Investigating the relationship between corporate social responsibility and firm’s financial performance and the moderating effect of corporate governance: Evidence from U.S. firms
Bibliographic record
Abstract
Many studies have examined the relationship between corporate social responsibility (CSR) and a firm’s financial performance. These investigations have had mixed results. Some studies find a positive relationship, others find a negative relationship, and yet some studies find no significant relationship. This ambiguity highlights the complexity of the relationship between CSR initiatives and firm performance. The present study attempts to better understand this relationship. As such, it has two objectives. Since most of the previous studies have examined a linear relationship between CSR and a company's financial performance, the first objective of this study is to investigate whether there is any nonlinear relationship between CSR and firm’s financial performance. The second objective of this study is to examine the moderating effects of corporate governance factors, especially the board of directors’ characteristics such as board size, board independence, board gender diversity, and CEO duality on the relationship between CSR and a firm’s financial performance. The latter factors have not been fully considered in previous studies as the focus has been on the direct link between CSR and the firm’s financial performance. The study uses panel data from a sample of 82 firms from a large group of publicly traded American firms, which are listed on the U.S. stock exchange and are part of the S&P 500 index covering the years 2012-2021, and a nonlinear panel regression model to estimate the relationship between firm’s financial performance as measured by Return on Asset (ROA) and CSR disclosure index along with a control variable and four Corporate Governance indicators and their interactions with CSR disclosure index. The study finds a non-linear positive relationship between firm’s performance and CSR, suggesting a declining effect of CSR on firm’s performance at higher levels of CSR. It also finds that board gender diversity positively affects the relationship between CSR and a firm’s financial performance. We find no statistically significant interactions between CSR and the Governance indicators of board size, board independence and CEO duality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".