LAUSR

This paper aims to analyze the interaction among the major variables of reverse logistics seen in automobile industries.,In this research, interpretive structural modeling (ISM) has been used to understand mutual influences among identified variables of reverse logistics. The advantage of the ISM methodology is that variables can be categorized depending upon their driving power and dependence.,Regulations make it mandatory for automobile companies to own responsibility of products manufactured throughout their life cycle by collecting and reusing products, reducing volume of waste generated, increasing the use of recycled materials, etc. For example, End-of-Life Vehicle Directive had directed manufacturers to take back their vehicles at the end of their usefulness and responsibly dispose them. In this research, regulation has appeared at bottom of the ISM model, indicating that it has high driving power to influence other variables. Also, financial limitations are a significant inhibitor faced by the top management for implementing reverse logistics programs.,The ISM methodology relies upon expert opinions for developing contextual relation among identified variables. Thus, an expert’s knowledge, his familiarity with industry and its operations may have affected the final results of the ISM model. One of research implications of this study is that variables identified in this ISM model are quite generic, and thus, with marginal adjustments, these can be used in the context of any other supply chain for increasing its productivity and performance.,The ISM model reveals that regulations affect a significant number of enabler variables of reverse logistics like support of policy entrepreneurs, green purchasing by companies, information and communication technologies that are seen at the upper level of ISM. This indicates that regulations force companies to be proactive towards product recovery actions that lead to initiation of reverse logistics programs by them.,This research has tried to analyze the interaction among the major variables of reverse logistics typically seen in automobile industries which could be useful to logistics managers for taking strategic-level decisions.