Impact Investment as an External Enabler of Entrepreneurship
Bibliographic record
Abstract
Recently, there has been a rise in impact investment funds that seek to support the establishment and growth of sustainable ventures, especially in the Global South. But does impact investment have an effect, and if so, how? In light of the lacking evidence and theory on how entrepreneurship is enabled by the environment, there are few answers to these questions. In this study, we seek to answer whether impact investment serves as an external enabler of entrepreneurship. We theorize that impact investment enables entrepreneurship through two different mechanisms. Impact investment enables entrepreneurship through resource expansion, that is, access to funds, and through modifying the institutional environment, that is, strengthening market-supporting institutions in recipient countries, thus enabling entrepreneurship. Using a dataset of 4,691 impact investments in 122 countries, we find general support for our theorization. Our study contributes to the knowledge on impact investment as one of the first studies to show impact investment’s effect on entrepreneurship. Furthermore, our study tests and extends the nascent external enabler framework.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".