<論文>Risks in Service-Oriented Manufacturing Supply Chains: Current Insights and Implications
Bibliographic record
Abstract
This research presents an analysis of the risks associated with the service-oriented manufacturing supply chain based on the contingency theory. It aims to offer a comprehensive overview of the existing information by identifying and categorising diverse hazards into three primary tiers of risk determinants. The present research utilises a generic Risk Breakdown Structure (RBS) as a foundation but focuses on a particular industrial context to examine and validate hazards identified in the existing literature. Leveraging the Fuzzy Delphi-Analytic Hierarchy Process (AHP) technique, information was gathered from 50 local construction specialists, including government representatives, consultants, contractors, and clients. We propose formulating a comprehensive definition for a service-oriented manufacturing supply chain grounded on its fundamental significance within the contemporary economic landscape. Researchers and practitioners can consider a comprehensive list of seven risk categories: demand, supply, operations, information, finance, time (delays), and external sources (human-made or natural-related). These categories provide valuable insights into potential risks associated with various aspects of a given context. This study is one of the first research endeavours to provide the notion and attributes of the service-oriented manufacturing supply chain. The Fuzzy technique is employed to produce comprehensive and industry-specific Resource Breakdown Structures (RBSs) inside a singular investigation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".