A Review on the Integration of Supply Chain Management and Industrial Cluster
Bibliographic record
Abstract
Although Supply Chain Management (SCM) and Industrial Cluster (IC) are two different fields of study, it has been identified that there is a natural and internal relationship between these two theories. Most of research works depict that, integration of the two concepts is in its infancy. The aim of this research is to review the integration between supply chain management and industrial cluster, at the same time to identify the gap and propose solution. To achieve the research aim, two pairs of keywords namely “supply chain” and “industrial cluster” were used, to track literatures from the online databases. The search initially identified over 46 articles. After further screening, they were reduced to 17. Finally, contents of these articles were analyzed based on their general focus area. From the content analysis, considerable evidences are found in the literature review on the integration of supply chain management with industrial cluster. The entire emphasis of the previous researches was on cluster supply chain (CSC) management, which highly promotes efficient operations of industrial clusters. Most of the CSC articles focused on the importance of cluster supply chain. However, there are few researches in the design, implementation and improvement of cluster supply chain. On the other hand, the role of industrial clusters in a global supply chain management and benchmarking of best practices have not yet been given the attention they deserve in previous studies. This is one of the first studies which critically examine researches that deal about supply chain management and industrial cluster integration theories.
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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".