Plan de reducción de gastos operativos y su incidencia en la rentabilidad de la empresa Neomotors SAC, de la ciudad de Trujillo 2018
Bibliographic record
Abstract
ABSTRACT \n \nThe objective of this research is to reduce the operating expenses of the company Neo motors SAC \nof the city of Trujillo for the period 2018, the organization is dedicated to the commercialization of \nnew vehicles of Chevrolet and Izusu brand, as well as to the sale of spare parts and preventive and \ncorrective maintenance of vehicles of the aforementioned brands. \nThe reduction plans are the restructuring of the variable remuneration of the sales personnel (sales \nconsultants and sales manager) who will have commission and bonuses for units delivered to the \nsales advisors and bonus for compliance with the goal for the sales manager, that way we will reduce \nthe commissions paid taking into account that the sales executed in the first quarter 2018 were not \nprojected, however many commissions and bonds were paid under an unconventional structure and \nthat goes to the reality of the income generated by sales. \nIn turn, a new policy was also structured to reduce marketing and logistics expenses, which will only \nbe executed as long as they are contemplated in the annual budget of the company under the \napproval of the Management and Finance area, if not thus, those responsible for the execution or \napproval of expenses will be responsible and will have to assume the excess expense for advertising \n(marketing) and general (logistics) tasks according to the organization's needs. \nIn this way it was possible to reduce the expenses of sales personnel, marketing expenses and \nlogistics expenses, that is to say, a reduction of operating expenses that allow generating an added \nvalue in comparison with the other companies of the item that only point to the increase of income \nas profitability strategy
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".