Developing a novel model of data envelopment analysis–discriminant analysis for predicting group membership of suppliers in sustainable supply chain

Elahe Boudaghi, Reza Farzipoor Saen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

The objective of this paper is to present a novel model of data envelopment analysis–discriminant analysis (DEA–DA) for predicting group membership of suppliers in sustainable supply chain context. Our new model can predict group membership of the suppliers with respect to the nature of factors including inputs, outputs, and efficiency of each supplier. To demonstrate applicability of this new DEA–DA model, using a case study, the initial DEA–DA model developed by Sueyoshi (1999) is analyzed and compared with our proposed model. The results of the analysis show that our new DEA–DA model presents more precise prediction of sustainable suppliers' group membership.

Original languageEnglish
Pages (from-to)348-359
Number of pages12
JournalComputers and Operations Research
Volume89
DOIs
Publication statusPublished - Jan 2018

Keywords

  • BCC
  • Data envelopment analysis–discriminant analysis (DEA–DA)
  • Efficiency
  • Prediction of suppliers' group membership
  • Sustainable supply chain management

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research

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