Unveiling the Structure of Reverse Supply Networks: An Empirical Exploration

As the levels of inventory in supply chains worldwide continue to rise, with over $800 billion of returned and excess inventory (equivalent to 3% of the U.S. GDP) passing through secondary market channels each year, efficient reverse supply networks have become increasingly important. In this study, we use a multi-method approach to analyze a longitudinal dataset from a large U.S. reverse logistics platform for the purpose of mapping the reverse supply network and exploring its evolution over time. Taking a network perspective and drawing upon the complex adaptive system theory, our study contributes to the literature by providing the first large-scale, long-term mapping of a reverse supply network. This analysis reveals how reverse supply networks evolve, how macroeconomic factors impact their dynamically changing structures, and how these networks differ from forward supply networks. Our findings also provide important implications for managers, shedding light on the importance of secondary markets and reverse supply networks in firms' overall supply chain strategies.