Should an organisation join a purchasing group?
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
Purpose The article deals with issues such as the size of a purchasing group, the types of benefits aimed for, and the real beneficiaries of purchasing groups. Design/methodology/approach The observations are based on the literature, as well as on interviews, mostly with Canadian and US health‐care managers. Findings Although often associated with the public sector, purchasing groups are also an alternative considered more and more by managers of the private sector. A purchasing group increases volume consolidation, making it possible to have only one negotiation, in order to increase the purchasing group members' power vis‐à‐vis that of its suppliers. However, a purchasing group also constitutes an additional link in the supply chain and its objectives could go contrary to those of some of its members. This is why organisations considering joining a purchasing group should analyse this option strategically, in order to assess correctly the potential long‐term benefits. Originality/value This article suggests key questions and an analytical framework to help managers assess the potential benefits and drawbacks of joining a purchase group.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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