Proceedings of the 9th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2020)

Research on Credit Risk Evaluation of Big Data Enterprises Based on Fuzzy DEA

Authors
Jie Ren, Hong Mei Zhang
Corresponding Author
Jie Ren
Available Online 12 April 2021.
DOI
https://doi.org/10.2991/aebmr.k.210409.034How to use a DOI?
Keywords
Fuzzy DEA, big data enterprise, credit risk
Abstract
The development of big data enterprises in China is still in its infancy, and there is a big gap between China and foreign countries in terms of technology and credit risk evaluation. In this context, based on the research of big data enterprises, this paper uses principal component analysis and correlation analysis to screen the credit risk evaluation indicators of big data enterprises, and uses fuzzy DEA method to evaluate the credit risk of big data enterprises. Finally, empirical analysis is carried out to evaluate the credit risk of big data enterprises.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Cite this article

TY  - CONF
AU  - Jie Ren
AU  - Hong Mei Zhang
PY  - 2021
DA  - 2021/04/12
TI  - Research on Credit Risk Evaluation of Big Data Enterprises Based on Fuzzy DEA
BT  - Proceedings of the 9th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2020)
PB  - Atlantis Press
SP  - 217
EP  - 222
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210409.034
DO  - https://doi.org/10.2991/aebmr.k.210409.034
ID  - Ren2021
ER  -