Entrepreneurial Financing in Africa during the COVID-19 Pandemic
Bibliographic record
Abstract
Access to finance by small-to-medium-enterprises (SMEs) remains an enigma that still warrants further research. The COVID-19 pandemic has exacerbated the funding gap and necessitated the need for entrepreneurs to seek alternative financing due to tight credit rationing by the traditional finance institutions. There is a marked increase in demand for alternative online finance known as crowdfunding amid social distancing and lockdowns occasioned by the COVID-19 pandemic. The main objective of this study was to examine the trends in the financing of African SMEs during the COVID-19 pandemic with a particular focus on crowdfunding. The postpositivist research philosophy and deductive strategy was adopted in this study with the view to test an existing theory and hypothesis. Secondary data sourced from TheCrowdDataCentre were utilised for the study. Eight hundred and fifty-nine African crowdfunding campaigns were employed as the unit of analysis. The study employed econometric techniques to test the research objectives of this study. The probit model was employed in the analysis. The results of the study revealed that backers, the COVID-19 and social network variables were positively and significantly related to campaign success. On the other hand, duration was found to be negatively and significantly related to crowdfunding success. The study contributes to the growing literature on the impact of COVID-19 on crowdfunding performance, as well as the literature on alternative sources of finance.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".