The impact of bank financing and internal financing sources on women’s motivation for e-entrepreneurship
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the impact of bank financing and internal financing sources on women’s motivation for e-entrepreneurship. Design/methodology/approach Female owners of e-businesses in India were surveyed regarding their perceptions of bank financing, internal financing sources and their motivations for e-entrepreneurship. Findings The findings of this study show that bank financing and internal financing sources positively impact women’s motivation for e-entrepreneurship in India. The results show that family status, education, easy access to new business information and location positively impact women’s motivation for e-entrepreneurship in India. The findings also show that bank financing has a higher impact on women’s motivation for e-entrepreneurship compared with internal financing sources. Research limitations/implications This is a co-relational study that investigated the relationship between bank financing and women’s motivation for e-entrepreneurship and the relationship between internal financing sources and women’s motivation for e-entrepreneurship. There is not necessarily a causal relationship between the two. The findings of this study may only be generalized to individuals similar to those that were included in this research. Originality/value This study contributes to the literature on the impact of bank financing and internal financing sources on women’s motivation for e-entrepreneurship. The findings may be useful for investment advisors, the Indian Government and entrepreneurship consultants.
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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 | 0.001 | 0.001 |
| 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 it