Credit Risk Evaluation of Chip Manufacturing Listed Companies Based on Fermatean Fuzzy VIKOR Method

Yu-tong Luo and Mu Zhang ()
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Yu-tong Luo: Guizhou University of Finance and Economics, School of Big Data Application and Economics
Mu Zhang: Guizhou University of Finance and Economics, School of Big Data Application and Economics

A chapter in Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), 2023, pp 206-212 from Springer

Abstract: ABSTRACT China's chip manufacturing technology has made great strides forward, and the study of credit risk of chip manufacturing listed companies can better perceive their risk status and provide more valuable decision-making information for both companies and investors. In response to the existing fuzzy language interpretation space is insufficient, this paper proposes a credit risk evaluation method based on Fermatean fuzzy VIKOR method. And the effectiveness of this method is demonstrated by example with the credit risk of chip manufacturing enterprises. First, the entropy weight method is applied to determine the attribute weight coefficients. Then, the decision matrix is evaluated by experts, and this evaluation needs to satisfy the Fermatean fuzzy constraint. Then, the VIKOR method is applied to rank the credit merits of the company in the Fermatean fuzzy environment. Finally, the Fermatean fuzzy and Pythagorean fuzzy VIKOR methods are compared. The results show that the Fermatean fuzzy VIKOR method has better differentiation and stronger credit risk assessment ability.

Keywords: Fermatean Fuzzy; VIKOR; The Entropy Weight Method; Credit Risk Assessment (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-194-4_29

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DOI: 10.2991/978-94-6463-194-4_29

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