ALONE OR IN COOPERATION: WHAT IS THE BEST STRATEGY FOR THE PERFORMANCE OF RADICAL PRODUCT INNOVATION IN THE VIDEO GAME INDUSTRY?
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
The aim of this research is to study the impact of inter-organisational strategies on performance of radical product innovation. We distinguish three kinds of strategies: (1) individual strategy, (2) cooperation with non-rivals strategy, and (3) coopetition strategy. We study innovation at the product level, and we analyse the market performance. We develop and test the hypotheses comparing the effects of these three strategies on the market performance of radical product innovation. An empirical research is carried out to study the video game publishing industry. We perform a quantitative analysis on a sample of 100 video games that involve radical innovations, identified among 822 video games launched between 2006 and 2011. The main results show that coopetition is the most fruitful strategy for developing a radical innovation. In this process, a direct competitor becomes the best and the most viable partner for that type of innovation.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it