Substantive innovation or strategic catering: Capital market pressure and corporate green innovation structure
Bibliographic record
Abstract
Green innovation requires a market environment willing to take on more risk and accept failure. Capital markets are essential in green innovation because they can spread out the risks associated with innovation. Compared to existing research, this paper focuses on the impact and processes of the short-selling mechanism on corporate green technology innovation structure. Specifically, this study utilizes a difference-in-difference model to examine the effects and underlying mechanisms based on the listed firms from 2011 to 2022. The results suggest that the pressure from the capital market might encourage the development of green technological innovation in corporations. Still, it also hinders the establishment of a structure for corporate green innovation and fosters the expansion of strategic patent behavior. The influence is achieved through enhancing managerial performance, monitoring external pressures, and transmitting stock price information. Heterogeneous analysis confirms that independent directors ratio and CEO duality play a critical role. The findings demonstrate how capital market pressure can affect corporate green innovation structure, support the critical role of capital market and contribute to further engagement in corporate green technology innovation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".