A Novel Application of a Hybrid Delphi-Analytic Hierarchy Process (AHP) Technique
Bibliographic record
Abstract
This research studies heterarchical collaboration in logistical transport. Specifically, it utilizes a hybrid Delphi-Analytic Hierarchy Process (AHP) approach to explore the relevant criteria for the formation and maintenance of a strategic alignment for heterarchical transport collaboration. The importance of this work is that it applies a novel hybrid approach for identifying criteria for success to a little-studied form of supply chain collaboration: heterarchical collaborative transport. The criteria for this form of collaboration identified by the application of Delphi-AHP include ones from the technical, risk, financial, organizational, and operational categories. This novel application of the hybrid approach leveraged the expertise of transportation collaboration experts from the U.K., France, Canada, Sweden, the Netherlands, and Italy to identify key criteria for a strategic alignment between heterarchical collaboration partners. Such collaborative initiatives are important in industry as an environmentally conscious, yet efficient and effective strategy for the transport of raw materials and finished products in the supply chain.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".