Business practices of highly innovative Japanese firms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Highly innovative firms are more competitive and achieve greater performance than their less innovative counterparts. Innovation orientation has been commonly used to assess an organization's innovative culture. To date, most innovation orientation research has explored its relationship with performance. However, the literature is unclear as to what innovative companies do differently to achieve superior performance. This study advances innovation orientation research by examining differing business practices of high versus low innovative Japanese firms. The various business practices include culture management, open innovation, analytics, innovation management software, crowdsourcing, design thinking, measuring innovation, stage-gate, and scientific discovery. Using data from 261 Japanese firms, this study finds that high innovators, as compared to low innovators, are more likely to engage in many of these business practices. Until this study, some of these business practices were not empirically shown to be correlated with high innovators, much less explored in the same study. This paper also offers a stepwise approach for executives seeking to enhance competitiveness via innovation. Specifically, executives should first look to creating an innovation orientation and subsequently implement such business practices.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it