Bibliographic record
Abstract
Title: Environmental Consideration in purchasing activities – A case study of Gambro Seminar date: 2012-05-30 Course: Master thesis in business administration, 30 University Credit Points (30 ECTS) Authors: Nicklas Eden, Emelia Hjortenholt Advisor/s: Per- Magnus Andersson Five key words: Management Control, Environmental Management, Green Supply, Purchasing Function, Purchasing Process Purpose: The Purpose of this thesis is to describe and analyze the environmental considerations taken within Gambro’s purchasing function and discuss how this can be improved in purchasing activities at Gambro as well in other Corporations Methodology: Case study of a single purchasing function within the case object Gambro in Lund Theoretical perspectives: Purchasing, Green Supply Empirical foundation: Interviews conducted with purchasing managers, purchasers, product development engineer, environmental manager and a complementary interview with transport purchaser at Tetra Laval in Lund. Internal documents describing purchaser work processes and environmental goals Conclusions: The result of the thesis presents indications that the degree of cost-orientation, regulation and support from the board of directors affects the ability to implement Green supply within the purchasing function. The presence of these conditions was identified as important factors determining Gambro’s ability to work with Green supply
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".