A dynamic capability theory perspective: borderless media breakthrough to enhance SMEs performance
Bibliographic record
Abstract
Social media technology as borderless media has made it easier for small and medium-sized businesses (SMEs) to interact with their customers. The application of social media has impacted the operation and information sharing of SMEs, allowing them to develop innovation opportunities, to meet customer needs, and to improve firm performance. This study examined the influence of social media use on business networking quality and product innovativeness of SMEs. The data for this cross-sectional study were gathered from jewelry crafting SMEs in Bali, Indonesia using the survey method. The data were analyzed using the covariance-based statistical analysis technique with SPSS via AMOS 23. The results indicate that, while the direct link between social media adoption and firm performance is not significant, this path is fully mediated through business networking quality and product innovativeness. Hence, these SMEs should leverage their social media adoption due to strong business networking quality and product innovativeness enabling competitive advantage that heightens firm performance. Firm-level product innovation can harness the economic performance of the SMEs. The study limitations and future research endeavors are presented at the end of this paper.
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How this classification was reachedexpand
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 | 0.008 | 0.002 |
| 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".