The role of innovation strategies in mediating covid-19 perceptions and entrepreneurship orientation on Endek weaving craft business performance
Bibliographic record
Abstract
This study aims to examine the role of innovation strategies in mediating Covid-19 perceptions and entrepreneurial orientation on the performance of endek weaving craft business in Bali Province. The theoretical basis used is RBV (Resources Based View) which argues that each company has varying resources with differences in resulting performances. The test was carried out by quantitative analysis using a Structural Equation Model (SEM) based on Partial Least Square (PLS). Data were collected from 139 MSME of endek weaving craftsmen. The results of testing the effect of Covid-19 perceptions and entrepreneurial orientation on business performance were insignificant. Meanwhile, those on innovation strategies and entrepreneurial orientation were positively significant. The results of testing the effect of innovation strategy on business performance and collaboration between the government and the private sector in moderating the innovation strategy on business performance were positively significant and insignificant. The results of testing the effect of innovation strategies mediating Covid-19 perceptions on business performance and mediating entrepreneurial orientation on business performance were positively significant. The study actually confirms that the innovation strategy is a strong mediating variable to bridge the relationships between entrepreneurial orientation variables, Covid-19 perceptions, and business performance. The collaboration between the government and the private sector is also an insignificant moderator to achieve the business performance of MSME actors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".