“Diseño, elaboración e implementación de un plan de negocios, para la empresa comercial it_control, que permita fortalecer la imagen corporativa, en la ciudad de Riobamba en el cuarto trimestre del 2016”.
Bibliographic record
Abstract
This research is about "Design, Development and Implementation of a Business Plan for the commercial company It_Control, which will strengthen the corporate image, in the city of Riobamba, in the fourth quarter of 2016", the inquiry was made With the main objective of strengthening the corporate image, thereby creating their identity; Which implies a better positioning, prestige, credibility, self-esteem, which leads to greater opportunities for the company in the regional market. To carry out a business plan in It_Control company, it is providing the necessary tools in the company, such as organizational, process, marketing or financial, to make decisions based on actual information, which will translate into effective information, Every organization should direct its efforts to establish a strong, coherent and distinctive corporate identity (of its products and / or services and of the organization itself) and communicate it appropriately to its public. In the research, a non-experimental-transectional design was used, which allowed the collection of qualitative and quantitative information through techniques such as surveys, 76.70% of the sample in a single moment, in a single time, and also quasi- Experimental study because 23,30% of the sample obtained from the population of the city of Riobamba, measurements were made to a certain group of people before and after the introduction of the experimental variable, that is to say, the strengthening of the corporate image, sustained In a theoretical framework that serves as a fundamental basis for the practical proposal that is formulated. With the implementation of the business plan according to the needs detected in It_Control Company, problems were detected in certain processes, lack employers empowerment was noticed so it was adopted appropriate techniques in each departmental area, in order to decrease these difficulties. The success of the organization will depend on the approach that is given to both aspects in the level of decision making and from there that a wrong policy in the image strategy affects its development and survival.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".