Micro, small, and medium enterprises (MSMEs): The emerging market analysis
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
This study aims to analyse the factors affecting the Micro, Small, and Medium Enterprises in the province of South Sumatra, Indonesia. Data of 100 MSMEs were collected through questionnaires in the 15 regencies/cities in South Sumatra. The statistical analysis used was Structural Equation Modelling (SEM) processed through AMOS. The results evidence that the external factors of capital support, business partners, and infrastructure directly have no direct effects but indirectly affect the performance of MSMEs in South Sumatra. Also, the availability of resources and environmental conditions; and the capability of business owners and employees indirectly affect the performance of MSMEs in South Sumatra. Lastly, the use of technology and research impact the performance of MSMEs in South Sumatra directly and indirectly through the availability of resources and environmental conditions and business owners and employees' capability. Theoretically, this study expands the MSMEs literature by discussing factors (i.e., external and internal) affecting MSMEs' performance holistically. Practically, this study is beneficial for the government, practitioners, and policymakers.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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