What Will the Future Bring? Dominance, Technology Expectations, and Radical Innovation
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
Are dominant firms laggards or leaders at innovation? The answers to this question are conflicting and controversial. In an attempt to resolve conflicting answers to this question, the authors argue that dominance is a multifaceted construct in which individual facets result in differing (and countervailing) propensities to innovate. To identify the overall effects of dominance, it is necessary to consider the effects of these facets taken together. The authors also study a hitherto ignored yet important driver of innovation, technology expectations, and show that managers have widely divergent expectations of the same new technology. Furthermore, even when their expectations are the same, managers of dominant firms display investment behavior at odds with their counterparts at nondominant firms. The authors use a triangulation of research methods and combine insights from lab studies with those from field interviews, archival data, and a survey of bricks-and-mortar banks’ responses to Internet banking.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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