The Role of Entrepreneurial Strategy, Network Ties, Human and Financial Capital in New Venture Performance
Bibliographic record
Abstract
In the current era of globalization and competitive edge, the survival of newly established ventures has become a big challenge. Numerous studies have been carried out to discover factors that are essential for newly initiated ventures but the results are still fragmented. This study focuses on measuring the effect of entrepreneurial strategy, network ties, human capital and financial capital on new venture performance. A structured questionnaire was used to collect data from 196 registered firms located in the emerging market Pakistan. The results indicate that entrepreneurial strategy, network ties and financial capital have a significant positive effect, while human capital showed an insignificant effect on new venture performance. This research recommends owners and managers of new firms build effective entrepreneurial strategies, expand their networks with external bodies (other firms, government and financial institutions) to acquire useful resources that in turn can spur their performance. Further implications are discussed. Policy makers and responsible authorities are advised to encourage and support new ventures which in turn can contribute to GDP and economic development. Practical implications and suggestions are also discussed.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".