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Among many applications, several studies using Data Envelopment Analysis (DEA) have examined and studied the efficiency of supply chains. However, the majority of existing approaches dealing with this research area have ignored the important factor of decision makers’ preferences. The main objective of this article is to provide consistent DEA models that allow for efficiency analysis in order to determine the optimal allocation of resources according to these preferences. We propose three cases that are inspired from the geometric decomposition of preference attributions: (1) horizontal attribution, which is when decision makers treat each supply chain as a single non-detachable entity; (2) vertical attribution, which is when decision makers consider supply chains detachable and (3) combined attribution, which is when decision makers concurrently assign weights to the supply chain and to its members. Based on this suggested decomposition, new DEA models are developed, and an illustrative example is applied. The obtained results are relevant and show that DEA is capable of easily incorporating the preferences of decision-makers without resorting to weight restrictions on inputs or outputs.


data envelopment analysis efficiency supply chains decision-makers preferences geometric attribution

Article Details

Author Biography

Walid Abdelfattah, Northern Border University/ College of Arts and Sciences of Rafha

Department of Mathematics
How to Cite
Abdelfattah, W., & Cherif, M. S. (2020). Incorporation of Preferences into Supply Chains DEA Efficiency: A Geometric Attribution Approach. Pakistan Journal of Statistics and Operation Research, 16(4), 761-774.


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