More than a quarter century of <i>Creativity and Innovation Management</i>: The journal's characteristics, evolution, and a look ahead
Bibliographic record
Abstract
When this journal was founded in 1992 by Tudor Rickards and Susan Moger, there was no academic outlet available that addressed issues at the intersection of creativity and innovation. From zero to 1,163 records, from the new kid on the block to one of the leading journals in creativity and innovation management has been quite a journey, and we would like to reflect on the past 28 years and the intellectual and conceptual structure of Creativity and Innovation Management (CIM). Specifically, we highlight milestones and influential articles, identify how key journal characteristics evolved, outline the (co‐)authorship structure, and finally, map the thematic landscape of CIM by means of a text‐mining analysis. This study represents the first systematic and comprehensive assessment of the journal's published body of knowledge and helps to understand the journal's influence on the creativity and innovation management community. We conclude by discussing future topics and paths of the journal as well as limitations of our approach.
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.030 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.027 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".