New venture creation: innovativeness, speed-to-breakeven, and revenue tradeoffs
Bibliographic record
Abstract
Abstract We present a Schumpeterian model of new venture creation, under uncertainty, which explains the tradeoff between speed-to-breakeven and revenue-at-breakeven and relates this to the level of innovation. We then explore the tradeoffs between these outcomes empirically in a sample of 331 information and communication technology (ICT) ventures using a multi-input, multi-output stochastic frontier model. We estimate the contribution of financial capital and labor to the outcomes and the tradeoffs between them, as well as address heterogeneity across ventures. We find that more innovative (and therefore more uncertain) ventures have lower speed-to-breakeven and/or lower revenue-at-breakeven. Moreover, for all innovativeness levels, new ventures face a tradeoff between speed-to-breakeven and revenue-at-breakeven. Our results suggest that it is the availability of proprietary resources (founder equity and founder labor) that helps ventures overcome bottlenecks in the venture creation process, and we propose a line of research to explain the variation in venture creation efficiency.
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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 | 0.000 | 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 | 0.001 |
| 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 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".