TY - JOUR
T1 - How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran
AU - Izadikhah, Mohammad
AU - Farzipoor Saen, Reza
AU - Ahmadi, Kourosh
AU - Shamsi, Mohadeseh
N1 - Funding Information:
The authors would like to appreciate three Reviewers for their constructive comments.
Publisher Copyright:
© 2020, Emerald Publishing Limited.
PY - 2020/6/16
Y1 - 2020/6/16
N2 - Purpose: The aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering. Design/methodology/approach: First, using fuzzy screening system, the authors identify and remove the unqualified suppliers. Then, the authors run their proposed clustering method. This paper proposes a data envelopment analysis (DEA) algorithm to cluster suppliers. Findings: This paper presents a two-aspect DEA-based algorithm for clustering suppliers into clusters. The first aspect applied DEA to consider efficient frontiers and the second aspect applied DEA to consider inefficient frontiers. The authors examine their proposed clustering approach by a numerical example. The results confirmed that their method can cluster DMUs into clusters. Originality/value: The main contributions of this paper are as follows: This paper develops a new clustering algorithm based on DEA models. This paper presents a new DEA model in inefficiency aspect. For the first time, the authors’ proposed algorithm uses fuzzy screening system and DEA to select suppliers. Our proposed method clusters suppliers of MPASR based on sustainability factors.
AB - Purpose: The aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering. Design/methodology/approach: First, using fuzzy screening system, the authors identify and remove the unqualified suppliers. Then, the authors run their proposed clustering method. This paper proposes a data envelopment analysis (DEA) algorithm to cluster suppliers. Findings: This paper presents a two-aspect DEA-based algorithm for clustering suppliers into clusters. The first aspect applied DEA to consider efficient frontiers and the second aspect applied DEA to consider inefficient frontiers. The authors examine their proposed clustering approach by a numerical example. The results confirmed that their method can cluster DMUs into clusters. Originality/value: The main contributions of this paper are as follows: This paper develops a new clustering algorithm based on DEA models. This paper presents a new DEA model in inefficiency aspect. For the first time, the authors’ proposed algorithm uses fuzzy screening system and DEA to select suppliers. Our proposed method clusters suppliers of MPASR based on sustainability factors.
KW - Data envelopment analysis (DEA)
KW - DEA-Based clustering method
KW - Enhanced Russell model (ERM)
KW - Fuzzy screening system
KW - Sustainable supply chain management
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U2 - 10.1108/JEIM-09-2019-0262
DO - 10.1108/JEIM-09-2019-0262
M3 - Article
AN - SCOPUS:85106373519
SN - 1741-0398
VL - 34
SP - 199
EP - 229
JO - Journal of Enterprise Information Management
JF - Journal of Enterprise Information Management
IS - 1
ER -