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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".