A model for classification of intermediate measures and evaluating the performance of chain and its members (Q2627409)

Summary: Data envelopment analysis (DEA) is a suitable tool for evaluating supply chain performance. In the conventional DEA, it is deemed that the variable status of each performance measure from the point view of input or output is known. In a supply chain, there are measures that treat as both an input and output. Since it is difficult to classify intermediate measure that connect supply chain members as `outputs' or `inputs' of the chain, and conventional data envelopment analysis cannot directly measure the performance of supply chain. So, a new model is needed. In this paper, we develop a two-stage DEA model to classify the status of intermediate measures and evaluate the performance of the chain and its members. Then, application of the proposed model is presented by an example taken from the literature. This numerical experiment shows the consistency of the results obtained by our model which needs less computational stages compared to a recent model found in the literature.