Exploring interrelationships among barriers and enablers of green procurement for a sustainable supply chain
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
This study aims to visualise the prioritisation and interactions of ecologically responsible goods in the pharmaceutical industry between obstacles and enablers to green procurement. For this purpose, ten barriers and nine enablers are identified through an exhaustive analysis of the literature, and their interconnections are visualised by implementing the grey-DEMATEL technique. This study offers a unique perspective of having barriers and enablers interplay for green procurement together simultaneously. The findings also indicate that the pharmaceutical manufacturers should provide consumers with relevant, supportable information to disperse their products' sustainability. Also, pharmaceutical industry should spend much in increasing consumer understanding of the effects of collective buying actions. Other identified enablers would help mitigate the obstacles in this industry. This study offers crucial insights into the interdependencies between barriers and enablers that also lead to the decision-making initiatives of management that promote the adoption of environmentally sustainable goods by customers.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| 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 it