Data envelopment analysis (DEA) is known as a useful tool\nthat produces many efficient decision-making units\n(DMUs). Traditional DEA provides relative efficient scores\nand reference sets, but does not influence and rank the\nefficient DMUs. This paper suggests a method that provides\ninfluence and ranking information by using PageRank\nas a centrality of Social Network analysis (SNA)\nbased on reference sets and their lambda values. The social\nnetwork structure expresses the DMU as a node, reference\nsets as link, and lambda as connection strengths or weights.\nThis paper, with PageRank, compares the Eigenvector\ncentrality suggested by Liu, et al. in 2009, and shows that\nPageRank centrality is more accurate.
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