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Rating of Financing Ability of Listed Companies Based on ESG Performance

Author

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  • Hua Ding

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Yongqi Xu

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

Abstract

At present, although there are a variety of assessment systems to rate the financing ability of enterprises, these systems suffer from the problems of outdated indicators and subjective weighting methods. In this paper, the impact of ESG performance on financing ability is taken as an evaluation index and combined with 13 other indexes to construct a new TOPSIS assessment system. Cooperative game theory in the form of the entropy weight method and a BP neural network is used to avoid the subjectivity of weighting. After establishing the evaluation model, we selected cross-sectional data from 4590 listed companies on the Shanghai and Shenzhen stock exchanges in 2023 to train the evaluation model and explore the impact of various indicators on financing capabilities. The results show the following: (1) Total revenue and total assets of main board companies are the main factors affecting financing ability. (2) Total revenue growth rate, total revenue, and R&D costs of Science and Technology Innovation Board Market (STAR Market) companies are the main factors affecting the financing ability. (3) Growth Enterprise Market (GEM) companies’ total revenue and R&D costs are the main factors affecting financing ability. This study uses data from 2023. In practical applications, it is recommended to use the latest data for evaluation and analysis, and to update the weights every six months.

Suggested Citation

  • Hua Ding & Yongqi Xu, 2025. "Rating of Financing Ability of Listed Companies Based on ESG Performance," Sustainability, MDPI, vol. 17(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8512-:d:1755289
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    References listed on IDEAS

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