Coordinating a Semi‐Centralized Global Production Network Through Different Levels of Headquarters Involvement
Bibliographic record
Abstract
Motivated by our experience with a global company, we propose and study the concept of a semi‐centralized supply chain and analyze its coordination issues. We focus on a supply chain consisting of a home plant and a foreign branch, both of which are under the same parent company but have considerable autonomy. The role of the home plant is to provide a key component to the foreign branch with guaranteed service (required by the headquarters). Because of a high fixed order cost, the branch orders the component rather infrequently, causing high expediting costs at the home plant. Our purpose is to help the headquarters to improve the supply chain efficiency. We show that under certain conditions, the headquarters can coordinate the supply chain by setting an upper bound on the expediting frequency. If these conditions fail to hold, a simple fixed cost‐sharing contract coordinates the supply chain. When centralized control is too costly or infeasible, the headquarters may delegate the contract design rights to the subunits. If the home plant receives the rights, the supply chain performance can be significantly improved (sometimes to near optimality). These results provide guidance to the headquarters on whether, when, and to whom to delegate the coordination initiatives.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".