Toward supply side incentive: The impact of government schemes on a vehicle manufacturer's adoption of electric vehicles
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
Abstract Besides the consumer subsidy scheme, governments have recently implemented a hybrid scheme with an additional dual‐credit scheme on the supply side. It is important to understand the impact of this new practice on a vehicle manufacturer (VM) that provides gasoline vehicles (GVs) and/or electric vehicles (EVs), and the consumer and social welfare. Implementing the dual‐credit scheme leads to higher prices of GVs and EVs, but the effective price of EVs is actually lower. As the cost difference decreases and consumers’ low‐carbon awareness (LCA) increases, the VM prefers the product choice strategy including EVs under the pure subsidy scheme. Surprisingly, the hybrid scheme makes selling EVs feasible even though the cost difference is high and LCA is low. Although the additional dual‐credit scheme can improve the adoption of EVs, its parameter values should be carefully designed because otherwise it will damage the VM's profit and the consumer and social welfare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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