Inter-Organizational Collaboration in Dynamic, Short-Term Supply Chains
Bibliographic record
Abstract
A new network organizational form, called dispersed manufacturing network or DMN, is emerging among companies' supply chains. The organizational form is both abetted as well as spurred by the increasing globalization of supply chains. This organizational form takes shape in the form of networks of dynamic and flexible supply chains held together by emergent and easily re-configurable short-term collaborative links between partners. Globalization allows more companies to connect and to collaborate with one another irrespective of distance or boundaries. However, globalized business environments are also more turbulent and complex. These give rise to the need for flexible DMN networks that are robust to unpredictable changes. Researchers need to identify and understand the new rules of engagement among companies that inform this novel organizational form. This chapter provides explanations for the emergence of such networks, describes their advantages, and show examples of such supply chains in the field. The chapter's domain covers the following supply chain areas; Design of supply chains Agility of supply chain Decision making in a supply chain Supply chain collaboration
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.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".