The Influence of Fixed and Flexible Funding Mechanisms on Reward-Based Crowdfunding Success
Bibliographic record
Abstract
This study examined whether fixed or flexible funding mechanisms influence crowdfunding success. Under the fixed funding mechanism, the pledges contributed to the crowdfunding campaign projects are returned to the backers if the project fails, whereas, under the flexible funding mechanism, the project creator can keep all the raised pledges, irrespective of whether the project succeeds or fails. Secondary data consisted of reward-based crowdfunding projects retrieved from The Crowd Data Centre. Logistic regression was employed to respond to research objectives. The results reveal that the fixed funding mechanism increases the probability of success more than flexible funding. Entrepreneur experience, spelling errors, and project description negatively affect crowdfunding success, and backers positively affect crowdfunding success. The findings guide entrepreneurs seeking financing to design and choose an appropriate funding mechanism that effectively reduces the failure rate. Although many entrepreneurs seek funding in the crowdfunding market, relatively little research has been conducted on the influence of flexible or fixed funding mechanisms on crowdfunding success in Africa. This study provides entrepreneurs with appropriate financing strategies that enhance crowdfunding success. The empirical literature indicates that the flexible funding mechanism creates distrust among backers due to unrealistic target amounts.
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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 | 0.001 | 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 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".