Unravelling the Effects of the Environmental Technology Portfolio on Corporate Sustainable Development
Bibliographic record
Abstract
Abstract A firm's environmental technology portfolio comprises of a heterogeneous class of technologies, each with distinct economic and environmental implications. Having a portfolio with a proper mix of different technologies is critical in achieving economic and environmental goals. Using data on major United States’ corporates, I identify five types of environmental technologies: pollution control, eco‐efficiency, green design, low‐carbon energy, and management systems. I find that the composition of the environmental technology portfolio affects a firm's performance. Most notably, raising the share of low‐carbon energy and pollution control technologies in the portfolio can negatively affect economic performance. But both low‐carbon energy and pollution control are effective in improving carbon productivity. The other technologies do not display significant impacts on firm performance. The results highlight that firms should take the differential effects of environmental technologies into consideration when designing an adequate technology portfolio to attain desired economic and environmental objectives. Copyright © 2018 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 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".