Research on Credit Evaluation of Metaverse Listed Companies Based on Hesitant Fuzzy Language PROMETHEE Method
- DOI
- 10.2991/978-94-6463-194-4_9How to use a DOI?
- Keywords
- Metaverse Listed Company; Credit Evaluation; Hesitant Fuzzy Language Set; PROMETHEE Method
- 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 .
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yi-fan Fu AU - Mu Zhang PY - 2023 DA - 2023/07/21 TI - Research on Credit Evaluation of Metaverse Listed Companies Based on Hesitant Fuzzy Language PROMETHEE Method BT - Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022) PB - Atlantis Press SP - 55 EP - 61 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-194-4_9 DO - 10.2991/978-94-6463-194-4_9 ID - Fu2023 ER -