股本回报率
衡平法
业务
人工神经网络
资产收益率
计量经济学
非线性系统
回归分析
灵敏度(控制系统)
线性模型
非营利组织
财务比率
财务
线性回归
经验模型
实证研究
预测建模
企业社会责任
金融危机
经济
经验证据
线性关系
持续性
前馈神经网络
会计
金融业
财务分析
作者
Aljaž Herman,Žan Jan Oplotnik,Timotej Jagrič
出处
期刊:Sustainability
[Multidisciplinary Digital Publishing Institute]
日期:2025-10-30
卷期号:17 (21): 9683-9683
被引量:6
摘要
This study investigates the relationship between ESG ratings and a firm’s financial performance, focusing on Return on Assets (ROA) and Return on Equity (ROE). Using a combination of stepwise linear regression and feedforward neural networks (FFNN), we assess both the linear and nonlinear effects of ESG on financial performance. The regression models identify ESG as a significant, positively correlated factor in explaining financial performance, alongside firm demographics, sector affiliation, and financial indicators. Neural networks reveal nonlinear dynamics, particularly for ROA, suggesting threshold effects in the ESG–performance relationship. Sensitivity analysis confirms that ESG’s influence strengthens at higher values. Our findings highlight that ESG is not only statistically relevant but also interacts with firm characteristics in complex ways. These results contribute to the ongoing discourse on sustainable finance by showing that ESG can be a meaningful driver of financial outcomes, especially when modeled through nonlinear approaches.
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