Structure, imprinting and survival of venture capital firms
Bibliographic record
Abstract
This longitudinal quantitative study investigates how organizational structure and the external environment impact VC firm survival. It examines how macroeconomic conditions may influence independent (IVC) firms and corporate (CVC) units differently. Results suggest CVCs and IVCs exhibit similar lifespans but add an important subtlety: for the first few years of their lives CVC units show higher mortality, but afterwards are longer-lived. They also show an imprinting effect, whereby all VC firms born in more difficult macroeconomic conditions show a higher long-run survival rate, contradicting prior studies of general firms. Finally, this imprinting effect is initially more pronounced in CVC firms. Resume : Cette etude quantitative longitudinale examine comment la structure organisationnelle et l’environnement externe influencent la survie des firmes de capital de risque (des « VC »). Plus precisement, elle examine comment les conditions macroeconomiques influencent de facon differente les VCs independantes (les « IVC ») et corporatives (les « CVC »). Les resultats suggerent que les CVC et IVC presentent des durees de vie similaires, mais ajoutent une subtilite importante : pour les premieres annees de leur vie, les unites CVC montrent une mortalite plus elevee, mais par la suite montrent une survie plus longue. Elles montrent egalement un effet d’impression (« imprinting ») de sorte que toutes les firmes de VC nees dans des conditions macroeconomiques plus difficiles montrent un taux de survie a long terme plus eleve, qui n’est pas coherent avec des etudes precedentes des firmes de type generales. Enfin, cet effet d’impression est initialement plus prononce dans les entreprises CVC. Acknowledgments: An earlier version of this work was presented at EGOS Montreal in July of 2013. Les Cahiers du GERAD G–2015–113 1
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".