Improving export performance trough innovation capability during COVID-19 pandemic: The mediation role of aesthetic-utilitarian value and positional advantage
Bibliographic record
Abstract
Globalization has made exports an important activity for several companies including the growing Small and Medium Enterprises (SMEs). This is observed in the wood craft SMEs which is one of the main pillars supporting the Balinese economy when the tourism sector experienced a decline during the COVID-19 pandemic. It is important to note that innovation capability is a special asset for SME to increase exports, especially when the products have value and advantages. Therefore, this study analyzed value creation through the adoption of the Service-Dominant Logic (SDL) theory which was manifested in the aesthetic-utilitarian value variable. The study population includes all the 242 woodcraft SMEs in Bali while the samples were selected using the census method and the data obtained were analyzed through the partial least squares technique. The results showed that innovation capability has a positive effect on export performance, aesthetic-utilitarian value, and positional advantage. Moreover, aesthetic-utilitarian value and positional advantage were discovered to have a positive influence on export performance and also partially mediated the relationship between innovation capability and export performance. This implies SMEs need to develop high innovation capabilities to ensure their products are superior to those of their competitors. Furthermore, the value offered also needs to be unique and in line with customer needs.
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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".