The effects of entrepreneurial skills, benchmarking, and innovation performance on culinary micro-small-medium enterprises
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 was to analyze the effect of entrepreneurial skills and benchmarking on the performance of culinary innovations (restaurants, restaurants, and cafes) of micro-small-medium enterprises (MSMEs) in Indonesia sub-urban areas. Online questionnaires were used as the instrument to collect data, and the data were analyzed by deception analysis to illustrate various features of the variables studied. Hypothesis test was conducted by Partial Least Square Path Modeling (SEM-PM). The MSME population was 231 and the representative sample was 144 culinary companies. It was found that entrepreneurial skills, benchmarking, and performance of culinary MSME innovations tended to be lower than expected. The results of this study revealed that entrepreneurship and benchmarking skills had significant effects on innovation performance. To improve innovation performance, companies must pay more attention to practical knowledge, especially knowledge of bookkeeping and digital marketing, and make more comparisons on financial aspects.
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 | 0.001 | 0.001 |
| 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