Relación entre la gestión de la calidad y ventaja competitiva en diferenciación en el área de producción de la empresa Menú Express, en la ciudad de Cajamarca en el primer cuatrimestre del año 2016
Bibliographic record
Abstract
ABSTRACT \nThe aim of this thesis was to determine the relationship between Quality Management and \nCompetitive Advantage in Differentiation in the production area of the company " Menu Express " in \nthe city of Cajamarca in the first quarter of 2016. \nThe research was descriptive, correlational, cross-sectional, not experimental, the population was \ncomposed of 72 people from the production area, between workers and administratives, to which \nwas applied the questionnaire referred to the relation to the planned objective, the same that was \nbuilt on a scale of five alternatives: definitely not, probably not, indecisive, probably yes, definitely \nyes, with values 1, 2, 3, 4 and 5 respectively, valid reliability through the Alfa Cronbach formula, \nwhose result it was 726; demonstrating a high degree of reliability. \nThe technique of analysis focused on descriptive statistics, specifically percentages among the \nresults found that: \nThe 61, 75% of workers felt that there is a media relationship between Quality Management and \nCompetitive Advantage in differentiation, since although there are processes that guarantee the \ndevelopment and safety of products, still need to adopt a culture total quality, build continuity and \norder in procedures also noted that efforts should be recognized, experience and intellectual \ncontribution towards them, creating a participatory management. \nIt was concluded that there is an average positive relationship with a correlation coefficient of \nPearson of 0.445, indicating high concomitance existing between both variables. \nKey words: Quality management, competitive advantage.
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.
How this classification was reachedexpand
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".