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Research on Credit Evaluation of Metaverse Listed Companies Based on Hesitant Fuzzy Language PROMETHEE Method

In: Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022)

Author

Listed:
  • Yi-fan Fu

    (Guizhou University of Finance and Economics, School of Big Data Application and Economics
    Guizhou University of Finance and Economics, Guizhou Institution for Technology Innovation & Entrepreneurship Investment)

  • Mu Zhang

    (Guizhou University of Finance and Economics, School of Big Data Application and Economics)

Abstract

ABSTRACT To objectively evaluate the credit level of Metaverse listed companies, this paper introduces technological innovation capability into the index system, and constructs the credit evaluation index of Metaverse listed companies from five aspects: profitability, solvency, growth capability, operational capability, and technological innovation capability. The system, and select the relevant financial data of the 12 Metaverse listed companies in 2021, based on the hesitant fuzzy language set theory, adopts the PROMETHEE multi-attribute decision-making method, and uses the priority function to measure the credit level of the 12 Metaverse listed companies. The empirical research results show that the four listed companies in Metaverse, Goertek, Changxin Technology, Longli Technology, and Xinguodu, have relatively high net flows and good credit levels. From the perspective of banks, when choosing to issue loans, they can give priority to .

Suggested Citation

  • Yi-fan Fu & Mu Zhang, 2023. "Research on Credit Evaluation of Metaverse Listed Companies Based on Hesitant Fuzzy Language PROMETHEE Method," Advances in Economics, Business and Management Research, in: Sen Qiao & Hongbin Cao & Aiwen Liu & Xueliang Chen & Tiefei Li (ed.), Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), pages 55-61, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-194-4_9
    DOI: 10.2991/978-94-6463-194-4_9
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