Technology Vision for Radical Innovation and Its Impact on Early Success
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
For firms involved with the very early stages of emergent radical innovation, technical goals are often held in the mind(s) of only one or a few individuals. The way these individuals mentally imagine or visualize such goals, or “technology visions,” provides an important looking glass for understanding a firm's progression along the path of involvement from a technical discontinuity toward project‐level and organizational‐level involvement with a given technology. Utilizing a large sample of firms engaged in radical innovation in N orth A merica and the U nited K ingdom, this empirical study examines the impact of five dimensions of technology vision on early success: benefits goals, efficiency goals, magnetism, specificity, and infrastructure clarity. Technology vision is found to have a significant positive impact on technical competitive advantage, early success with customers, and ability to attract capital, as measures of early success.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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