Influence of information and communication technologies on the competitive advantage of micro-enterprises – Huancayo
Bibliographic record
Abstract
In a context where ICTs are indispensable elements for the development of business activities, it is necessary to know their influence on the internal improvement of processes. This research seeks to establish the influence of ICTs on the competitive advantage of micro-enterprises in Huancayo 2024. Research developed under a basic type study, has a quantitative approach with a correlational and cross-sectional level, the sample was made up of 59 entrepreneurs in the bakery sector in the province of Huancayo. Data analysis and processing was carried out using structural equations based on PLS. The study obtained the following results: a Sperman 's Rho correlation coefficient of 0.821 with a significance level of ,000 which shows a high and positive degree of influence between ICTs and competitive advantage as well as its different dimensions Level of use, alignment of use and training; Likewise, the general hypothesis is accepted, which establishes that there is a significant relationship between Information and Communication Technology ( ICTs ) and the competitive advantage in SMEs in the pastry sector - Huancayo 2024.
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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 | 0.001 | 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 | 0.000 | 0.004 |
| 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 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".