The Impact of ESG on Business Performance: An Empirical Analysis of NASDAQ–NYSE-Listed Companies

Aljaž Herman (), Žan Jan Oplotnik and Timotej Jagrič
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Aljaž Herman: Institute of Finance and Artificial Intelligence, Faculty of Economics and Business, University of Maribor, Razlagova 14, 2000 Maribor, Slovenia
Žan Jan Oplotnik: Institute of Finance and Artificial Intelligence, Faculty of Economics and Business, University of Maribor, Razlagova 14, 2000 Maribor, Slovenia
Timotej Jagrič: Institute of Finance and Artificial Intelligence, Faculty of Economics and Business, University of Maribor, Razlagova 14, 2000 Maribor, Slovenia

Sustainability, 2025, vol. 17, issue 21, 1-17

Abstract: 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.

Keywords: ESG; financial performance; ROA; ROE; regression; neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:21:p:9683-:d:1783581

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