Exploiting Synergies to Leverage Operational Performance and Efficiency with Collaborative Business Strategies
Bibliographic record
Abstract
Resource and knowledge recombination activities of manufacturers, suppliers, and service providers have evolved with the advent of globalization and increased market complexities. Such changes in resource and knowledge recombination activities have enabled and advanced the relevance of well-forged and properly implemented collaborative partnerships. Collaborative partnerships are credible alternatives in the provision of goods and services. The participants in this multiple case study design were 12 senior business managers from three oil, gas, and energy companies in a metropolitan area in a western province of Canada. Participants revealed the strategies they used to forge profitable collaborative business partnerships. The resource-based view (RBV) and the relational view (RV) constituted the conceptual framework of this study. Data were collected were using semistructured face-to-face interviews and analysis of organization documents. Member checking preceded the final data analysis process. The modified van Kaam method served to manage the emerged themes. Themes that emerged from data analysis included planning, organizing, and managing work; decision-making; leadership; people, relationship management; and managing complexities. The findings of this study may contribute to social change through the interdependencies that collaborative partnerships promote and encourage among employees of the collaborating organizations. Collaborative partnership interdependencies create the opportunities and conducive environments that might enable people from different cultures, and with different and inimitable capabilities, skills, and resources to cohabit peacefully and to work together productively.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".