Measuring the efficiency of third party reverse logistics provider in supply chain by multi objective additive network DEA model

The demand for third-party reverse logistics (3PL) provider becomes an increasingly significant issue for corporations seeking improved customer service and cost reduction. Hence, 3PL provider evaluation and selection is an important issue and it has a strategic significance for every company. One of the techniques that can be used for evaluating and selecting 3PL providers is data envelopment analysis (DEA). The traditional models for DEA type performance measurement are based on thinking about production as a 'black box'. Inputs are transformed in this box into outputs. One of the drawbacks of these models is the neglect of linking activities. An important body of work has been directed at problem settings where the decision making unit (DMU) is characterised by a multistage process; supply chains take this form. Recent DEA literature on serial processes has tended to focus on closed systems, that is, where the outputs from one stage become the inputs to the next stage, and where no other inputs enter the process at any intermediate stage. In this paper, we propose a multi objective additive network DEA model to evaluate and select the most appropriate 3PL providers. Finally, a case study demonstrates the application of the proposed model.