Assessment of the significance of factors affecting the growth of women entrepreneurs: study based on experience categorization
Bibliographic record
Abstract
Purpose The ascent of women enterprising community (WEC) in a couple of decades draws the attention of various government and non-government bodies. Literature has mentioned various studies that focus on the factors affecting the success or failure of women entrepreneurs (WEs), but understanding of the ranking of the factors depending on the experiences of different WEs is needed. This study aims to identify the significant factors essential for the growth of WEC. Design/methodology/approach This study examines the factors through interview of 33 WEs having different entrepreneurial experiences (less than 1 year, more than 1 year but less than 10 years and more than 10 years of experiences) from different regions of Uttar Pradesh, India, and with the help of analytical hierarchical process, ranks the factors affecting the sustainable growth of WEs. Findings Through analysis, significant factors have been identified such as determination, education, entrepreneurial resilience, personal satisfaction and provide employment, and these factors have been analysed according to the different experiences of WEs. An investigation of ranking these factors of WEC, especially in the emerging nations, can assist policymakers in designing projects that improve the mindfulness associated with women enterprise and define the compelling methodologies. Practical implications The growth of the WEC is significantly affected by gender orientation ways of thinking as driven by entrepreneurship models. Originality/value This study gives a direction to policymakers by emphasizing on significant factors of various stages of enterprise development for the encouragement of WEs in the emerging economies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".