Environmental Preferences and Technological Choices: Is Market Competition Clean or Dirty?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper investigates the joint effect of consumers' environmental concerns and product-market competition on firms' decisions whether to innovate "clean" or "dirty". We first develop a stepby-step innovation model to capture the basic intuition that socially responsible consumers induce firms to escape competition by pursuing greener innovations. To test and quantify the theory, we bring together patent data, survey data on environmental values, and competition measures. Using a panel of 8,562 firms from the automobile sector that patented in 42 countries between 1998 and 2012, we indeed find that greater exposure to environmental attitudes has a significant positive effect on the probability for a firm to innovate in the clean direction, and all the more so the higher the degree of product market competition. Results suggest that the combination of historically realistic increases in prosocial attitudes and product market competition can have the same effect on green innovation as major increase in fuel prices.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 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 it