Green supplier selection in new era for sustainability: A novel method for integrating big data analytics and a hybrid fuzzy multi-criteria decision making

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Soft Computing, 2021 (Journal Indexed in SCI Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2021
  • Doi Number: 10.1007/s00500-021-06477-8
  • Title of Journal : Soft Computing
  • Keywords: Big data analytics, Fuzzy decision making, Green supplier selection, Hybrid multi-criteria decision making, Sustainability


© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Environmentally conscious supplier selection has become increasingly important in recent years. Green supplier selection is one of the vital decisions of supply chain management, as it is preferred for businesses in the market that adopt an environmental approach and green philosophy in line with material and moral benefits. In this context, the problem of choosing the most efficient green supplier is addressed with a three-step methodology using big data analytics that includes an integrated approach and hybrid fuzzy AHP-TOPSIS techniques. First of all, big data plays an important role in delivering meaningful results by reducing complexity to a more fundamental level. It is possible to obtain more consistent results by examining a series of criteria in green supplier selection at a more reasonable and operational level. Thus, the role of big data analytics provides an input for decision-making, which enables a systematic reduction to more concise data. Then, these inputs are evaluated in a fuzzy environment with hybrid MCDM techniques and the most efficient green supplier is determined among the suppliers. This authentic study sheds light on providing a significant competitive advantage to businesses in line with their strategic targets as well as having environmental contributions to sustainability. Graphical abstract: [Figure not available: see fulltext.]