Early warning analysis and empirical research of real estate enterprise capital chain crisis based on cloud model
Yuhang Lin, Jiwei Zhu, Nan Lu · 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence · 2021
In recent years, with the upgrading of macroeconomic control and the increase in corporate concentration, the development of the real estate industry has entered a period of adjustment. The high-leverage and high-debt operating model cannot be sustained. In the future, industry competition and corporate funding pressure will continue to increase. This paper takes real estate enterprises as the research object, based on the analysis of the characteristics of the capital chain crisis in the whole life cycle of the real estate business activities, constructs the capital chain crisis evaluation index system, and tests the rationality of the indicators, and uses the combined weight method to calculate the index weights. Established a crisis early warning model based on cloud model theory, and applied and tested the early warning model through empirical research. The results confirmed that the established index system has high applicability to real estate companies, and the constructed early warning model has a more accurate early warning effect on real estate companies’ capital chain crises, and the Modeling ideas that Combination weight and cloud model two methods are coupled and coordinated further improved the scope, accuracy and rationality of the early warning system.