Network DEA Pitfalls: Divisional Efficiency and Frontier Projection

Yao Chen (), Wade D. Cook (), Chiang Kao () and Joe Zhu ()
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Yao Chen: University of Massachusetts at Lowell
Wade D. Cook: York University
Chiang Kao: National Cheng Kung University
Joe Zhu: Worcester Polytechnic Institute

Chapter Chapter 2 in Data Envelopment Analysis, 2014, pp 31-54 from Springer

Abstract: Abstract Recently network DEA models have been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In general, there are two types of network DEA models. One is developed under the standard multiplier DEA models based upon the DEA ratio efficiency, and the other under the envelopment DEA models based upon production possibility sets. While the multiplier and envelopment DEA models are dual models and equivalent under the standard DEA, such is not necessarily true for the two types of network DEA models. Pitfalls in network DEA are discussed with respect to the determination of divisional efficiency, frontier type, and projections. We point out that the envelopment-based network DEA model should be used for determining the frontier projection for inefficient DMUs while the multiplier-based network DEA model should be used for determining the divisional efficiency. Finally, we demonstrate that under general network structures, the multiplier and envelopment network DEA models are two different approaches. The divisional efficiency obtained from the multiplier network DEA model can be infeasible in the envelopment network DEA model. This indicates that these two types of network DEA models use different concepts of efficiency. We further demonstrate that the envelopment model’s divisional efficiency may actually be the overall efficiency.

Keywords: Data envelopment analysis (DEA); Efficiency; Network; Intermediate measure; Link; Frontier (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-1-4899-8068-7_2

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