A Coherent Data Envelopment Analysis to Evaluate the Efficiency of Sustainable Supply Chains

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Abstract
Measuring and improving the efficiency of a sustainable supply chain in an effective way for strategic decision making is important in the business world. In this article, an alternative coherent data envelopment analysis (CoDEA) with a representation of the intramural structure is established for evaluating the efficiency of a sustainable supply chain. The proposed CoDEA model not only maintains the traditional value of data envelopment analysis (DEA) in its “black box” approach, which avoids the intermediate measures among different nodes in the supply chain, but also overcomes some main pitfalls in previously developed DEA models. The usefulness of the proposed model is illustrated in both simple and complex supply chain situations, yielding reasonable efficiency scores as compared with those from the existing methods. Moreover, the dummy decision-making unit (DMU) introduced in CoDEA offers additional benefits in the scenario of a small supply chain. The approach allows the implicit rule that requires three times the ratio between the total measurement factors and total DMUs to be always satisfied, providing a higher discriminatory power of CoDEA. Based on the case studies covering both simple and complex supply chains, the results and sensitivity analysis ascertain that the proposed CoDEA model is a flexible and reasonable alternative with a good efficiency evaluation, contributing toward an efficient and sustainable supply chain management process pertaining to sustainable strategy or policy recommendations.

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