Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company

By Devika Kannan, Ana Beatriz Lopes de Sousa Jabbour, Charbel José Chiappetta Jabbour. European Journal of Operational Research, 2014

675 citations recorded by the source corpus.

Due to an increased awareness and significant environmental pressures from various stakeholders, companies have begun to realize the significance of incorporating green practices into their daily activities. This paper proposes a framework using Fuzzy TOPSIS to select green suppliers for a Brazilian electronics company; our framework is built on the criteria of green supply chain management (GSCM) practices. An empirical analysis is made, and the data are collected from a set of 12 available suppliers. We use a fuzzy TOPSIS approach to rank the suppliers, and the results of the proposed framework are compared with the ranks obtained by both the geometric mean and the graded mean methods of fuzzy TOPSIS methodology. Then a Spearman rank correlation coefficient is used to find the statistical difference between the ranks obtained by the three methods. Finally, a sensitivity analysis has been performed to examine the influence of the preferences given by the decision makers for the chosen GSCM practices on the selection of green suppliers. Results indicate that the four dominant criteria are Commitment of senior management to GSCM; Product designs that reduce, reuse, recycle, or reclaim materials, components, or energy; Compliance with legal environmental requirements and auditing programs; and Product designs that avoid or reduce toxic or hazardous material use.

Subfields: Management Science and Operations Research, Marketing, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/8a24c150edf582c77f0c17166553a33a0d2c8f1f

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Citations in the corpus

An Integrated Hybrid Approach for Circular supplier selection and Closed loop Supply Chain Network Design under Uncertainty (2020, methodology): “MCDM problems constitute a framework for structuring decision making problems, as well as a set of methods for generating preferences among alternatives (Govindan et al., 2013; Kannan et al., 2014).”
Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers (2018, methodology): “TOPSIS method has some limitations in capturing the vagueness of data under fuzzy environment (Kannan et al., 2014), which Yu (2002) stated that fuzziness and vagueness are characteristics of many decisionmaking problems.”
Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry (2015, background): “Based on a case analysis of 3 business organizations, Kitazawa and Sarkis (2000) concluded that employee empowerment is a key to successfully implementing environmental management systems (ISO 14001) and reaping benefits associated with total quality management (TQM) and just-in-time (JIT) programs.”
Intuitionistic fuzzy based DEMATEL method for developing green practices and performances in a green supply chain (2015, neutral): “…Govindan et al., 2013; Hajmohammad, Vachon, Klassen, & Gavronski, 2013; Hsu & Hu, 2009; Jayant & Azhar, 2014; Kannan, Jabbour, & Jabbour, 2014; Kannan et al., 2014; Lin, 2013; Mirhedayatian, Azadi, & Farzipoor Saen, 2014; Testa & Iraldo, 2010; Tseng & Chiu, 2013; Tseng, Wang, Chiu, Geng, &…”
TOPSIS Method Based on Correlation Coefficient under Pythagorean Fuzzy Soft Environment and Its Application towards Green Supply Chain Management (2021, background): “In scientific research on advanced operations management, the most important issue for green supply chain management (GSCM) is to continuously improve the environmental capabilities of the supply chain [49].”