Process of Innovation and Its Impact on a Sustainable Development and Digitalisation in the Service Sector
Bibliographic record
Abstract
Abstract Purpose: Process innovations are becoming increasingly significant in a changing digital society. The goal of this study is to focus on the service industry, particularly on how this sector has lately been influenced by sustainable development and digitalisation. The main focus will be on education. The cohabitation of three aspects (innovation, digitalisation, and sustainability) is declared as a fact in the competitive landscape. Methodology: This study uses a multi-case approach emphasising the new system of processes in educational institutions in Canada, Ontario. These case studies are relevant to exceptional results consistently produced by various educational institutions. Findings: The Waterloo region is known as a digitalisation triangle in Canada. Personal experiences and research findings serve as an example of the value of the global digitalised economy as a partnership principle in the educational and entrepreneurship fields. Significance: The obtained experience and the attempt to share the knowledge and results of this work and research will be useful in future for other academic environments, cities, and countries. Practical Implications: Cohesion between the purpose of this study and practice is explained as a need to see educational institutions as an important factor of innovation and economic development. In this case, the author shows how this successful case of Ontario, Canada created a stronger base for competitiveness and economic growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".