A HAND ON THE RUDDER OF INNOVATION: INVESTIGATING THE INFLUENCE OF BOARD OF DIRECTORS AND TOP MANAGEMENT TEAMS.
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
This study provides one of the rare evidences based on a field study regarding the influence of corporate governance on innovation. Drawing on semi-structured interviews, it investigates how the internal governance chain (board of directors and top management teams) contribute to foster innovation in their organization. The interviewees' statements highlight the considerable impact that directors and managers can have on innovation, and in that sense that they certainly have "a hand on the rudder of innovation". However, the collected data also shows that other factors such as organizational characteristics (e.g. sector of the firm and partners) play a major role, thus revealing that many other aspects and stakeholders also have "a hand on the rudder of innovation". The in-depth analysis contained in the present paper gave rise to a conceptual framework that includes 5 dimensions and 19 sub-dismensions. This framework promotes a more holistic approach when studying the link between the internal governance chain and innovation. It also emphasises the complexity of this relationship and thus helps to better tackle it.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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