An Integrated Interval Type-2 Fuzzy Set Model for Evaluating Circular Low Carbon Suppliers in a Developing Country


ENGINEERING MANAGEMENT JOURNAL, vol.36, no.2, pp.221-243, 2024 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 2
  • Publication Date: 2024
  • Doi Number: 10.1080/10429247.2023.2253691
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, ABI/INFORM, Business Source Elite, Business Source Premier, Compendex, INSPEC
  • Page Numbers: pp.221-243
  • Keywords: Circular Low Carbon Supply Chain, COPRAS, DANP, Decision Making & Risk Management, Interval Type-2 Fuzzy Sets, Operations Management, Supplier Evaluation, Supply Chain Management, Sustainability
  • Karadeniz Technical University Affiliated: Yes


Increasing carbon emissions and environmental degradation have led to rapid depletion of resources. This requires circular low carbon (CLC) supply chains which extend the lifecycle of resources as much as possible. The aim of this study is to propose an integrated model for CLC supplier selection. First, economic, environmental and social responsibilities related to carbon management are identified. Then, DANP (Dematel-Analytic Network Process) and COPRAS (Complex Proportional Assessment) model with interval type-2 (IT-2) fuzzy sets are applied to evaluate the suppliers of a case energy company in Turkey. In this study, the ranking of dimensions from the most important to the least yielded the following order: environmental, social, and economic. In turn, carbon policy, carbon emission risks and low carbon supplier collaboration are found to be the most important environmental criteria. The current study has been used for the first time for a CLC supplier selection problem. Further, the study innovatively employs IT-2 fuzzy sets to better address differences and uncertainties that may come into play with a group of experts' linguistic judgments. The validity of the proposed method is determined through sensitivity and comparative analysis.