The relationship between executive compensation structure and CSR in Chinese listed firms
Bibliographic record
Abstract
The purpose of this paper is to investigate the role of executive compensation structure, split between short-term (cash-based) compensation and long-term (equity-based) compensation, in relation to corporate social responsibility performance in the Chinese listed firms and how the association varies within state-owned enterprises (SOEs) and non-state-owned enterprises (Non-SOEs). \nBased on a sample of 302 Chinese lister firms over the period 2015-2017. The results show that both short-term compensation and long-term compensation have an impact on CSR. Specifically, short-term executive compensation has a positive association with CSR performance, and long-term compensation has a negative relationship with CSR performance. Furthermore, the cash-based compensation executed in SOEs is more attractive for executives to be encouraged to implement CSR than that in Non-SOEs. The paper has important implications for designing the executive incentive plan and confirms the prominent role of the executive about CSR decisions in China. Previous studies on the relationship between executives’ compensation and CSR has mainly focused on developed countries, like the U.S. and Canada. This study is set in an emerging economy and identifies new evidence to show that executive incentives' effect is institutionally specific.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".