The limitations of open innovation: an examination of innovation orientation, open innovation and performance in North America
Bibliographic record
Abstract
Purpose Prior innovation orientation research has mostly focused on performance consequences, with some recent work examining its relationship with innovative practices such as open innovation. Yet, despite this growing body of open innovation research, there are still gaps and limitations. Notably, most prior studies have been conducted in Europe, limiting their generalizability to the rest of the world, and are replicative, exploring performance and competitive outcomes. There is very limited work examining the potential limitations of open innovation. This study extends innovation orientation research and examines the limitations of open innovation in North America. Design/methodology/approach This study explores the relationships between innovation orientation and performance, open innovation and performance and innovation orientation and open innovation among 386 North American companies. Findings This study is novel as it examines the relationships between innovation orientation and performance, open innovation and performance and innovation orientation and open innovation among North American companies. The research uncovers a linear relationship between innovation orientation and performance, a correlation between innovation orientation and open innovation and a counterintuitive curvilinear relationship between open innovation and performance. The curvilinear relationship, shaped as an inverted u-shape, suggests there are limitations to the strategy's effectiveness, actionable insight to companies, consultants and scholars alike. In the discussion section, findings are further unpacked with regard to their implications for the scholarly literature. The paper concludes with managerial considerations for creating an innovation orientation and the most effective level of open innovation for maximum competitive and performance implications. Originality/value Beyond the innovation orientation and open innovation research contributions, this study offers managerial insight for executives seeking to enhance competitiveness and drive firm performance.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".