Supply chain pessimistic efficiency evaluation using a modified data envelopment analysis model

Abstract

Estimating supply chain performance is a complicated decision making problem for managers. Exaggerating the performance places the results of the performance evaluation and its application at risk, because it leads to shortfall of improvement strategies for the companies. A pessimistic efficiency evaluation point of view for the supply chain gives a safe margin for improvement. This paper compares the efficiency scores of the Banker, Charnes & Cooper (BCC) model and a modified Data envelopment (DEA) model to highlight the exaggerated units. The results show that some models exaggerate the performance of some units, especially the weak efficient and inefficient units which compare by these units. The contribution of this study suggests a more robust model into the DEA literature for efficiency evaluation of supply chain, to avert the problem of improvement shortfall as a result of efficiency exaggeration by some models. © ExcelingTech Pub, UK.