Motivation for firm ECSR: Firm’s CO2 emissions and Search for Renewable Energy Technology
Bibliographic record
Abstract
Research in environmental corporate social responsibility has mainly focused on external pressures as determinants of firms to engage in eco-friendly behaviors. However, firms are heterogeneous in executing environmental behaviors, which cannot be explained solely by external factors. What motivates firms to engage in proactive environmental behavior, in particular, searching for environmental technology? This study tries to answer this question using the difference between the firm’s CO2 emissions and their aspiration levels, and examines how this gap affects a firm’s renewable energy technology search behavior. By testing our hypotheses within renewable energy technology search behavior of U.S. Fortune 500 information, communication, and technology firms from 2010 to 2018, we find that firms are more likely to search for renewable energy technology as the gap between firms’ CO2 emissions and aspiration levels widens. When a firm’s CO2 emissions is greater than aspirations, the impact of social gap on searching behavior is greater than the impact of historical gap. On the contrary, when a firm’s CO2 emissions is less than aspirations, the impact of historical gap on searching behavior is greater than the impact of social gap.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".