The Influence of Technology Differences on Corporate Environmental Patents: A Resource‐Based Versus an Institutional View of Green Innovations
Bibliographic record
Abstract
Abstract This paper proposes that both the resource‐based view and institutional theory predict a positive relationship between the number of patented environmental innovations and non‐environmental innovations held by a firm, because they both are subject to the influence of similar factors. However, while the resource‐based view predicts that technological differences between the patented environmental innovations owned by a firm and those in the industry as a whole will positively affect the firm's environmental innovations, the institutional perspective predicts a negative relationship. Our results derive from a sample of 5537 environmental patents from 59 large companies in the electrical components and equipment industry worldwide, and show a positive relationship between patented environmental and non‐environmental innovations in a firm, but a negative influence on the number of the firm's patented environmental innovations resulting from differences between the firm's environmental technologies and those generally prevalent in the industry. Copyright © 2015 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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".