Development of a multidimensional scale to measure organizational creative capabilities
Bibliographic record
Abstract
Abstract Although the literature's case and longitudinal studies provide ample evidence of organizational routines that foster creative behaviors, it still lacks an integrative model of organizational creative capabilities (OCCs) and the quantitative evidence to validate such a model. This research is aimed at conceptualizing and developing a reliable and valid scale for OCCs. First, we define the OCC construct's domain by conducting an extensive literature review. We then generate a list of items for the five dimensions of OCCs through a qualitative study involving a group of 24 practitioners (Study 1a) and by surveying nine senior researchers (Study 1b). We refine the OCC scale using a sample of 269 responses collected in France and Canada (Study 2), and we conduct a first‐order confirmatory factor analysis (Study 3). Finally, we perform a second‐order confirmatory analysis (Study 4a) on samples of 220 responses collected mainly in the United States and Europe, generalize our results to a sample of 205 responses, and strengthen the predictive validity (Study 4b). Our results provide significant evidence that OCCs can be conceptualized around five dimensions: internal socialization routines, idea management routines, external openness routines, creative equipment routines, and internal agility routines. Furthermore, the research confirms the scale's good psychometric qualities, thus ensuring that researchers can be confident in the reliability of any future academic research design using the scale. We also validate the OCC scale's predictive validity by verifying that a five‐dimensional reflective scale with 16 indicators has a significant positive effect on the creative outcome. This OCC scale can be used by practitioners to better understand the organizational routines they have to develop in order to strengthen their organization's creativity. It also provides a way for longitudinal studies to observe how OCCs evolve over time.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".