The effects of knowledge sharing, social capital and innovation on marketing performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Women entrepreneurs and the informal sector are looking for footholds in the COVID-19 pandemic, which will lead women to develop creative businesses. This study examines the role of sharing knowledge and innovation in addressing gaps in social capital and marketing performance. Purposive sampling is used in the technique sample with 229 samples and Structural Equation Modeling (SEM-PLS) analysis techniques with SmartPLS is used for processing applications. The results show that social capital has a positive effect on the business performance of women entrepreneurs in Bali, Indonesia. The knowledge-sharing variable can be a mediator in the relationship between social capital and performance, and social capital has a significant positive effect on innovation, but innovation does not have a positive effect on marketing performance and knowledge sharing. In the end, women entrepreneurs will use knowledge sharing to create various innovations to meet market demand. However, opportunities for women entrepreneurs are very limited on capital due to the lack of guaranteed capital, and a lack of entrepreneurial skills in the era of technology, market access, bureaucracy, and legal matters. In addition, managerial skills, access to information technology, and the perspective that men should excel in Balinese culture and customs, limit business for women entrepreneurs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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