New-Born Startups Performance: Influences of Resources and Entrepreneurial Team Experiences
Bibliographic record
Abstract
This study examines the interaction effects of entrepreneurial team experiences and resources on new-born startup firm performance, from a contextual view point of entrepreneurship. The sample is from a longitudinal panel data of Kauffman Firm Survey conducted over the period of 2005-2012 by the Ewing Marion Kauffman Foundation. Results suggest that financial resources have positive impacts on startup firms’ profitability; whereas the impacts of initial firm size on profitability are negative. Startups are more likely to be profitable when the firm size is small at the new-born stage. The positive impact of financial resources on profitability is greater when entrepreneurial teams have strong industry experience; whereas entrepreneurial teams’ industry experience and intangible resources have a negative interaction effect on profitability. Entrepreneurial team’s startup experience has most negative interaction effects on new-born startup firms’ profitability. This finding indicates that the entrepreneurial team’s startup experience plays stronger roles in venturing profitable startups when the amount of financial resources and initial firm size are small; however, the team’s startup experience and intangible resources have positive interaction effects on new-born startups’ profitability.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".