Digital Transformation for Sustainability: A Qualitative Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the digital era, finding a new way to conduct business becomes mandatory. The risk of disruption, the bloody competition, the change in customer behaviours and the scarcity of resources, these are few of many drivers that force companies to change their business models and adapt to the new market reality. Digital transformation emerged as a recent concept that help companies to best leverage digital capabilities such as Big data, Internet of things, Cloud Computing and Artificial Intelligence. The purpose of this paper was to conduct a qualitative analysis on three big size companies in order to enrich the literature on this concept and to discuss whether or not companies could reach sustainability during their transformation journeys. The three in-depth case studies showed that customers, data, competition and innovation are four dimensions of digital transformation that have an impact on the companies’ sustainability actions. We proposed at the end of the article a future research model, composed of 5 hypotheses, to be validated by a future empirical study.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.032 |
| Open science | 0.000 | 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 it