Reverse logistics (RL), which refers to the distribution activities involved in product returns, has recently received much attention because many companies are using it as a strategic tool to serve their customers and can generate good revenue. An efficient reverse distribution structure may lead to a significant return on investment as well as a significantly increased competitiveness in the market. Therefore, analysis of the interaction among the major barriers, which hinder or prevent the application of reverse logistics, is a crucial issue. Existing models have focused on diagnosing these barriers independently. As a result, the holistic view in understanding the barriers is not accounted for. This paper utilizes the Interpretive Structural Modeling (ISM) methodology to understand the mutual influences among the barriers so that those driving barriers, which can aggravate few more barriers and those independent barriers, which are most influenced by driving barriers, are identified.