Modeling efficiency in the presence of multiple partial input to output processes

Wang Hong Li, Liang Liang, Sonia Valeria Avilés-Sacoto, Raha Imanirad, Wade D. Cook () and Joe Zhu
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Wang Hong Li: School of Management University of Science and Technology of China
Liang Liang: School of management University of Science and Technology of China
Sonia Valeria Avilés-Sacoto: ITESM - Monterrey
Raha Imanirad: Harvard University
Wade D. Cook: York University
Joe Zhu: Nanjing Audit University

Annals of Operations Research, 2017, vol. 250, issue 1, No 14, 235-248

Abstract: Abstract Data envelopment analysis (DEA) is a methodology used to measure the relative efficiencies of peer decision-making units (DMUs). In the original model, it is assumed that in a multiple input, multiple output setting, all members of the input bundle affect the entire output bundle. There are many situations, however, where this assumption does not hold. In a manufacturing setting, for example, packaging resources (inputs) only influence the production of those products that require packaging. This is referred as partial input-to-output interactions where the DEA model is based on the view of a DMU as a business unit consisting of a set of independent subunits, such that efficiency of the DMU can be defined as a weighted average of the efficiencies of those subunits. The current paper presents an extension to that methodology to allow for efficiency measurement in situations where there exist multiple procedures or processes for generating given output bundles. The proposed model is then applied to the problem of evaluating the efficiencies of a set of steel fabrication plants.

Keywords: DEA; Partial impacts; Sub units; Multiple processes (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-015-2006-2

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