Modeling the hierarchical structure of reverse logistic using driving and dependence power analysis

Reverse logistic is important in a green supply chain by providing customers the returns of used or defected products to the manufacturers as well as to gain the values from returned products. An efficient reverse logistics planning will create and increase the competitive advantage for those operations in market place. This literature aims at making the decisions to select the third party reverse logistics providers efficiently. This research uses the combination of interpretive structural modeling to address the analytical objective. The proposed variables categorize into a hierarchical structure and apply according to the dependence and driving power. The findings originate insights the adoption of reverse logistics practices in auto-parts and electronics and electrical equipment industrial. Managerial and theoretical implications of our findings are discussed.