How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran

• Published in: Journal of enterprise information management Vol. 34; no. 1; pp. 199 - 229
• Main Authors: Izadikhah, Mohammad, Farzipoor Saen, Reza, Ahmadi, Kourosh, Shamsi, Mohadeseh
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 28.01.2021; Emerald Group Publishing Limited
• Subjects: Algorithms; Case studies; Clustering; Collaboration; Data analysis; Data envelopment analysis; Decision making; Fuzzy sets; Linear programming; Literature reviews; Methods; Screening; Suppliers; Supply chain management; Sustainability; Iran; Data envelopment analysis (DEA); Sustainable supply chain management; Enhanced Russell model (ERM); DEA-Based clustering method; Fuzzy screening system
• ISSN: 1741-0398; 1758-7409
• DOI: 10.1108/JEIM-09-2019-0262

PurposeThe 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/approachFirst, 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.FindingsThis 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/valueThe 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.