A hybrid multi‐criteria decision‐making approach to evaluate interrelationships and impacts of supply chain performance factors on pharmaceutical industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Pharmaceutical Supply Chain (PSC) plays a critical role in the healthcare sector. This study identifies, validates, and prioritises the factors that play a crucial role in PSC performance, adopting a threefold approach. In the first stage performance, indicators were identified through an extensive review of the literature. With the help of expert opinion, the identified factors were validated and then categorised based on technological—organisational—environmental (TOE) and supply chain (SC) theories to propose a framework. The Pakistani Pharmaceutical sector firms were selected to investigate the cause and effect relationship among the factors, their interdependencies, and impact on overall PSC performance. This investigation was supported by a novel integrated analytic model composed of best worst method (BWM), decision‐making trial and evaluation laboratory (DEMATEL), and analytical network process (ANP) methods. The results indicate that ‘human resource skills, competencies, and involvement’, ‘process improvement and healthcare reform, and manufacturing’, and ‘distribution and inventory management’ are the top three factors that have a high impact on the overall PSC performance. This study outcome help inform decision‐makers and managers in the healthcare sector in formulating strategies to improve their SC performance.
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.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it