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Supply chain DEA: Production possibility set and performance evaluation model

  • Feng Yang
  • , Dexiang Wu
  • , Liang Liang
  • , Gongbing Bi
  • , Desheng Dash Wu
  • University of Science and Technology of China
  • Reykjavík University
  • University of Toronto

Research output: Contribution to journalArticlepeer-review

Abstract

Performance evaluation is of great importance for effective supply chain management. The foundation of efficiency evaluation is to faithfully identify the corresponding production possibility set. Although a lot of researches have been done on supply chain DEA models, the exact definition for supply chain production possibility set is still in absence. This paper defines two types of supply chain production possibility sets, which are proved to be equivalent to each other. Based upon the production possibility set, a supply chain CRS DEA model is advanced to appraise the overall technical efficiency of supply chains. The major advantage of the model lies on the fact that it can help to find out the most efficient production abilities in supply chains, by replacing or improving inefficient subsystems (supply chain members). The proposed model also directly identifies the benchmarking units for inefficient supply chains to improve their performance. A real case validates the reasonableness and acceptability of this approach.

Original languageEnglish
Pages (from-to)195-211
Number of pages17
JournalAnnals of Operations Research
Volume185
Issue number1
DOIs
StatePublished - May 2011
Externally publishedYes

Keywords

  • Constant return to scale (CRS)
  • Data envelopment analysis (DEA)
  • Performance evaluation
  • Production possibility set
  • Supply chain management (SCM)

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