Network patterns and competitive advantage before the emergence of a dominant design
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
Abstract This study examines the performance implications of the alliance networks of 49 firms that competed for two technology standards in the U.S. local area network industry from 1989 to 1996. During the race to define a dominant design, individual firms attract the suppliers of complements by building alliance networks to favor the firms' preferred technology standard. Controlling for the number of suppliers in each technology standard community and the extent of technical progress achieved by individual firms, the panel data analysis shows that central firms with high ego network density, coupled with a strategic intent to acquire and share knowledge broadly within the technological community, achieve better innovation performance. The size of the technological community and some random events in the early formation of the industry do not provide a sufficient explanation of how these firms gain the diverse support of suppliers or enhance their competitive advantage. By demonstrating the independent and contingent effects of alliance network properties, this study explains how network patterns might enhance or limit the benefits of alliance networks when focal firms embrace different innovation strategies. Copyright © 2009 John Wiley & Sons, Ltd.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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