The Influence of Strategic Alliance on Competitive Advantage through Market Area and Product Innovation
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
This study is aimed to prove the implementation of strategic alliance can increasing competitive advantage of wood industry of Perhutani through develop of market area and market innovation. Based on the results of hypothesis testing and the analysis of strategic alliances, market area and product innovation against competitive advantage, it is known that building a competitive advantage in the timber industry forestry can be achieved through the establishment of strategic alliances right, based on the exchange of raw material resources, technology or resources marketing. Strategic alliances are used to strengthen the position of the timber industry in the face of competition forestry business. The more precise the model selection strategic alliance Perhutani timber industry will be able to build competitive advantage of her. The development model of strategic alliances Perhutani timber industry that needs to be developed is to increase the competitive advantage has the form of an alliance focused on cooperation in provision of raw materials, interest in improving the skills of cooperation and the application of the production process technology.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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