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The Service Quality Evaluation of Agricultural E‐Commerce Based on Interval‐Valued Intuitionistic Fuzzy GRA Method

Author

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  • Haibin Zhang
  • Lei Wang

Abstract

The service quality evaluation of agricultural business‐to‐customer (B2C) e‐commerce is viewed as a multiattribute group decision‐making (MAGDM) activity. Thus, a useful MAGDM process is required. Based on the grey relational analysis (GRA) process and the interval‐valued intuitionistic fuzzy set (IVIFS), this study defines an interval‐valued intuitionistic fuzzy (IVIF) GRA process to depict the service quality of agricultural B2C e‐commerce. This is important to agricultural B2C e‐commerce because this industry increases rapidly and many new services are innovated. In this article, some necessary definitions related to IVIFSs are reviewed. Additionally, criteria weights are derived using the Criteria Importance Through Intercriteria Correlation method (CRITIC). Subsequently, the GRA method is extended to incorporate IVIFs to obtain a final service alternative. All alternatives can then be ranked, and the best service quality option can be identified and promulgated. Finally, a numerical example and some useful comparative studies are obtained. The analysis results show that the defined algorithm is effective for identifying the service qualities of agricultural B2C e‐commerce, which provide a new assessment method for MAGDM.

Suggested Citation

  • Haibin Zhang & Lei Wang, 2022. "The Service Quality Evaluation of Agricultural E‐Commerce Based on Interval‐Valued Intuitionistic Fuzzy GRA Method," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:3931136
    DOI: 10.1155/2022/3931136
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