A model using data envelopment analysis for the cross evaluation of suppliers under uncertainty

The paper addresses one of the key objectives of the purchasing function of a supply chain, i.e., the optimal selection of suppliers. We present a novel methodology that integrates the well-known cross-efficiency evaluation called Data Envelopment Analysis (DEA) and the Monte Carlo approach, to manage supplier selection considering uncertainty in the supply process, e.g. evaluating potential suppliers. The model allows to distinguish among several suppliers, overcoming the limitation of the traditional DEA method of not distinguishing among efficient suppliers. Moreover, the technique is able to classify suppliers with uncertain performance. The method is applied to the selection of suppliers of a Southern Italy SME.