Does Innovation Drive Environmental Disclosure? A New Insight into Sustainable Development
Bibliographic record
Abstract
Abstract Sustainable development is a hot topic in business and the media, and there is a growing demand for reliable environmental disclosure from a wide range of stakeholders. Ethical performance, including social and environmental performance, is actively scrutinized. A firm's stakeholders expect reliable disclosure to correctly assess its performance. Research on the link between environmental disclosure and environmental performance shows mixed results. Both a positive and a negative association have been found. This study reexamines this association by considering environmental innovation as a key determinant of environmental disclosure. We find that environmental performance and environmental innovation jointly determine environmental disclosure. At low levels of environmental performance, innovative firms tend to disclose more than their non‐innovative counterparts to inform stakeholders about their innovation and strategy to obtain an improved environmental performance. This disclosure gap tends to diminish as innovative firms become better environmental performers. The higher levels of environmental disclosure are closely associated with firms' environmental performance for both groups. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".