Open and Digital Innovation: Intellectual Structure, Global Trends, and Future Research Directions
Bibliographic record
Abstract
Advancements in open innovation and digital innovation have reshaped how firms manage their innovation processes. This study investigates the intellectual structure of current open innovation and digital innovation research, reporting on a scoping review using bibliometric and science mapping techniques. Through analysis of 261 journal articles published between 2015 and 2025, three research clusters were identified: (1) digital innovation and industrial research, (2) sustainability-driven strategic innovation, and (3) collaborative decision-making. The study highlights the significant growth in academic output and emphasizes the reciprocal relationship between digital transformation and open innovation, particularly within SMEs and platform-based ecosystems. Gaps in current research are identified in the contexts of digital product ecosystems, decision-making in innovation networks, and ethical considerations. This study provides both theoretical and practical insights for innovation management, emphasizing sustainability and platform-centric business models.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.026 | 0.039 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".