Board-related processes and innovation in small and medium-sized enterprises: A continuum logic and configurational approach
Bibliographic record
Abstract
This article identifies configurations in terms of original board-related processes (i.e., establishment, integration, centralization, and bureaucracy) that can stimulate innovation. A singular theorization is developed around a continuum logic and various theoretical postulates. Its experimentation via a configurational approach (Fiss, 2011; Furnari et al., 2021; Misangyi et al., 2017) has been applied to data collected through a survey of 300 small and medium-sized enterprises (SMEs). Ultimately, the results show that innovation may result from complex combined effects between four board-related processes that occur at different times (i.e., upstream, midstream, and downstream) and evolve according to SMEs’ bi-dimensional level of growth (i.e., size and age). Thus, this study notably goes beyond the simplistic view that currently prevails in the literature regarding the hypothesis of linear links between the board of directors (BoD) and innovation. By the same token, this work emancipates itself from the tendency to establish hierarchies implying that certain isolated elements would necessarily be pre-eminent regarding innovation. These findings, which integrate the necessary nuanced approach when studying such a complex phenomenon, have made it possible to generate multiple contributions, both theoretical and practical.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".