Abstract

In recent decades, environmental issues have become one of the main concerns of governments and societies. Manufacturing companies are looking for environmental-oriented operations to minimise landfills and maximise environmental and economic profit. Reverse logistics (RL) as one of the manufacturing methods is applying different types of approaches to recover used products and return them back to the market. However, recovered products are competing with new products in quality, quantity and value for gaining market share. Competition with new products requires identification of critical success factor (CSFs) in RL. The available literature on RL critical success factor is still very limited. Therefore, the aim of this paper is identification and classification of CSFs by interpretive structural modelling in RL. Moreover, ranking of the CSFs in RL by interpretive structural modelling is the other objective of this paper. Sixteen CSFs are identified from the literature and interpretive structural modelling is used to determine the ranking of these criteria. Results indicate that these factors are linked because of mutual effect.

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