Managing Value Co-Creation Through Interfaces with Suppliers
Bibliographic record
Abstract
reliance on purchasing and supply management. This means that an increasing proportion of value is createdoutside the boundaries of the firm, namely by suppliers. In this context, the paper aims to relate the configurationof the bonds companies establish with their suppliers to the process of value creation. On the basis of a casestudy approach, the paper furthers our understanding of buyer-supplier relationships as mechanisms for thecoordination and development of capabilities on both sides of the dyad. Evidence was found that relationshipsaffect not only the access and exploration of suppliers’ resources, but also the perception the buying firm hasabout their capabilities which is likely to condition the potential for joint value creation. The main contributionof the paper is that co-creating value with suppliers is not a recipe. It is not the ‘right’ solution in all instances.Rather, value co-creation involving suppliers must be regarded as a strategic option which depends on severalconditions. This research puts in evidence two of these conditions: suppliers’ capabilities and the way thebuyer-seller relationships are configured.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".