine the disposition decision for refrigerators, washing machines and passenger cars in the Indian context using data for product returns from literature. Using standard off‐the‐shelf software, the break‐even values of returns are calculated for setting up various VR facilities under different scenarios to maximize profits for a ten‐year time‐horizon. Findings The VR activities are profitable for all the three categories of products beyond a certain minimum quantity of returns. Experimentation across the three product categories shows that presently remanufacturing is not a viable economic proposition in the Indian context. Further, the VR network design suggested by this approach is volume flexible. Research limitations/implications A “push” system where the volumes and grades of returns drive the VR decisions. Optimization has been carried out for three product categories and not brands or OEMs. No free choice of facility locations. Practical implications The insights and learning under different scenarios may be utilized as inputs for decision‐making and for designing various incentive plans. Originality/value This work is a first step towards VR network design in the Indian context. Various tools from the methodological perspective are used and provide detailed network design from the topological perspective.

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