Which ties matter when? the contingent effects of interorganizational partnerships on IPO success
Bibliographic record
Abstract
Abstract This paper investigates the contingent value of interorganizational relationships at the time of a young firm's initial public offering (IPO). We compare the signaling value to young firms of having ties with two types of interorganizational partnerships: endorsement relationships such as those with venture capital firms and investment banks, and strategic alliance partnerships. We propose that, under different equity market conditions, potential investors in an issuing firm attend to different types of uncertainty; attention to these different types of uncertainty affects investors' perceptions of the relative value of a young firm's different kinds of endorsements and partnerships and, hence, IPO success. Results from a sample of young biotechnology firms show that ties to prominent venture capital firms are particularly beneficial to IPO success during cold markets, while ties to prominent investment banks are particularly beneficial to IPO success during hot markets; a firm's strategic alliances with major pharmaceutical/health care firms did not have such contingent effects. Implications for understanding the contingent value of interorganizational ties are discussed. Copyright © 2003 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".