Adoption of Digital Technology and Financial Knowledge: Strategies for Achieving Sustainable Performance of MSMEs
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
Micro, small and medium enterprises (MSMEs) contribute significantly to Indonesia’s economic growth. In an increasingly digitalised era, MSMEs face challenges and opportunities that affect their performance. Technology adoption will have an impact on operational efficiency and ease of transactions, providing added value for consumers. Meanwhile, good financial management depends on the level of financial literacy and inclusion of MSME players. This study aims to examine the factors that influence the sustainable performance of MSMEs from the aspects of technology adoption and financial knowledge. The independent variables include automation, digital payments, financial inclusion and financial literacy, and the dependent variable is MSME performance. This study uses primary data in the form of questionnaires, and data processing uses SEM-PLS. Statistical test results show that the variables of business automation and financial literacy have a positive effect, while the variables of digital payments and financial inclusion have no effect. The results of the study show that financial literacy is an important key to MSME performance and the importance of business automation that affects efficiency through technology. The results of this study are expected to provide useful recommendations for MSME actors and policymakers in formulating strategies to improve the competitiveness of MSMEs.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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