To cooperate or not? The cooperation conditions of different new energy vehicle manufacturers on power battery under government subsid
Bibliographic record
Abstract
To stimulate the new energy vehicle (NEV) market, China has raised the bar for NEV subsidies so that only NEVs with high endurance are eligible for subsidies. As a result, the NEV manufacturers may cooperate on power batteries, which makes their relationship shift from competition to downstream competition and upstream cooperation, i.e. co-opetition. Based on this, this paper investigates the cooperation conditions between the leading NEV manufacturer and the emerging NEV manufacturer on power batteries under the revised subsidy policy. By establishing a Cournot model, we first analyze the optimal decisions of the two manufacturers under government subsidy policy in competition and co-opetition scenarios, respectively. By comparing the profits of NEV manufacturers in these two scenarios, we derive the conditions under which they can cooperate on power batteries. The results show that whether the NEV manufacturers can cooperate depends on the power battery cost of the emerging NEV manufacturer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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; a candidate call from one teacher head, 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".