Firm and Group Influences on Venture Capital Firms’ Involvement in New Ventures
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Bibliographic record
Abstract
abstract Drawing on expectancy, equity, and collective effort theories, we argue that the level of involvement of individual firms in multifirm alliances depends on both individual firms’ self‐focused interests and factors stemming from the firms’ membership in the alliance group. We apply our theoretical arguments to the context of venture capital syndicates and test the hypotheses using data about 160 venture capital firms (VCFs) drawn from a survey instrument and a secondary data source. The results show that individual firms’ involvement in a multifirm alliance is somewhat dominated by group effects; specifically, financial stake relative to that of the group and the reputation of the other group members significantly influence the focal firm's involvement. However, focal firms’ involvement relates negatively to their own reputation. We discuss the implications of these findings for future research. Our results imply that firms in multiparty alliances pay attention to the characteristics of their alliance partnership to calibrate their own behaviour. In our specific setting, VCF involvement in syndicates depends more on relative syndicate characteristics than on the focal firm's absolute level of investment. Further, because reputation is negatively associated with involvement, entrepreneurs and potential syndicate entrants should ensure that they fully leverage VCF reputation to achieve their goals.
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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 | 0.000 |
| 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 it