Digital Transformation as a Business Sustainability Instrument
Bibliographic record
Abstract
In recent years, companies' contribution to achieving the sustainable development of countries has been significant, especially in an environment of dizzying and unpredictable business changes in most business sectors. A business environment where companies need to continuously improve their ability to develop and maintain a competitive advantage. To face these environments and be sustainable over time facing new forms of business management, it is essential to join the digital revolution through a digital transformation which is a process that aims to optimize a company by promoting changes in its characteristics by combining information technologies, automation, communication and connectivity with priority in a strategic and aligned way according to the evolution in tastes and preferences of us individuals. The objective of this paper is to share a review of both concepts aligned with each other: Digital transformation and sustainability as a basis in their current relationship to raise from the business vision the new competitiveness consolidated in technology to adapt to business challenges and the dynamics of changes in business preferences.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| 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".