A MULTI-COUNTRY COMPARISON OF PERCEIVED ENVIRONMENTAL CHARACTERISTICS, INDUSTRY EFFECTS, AND PERFORMANCE IN ENTREPRENEURIAL FIRMS
Bibliographic record
Abstract
This paper examines the relationship between industry effects, environmental perceptions, and firm performance in a multi-country sample of entrepreneurial firms. Using a sample of 1045 finalists in Ernst & Young's International "Entrepreneur of the Year" competition, we examined whether environmental constructs that have been studied and validated in North American entrepreneurship research were generalizable to firms in fifteen countries located in Europe, Asia, and Africa. Using measures common to North American entrepreneurship research; we identified two environmental dimensions in subsamples of North American (United States and Canada) and non-North American firms: dynamism and hostility. However, while the constructs were identified in both subsamples, they also were not significantly associated with firm performance. We conclude the paper by suggesting this lack of environmental perception-firm performance relationship may be attributable to an entrepreneurial mindset that focuses on identifying and recognizing specific opportunities rather than responding to general characteristics of the external environment.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".