Profit sharing, industrial upgrading, and global supply chains: Theory and evidence
Bibliographic record
Abstract
Abstract This research constructs a simple model to illustrate the global supply‐chain (GSC) profit sharing and industrial upgrading mechanism, finding that the average profitability distribution in the different supply‐chain stages is determined by three main conditions: (1) the average product of the labor in the firms at each production stage; (2) the production complexity level of each production stage in the chain; and (3) the ratio of the output elasticity of capital to the output elasticity of labor in each stage. This study also proposes a new industrial upgrading mechanism, the “smile‐curve‐driven supply‐chain upgrading,” for supply‐chain firms. Increases in production complexity and level of factor intensity in each production stage are found to be the two essential conditions for the smile‐curve‐driven supply‐chain upgrading. Our static and dynamic panel empirical models, including robustness checks, are both broadly consistent with the theoretical predictions of this paper.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".