Resource commitment and sustainability: a reverse logistics performance process model

Purpose The purpose of this paper is to extend existing and motivate future sustainable supply chain management (SCM) and logistics research by examining a structure-conduct-performance framework linking resource commitment to sustainable SCM, reverse logistics, and operational performance. A sustainable reverse logistics capability is investigated as mediating the performance benefits associated with resource commitments to sustainable SCM. Design/methodology/approach Survey methods and structural equation modeling were used to collect and analyze data from 180 supply chain professionals. Findings The results of a mediated model suggest that resource commitments may be used to develop a sustainable reverse logistics capability, reducing the environmental impact of reverse logistics activities. A strong sustainable reverse logistics capability results from resources committed specifically to sustainable reverse logistics and a commitment to the sustainability of the supply chain. Research limitations/implications This study applied a purposefully general sampling procedure. Specific industries may have additional constraints (e.g. risk, transparency, governance factors) that directly impact reverse logistics. These constraints are limitations of the study as well as opportunities for future research. Resource commitment is critical to the success of an overall firm strategy to build a sustainable supply chain, especially when considering reverse logistics. Practical implications As managers examine the benefits of sustainable SCM, they must consider the resources required. For firms engaging in sustainable SCM, developing a sustainable reverse logistics capability is a key success factor for improved performance. Originality/value Given the growing acceptance and importance of sustainable SCM, this research provides insights to managers and academics regarding the key mediating role of a sustainable reverse logistics capability when integrated into existing and future supply chain research frameworks and processes.