Bibliographic record
Abstract
The article is devoted to the theoretical-scientometric analysis of the role of innovations in the process of business transformation with an emphasis on strategic planning, change management, and adaptation to new market conditions. A comprehensive bibliometric analysis of scientific publications on the topic "Innovation as a catalyst for business" was conducted to achieve the goal. A corresponding search query in the Scopus database generated the publication input array. Further scientometric analysis was carried out using R Studio software, R language, Shiny, and Biblioshiny packages (for data analysis and visualizations in the form of keyword cloud, treemap, keyword compatibility network, and thematic map). In addition, a statistical data analysis was carried out to assess the impact of digital transformation on the economic growth of countries and the productivity of enterprises. A comparative analysis of data from different countries (USA, Great Britain, Canada, Japan, France, Italy) made identifying general trends and features possible. An effective national system that promotes the generation and implementation of innovations is the key to the country's successful development, and countries that are leaders in technological development set trends for the entire world economy. As a result of the study, it was substantiated that innovation is a crucial factor in the development of modern business. Digital transformation, as an integral part of the innovation process, allows companies to optimize processes, personalize interaction with customers, and increase efficiency. The analysis of scientific publications showed that the main research directions in the context of innovation as a catalyst of business transformations are focused on issues such as digital transformation, artificial intelligence, big data, sustainable development, and innovative business models. The scientific novelty of the conducted research is the substantiation and addition of existing knowledge about the role of innovation in business transformation through detailed scientometric and bibliometric analysis of scientific publications and visualization of research results. The research results can be used by company managers, scientists, and policymakers to develop innovation strategies, assess the impact of innovation on business, and develop recommendations for implementing innovative technologies.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".