Corporate environmental information disclosure and green innovation: The moderating effect of <scp>CEO</scp> visibility
Bibliographic record
Abstract
Abstract This study investigates the effect of corporate environmental information disclosure (EID) on green innovation in China's heavily polluting industries during 2009–2020 and the moderating effect of Chief Executive Officer (CEO) visibility. The results show that: (1) corporate EID increases green innovation, and CEO visibility strengthens the positive impact of corporate EID on green innovation. (2) The green innovation fostered by EID comes from the leverage effect, not from the crowding‐out effect at the expense of other existing innovations; EID stimulates green innovation by alleviating financing constraints and increasing R&D expenditures. (3) Corporate EID has a greater impact on substantive green innovation than on strategic green innovation, and hard EID makes a more significant contribution to green innovation than soft EID does. (4) State‐owned, large, and established enterprises benefit more from the promotion effect of EID on green innovation as well as the positive moderating effect of CEO visibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".