Assessing subsidy policies for green products: operational and environmental perspectives
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This paper studies the impacts of two government subsidy policies, a fixed amount subsidy and discount subsidy, on the environment and operations of a two‐echelon supply chain, where the supply chain serves the market with either a marginal cost intensive green product (MIGP) or development‐intensive green product (DIGP). We first derive the equilibrium unit greenness level, pricing decisions, and the resulting economic and aggregate environmental performances. Then, we compare the effects of the two subsidy policies for the MIGP and DIGP with and without a total subsidy budget constraint. The main results are as follows: (1) We identify the congruence regions (conflict regions) within which one subsidy policy dominates the other according to all (some) criteria. (2) With the budget constraint, the fixed amount subsidy outperforms the discount subsidy for both MIGP and DIGP in terms of the unit and aggregate greenness levels.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it