Estrategias de internacionalización para incrementar el nivel de exportación de la cebolla roja producida por la empresa Gicade SAC hacia el país de Canadá - Vancouver, 2016
Bibliographic record
Abstract
ABSTRACT \nThrough a research study applied to company GICADE SAC, in Trujillo city, in 2016, which is \ndedicated to the production and exportation of red onion that also has a high demand both nationally \nand internationally, of which the main internationalization strategies carried out an arduous \ninvestigation, which helped us to identify the appropriate strategies that allow to increase the level of \nexport of the red onion produced by the company GICADE SAC to the country of Canada - \nVancouver. \nAnalyzing the main importing countries, we found that Canada is ranked among the top 10 onion \nimporters, whose main city is Vancouver, and which has a great influence on the product´s \nconsumption. Regarding the research, it was decided to apply the localization strategy and the entry \nand stay strategy, which would benefit both the company and the national market for national onion \nproduction. \nIn order to gather necessary information, we used the appropriate instruments that facilitated the \ninterview, the bibliography sheet and the data index. Due to what we used the method of the \nsynthesis analysis that allowed us to interpret the interviews, the theory found for the theoretical \nframework and the data index of exports. \nAlso, in applying this research, we were able to measure the internationalization strategies that are: \nlocalization strategies, entry and stay strategy, growth strategy, coexistence strategy, corporate \nstrategy, internationalization strategy, competitive strategy, Structure, focus strategy and sequence \nstrategy. However, the location strategy and the strategy of entry and permanence are the two \nappropriate, so that the company GICADE SAC, have a better acceptance in the international market \nand in decision making.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".