Examining the Interactive Effect of Advertising Investment and Corporate Social Responsibility on Financial Performance
Bibliographic record
Abstract
This article explores the interactive effect of advertising investment and corporate social responsibility (CSR) on financial performance by selecting 2431 listed companies that participated in the professional evaluation of Hexun.com as the research sample, with a total of 12,471 observed values. The panel regression, analysis and hypotheses tests were conducted to examine the interactive effect of advertising investment and CSR on financial performance. There are four empirical findings. First, an advertising investment plays a significant role in improving corporate financial performance. Second, actively fulfilling CSR can effectively upgrade the financial performance of an enterprise. Third, different functional mechanisms will not change the positive impact of CSR on financial performance. Fourth, the interaction between advertising investment and CSR has a significant positive correction on financial performance. Combining the advertising investment with CSR they have a remarkable complementary effect on financial performance. Based on these findings, this article claims that to maximize the advertising effect, company managers should actively carry out business activities and conduct appropriate advertising investments from the perspective of CSR. In other words, to enhance the return on marketing activities and strengthen the promotion of financial performance by advertising investment, company managers should pay more attention to fulfilling CSR and take advantage of the reputational and social images generated by CSR to bring greater market value and financial growth.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".