A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty

A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty

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Article ID: iaor20161006
Volume: 23
Issue: 4
Start Page Number: 725
End Page Number: 748
Publication Date: Jul 2016
Journal: International Transactions in Operational Research
Authors: , , ,
Keywords: decision, statistics: data envelopment analysis, stochastic processes, simulation
Abstract:

This paper addresses one of the key objectives of the supply chain strategic design phase, that is, the optimal selection of suppliers. A methodology for supplier selection under uncertainty is proposed, integrating the cross‐efficiency data envelopment analysis (DEA) and Monte Carlo approach. The combination of these two techniques allows overcoming the deterministic feature of the classical cross‐efficiency DEA approach. Moreover, we define an indicator of the robustness of the determined supplier ranking. The technique is able to manage the supplier selection problem considering nondeterministic input and output data. It allows the evaluation of suppliers under uncertainty, a particularly significant circumstance for the assessment of potential suppliers. The novel approach helps buyers in choosing the right partners under uncertainty and ranking suppliers upon a multiple sourcing strategy, even when considering complex evaluations with a high number of suppliers and many input and output criteria.

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