Regional-level coopetition strategies and company performance: evidence from the Canadian wine industry
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
Regional-level coopetition (collaboration among competitors in rural communities) has been linked to company performance. That said, there could be conditions (moderators) that help or hinder these networks from fulfilling such outcomes. This investigation examines the nature of the relationship between regional-level coopetition and company performance under key moderating effects. A resource-based theoretical lens is utilized to underpin the study. Following field interviews to shape the operationalizations and survey instructions, a quantitative study was undertaken in the Canadian wine industry to test the elements of the conceptual framework. The findings revealed that while regional-level coopetition drives company performance, regional-level rivalry negatively impacts this association. Surprisingly, industry experience intensified the potential dark-sides of these activities. As such, improved evidence has emerged on how coopetition strategies can be implemented in rural communities through the underlying mechanisms that can assist decision-makers of small enterprises to enhance their performance. Additionally, stronger insights are offered regarding a relational, stakeholder perspective of resource-based theory, in terms of how decision-makers may need to work with complementary and trustworthy rivals that can assist them to increase their company performance in competitively intensive environmental-level conditions.
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 | 0.001 | 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