Harness collaboration between manufacturing Small and medium-sized enterprises through a collaborative platform based on the business model canvas
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
Innovation, open innovation, and collaborative platforms are concepts in effervescence in the last few years. Innovation’s future will observe a growing number of collaborations. The links between collaboration and collaborative platforms are known in the transport and accommodation sector (such as Uber) however are less used in manufacturing. This paper aims to identify the main challenges between manufacturing firms which intend to collaborate enabled by a prototype platform. A collaborative business model was designed using the business model canvas and tested using a real case to generate valuable collaboration. Collaboration experimentation was monitored over 21 weeks between two firms of the Quebec aerospace cluster and ended with a semi-structured interview. Six challenges were identified: partner selection, commitment and trust, intellectual property management, collaboration evaluation, collaboration symmetry and terminology difficulties. Suggested solutions included, compatibility criteria between the partners, creating a vocabulary lexicon, and establishing collaboration expectations prior to collaboration.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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