Innovation strategy in the US: top executives offer their views
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
Purpose – The USA is the world’s largest economy, but is it a leading innovation nation? As economies mature and slow in growth, innovation will prove to be a key driver in maintaining transient advantage. This article presents a pulse on innovation in the USA as F1000 C-suite executives weigh in on their organization’s innovation health. It also compares the US score with proxy benchmark measures in other countries, and provides operational and strategic considerations to advance innovation platforms in US organizations. Managers will gain insight into common hurdles faced by some of America’s most prominent companies, as well as how to improve innovation practices in their own organization. Design/methodology/approach – This current article reports on findings of innovation health in the USA based on responses from 1,127 F1000 executives (manager level and higher). F1000 executives report their innovation culture through completion of an innovation culture model survey developed by the authors. The F1000 is a listing created by Fortune magazine detailing the 1,000 largest companies in the USA based on revenues. This survey is considered one of the largest surveys on innovation culture in the USA to date. Findings – One of the leading questions that this survey set out to answer is the current measure of innovation orientation amongst America’s largest organizations. Our findings suggest that US business is just beginning to catch the wave of innovation. Other major findings include: innovation amongst the F1000 is average at best; innovation is random and incremental; innovation strategy is missing in most organizations; there is an executive/employee innovation perception gap; innovation governance is missing; employees can not be blamed for a lack of innovation; and companies that fail to innovate will struggle even more. Practical implications – There are a number of operational and strategic considerations presented to support the advancement of innovation in organizations. These include considerations around the leadership, resources, knowledge management and execution to strategically support innovation. Originality/value – This is an original contribution in that it uses a scientifically developed model to measure innovation culture. It is the largest survey of innovation to date amongst the US Fortune 1000, and the finding present considerations to advance the innovation agendas of organizations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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