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Intuitionistic Fuzzy Selected Element Reduction Approach (IF-SERA) on Service Quality Evaluation of Digital Suppliers

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1602)

Abstract

In the application of fuzzy multi-criteria decision-making methods, criteria weights directly affect the evaluation. The methods in the literature are used to calculate the weights of subjective or objective criteria with various techniques. In addition to these methods, the effect of criteria reduction on weighting can be investigated for fuzzy decisions. This study developed a new method for weighting criteria in decision-making problems in intuitionistic fuzzy environment. The Intuitionistic Fuzzy Selected Element Reduction Approach (IF-SERA) is based on the change caused by the reduction of a criterion in an intuitionistic fuzzy decision matrix. The evaluations of decision-makers are used to determine the overall ranking. The influence of a chosen criterion on the findings is then determined by eliminating it from the evaluation. As a result, the criterion that causes the most change is assigned the most weight. The approach yields results that are directly proportional to the criterion weights. With the implementation of the service quality evaluation for digital suppliers, the novel fuzzy weighting approach is introduced to the literature.

Keywords

  • Selected element reduction approach
  • Fuzzy multi criteria decision making
  • Intuitionistic fuzzy set
  • Service quality evaluation
  • Digital suppliers

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Acknowledgement

“This work has been supported by the Scientific Research Projects Commission of Galatasaray University under grant number # FBA-2022-1085”.

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Correspondence to Esra Çakır .

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Çakır, E., Taş, M.A., Demircioğlu, E. (2022). Intuitionistic Fuzzy Selected Element Reduction Approach (IF-SERA) on Service Quality Evaluation of Digital Suppliers. In: , et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2022. Communications in Computer and Information Science, vol 1602. Springer, Cham. https://doi.org/10.1007/978-3-031-08974-9_11

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  • DOI: https://doi.org/10.1007/978-3-031-08974-9_11

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