TY - JOUR
T1 - Developing a novel model of data envelopment analysis–discriminant analysis for predicting group membership of suppliers in sustainable supply chain
AU - Boudaghi, Elahe
AU - Farzipoor Saen, Reza
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2018/1
Y1 - 2018/1
N2 - 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.
AB - 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.
KW - BCC
KW - Data envelopment analysis–discriminant analysis (DEA–DA)
KW - Efficiency
KW - Prediction of suppliers' group membership
KW - Sustainable supply chain management
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U2 - 10.1016/j.cor.2017.01.006
DO - 10.1016/j.cor.2017.01.006
M3 - Article
AN - SCOPUS:85010282124
VL - 89
SP - 348
EP - 359
JO - Computers and Operations Research
JF - Computers and Operations Research
SN - 0305-0548
ER -