Synergistic Impacts of Entrepreneurial and Learning Orientations on Performance: A Meta-Analysis
Bibliographic record
Abstract
Entrepreneurial orientation (EO) and learning orientation (LO) are two key strategic orientations that are thought to individually influence firm performance. However, there is little understanding regarding their mutual relationship – similarities and complementarities – and their combinative effect on performance. To address this, we meta-analyzed 60 samples from 59 studies based on 16762 firms using a random effects model, to find the relationships between EO, LO, and firm performance. We find that the correlation between EO and LO is fairly large (r = 0.44) and is moderated by the country’s entrepreneurship profile, represented by entrepreneurial intention and fear of failure. While EO and LO operate through similar processes, they have independent, additive and synergistic effects on performance. EO and LO explain 17% and 13% of performance respectively while synergistically explaining 21% when combined. Furthermore, the EO-LO intercorrelation moderates the EO-performance and LO-performance relationships, so under conditions of high association, their combined effect can reach 38% of the performance variance.
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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 | 0.022 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".