Firm Performance and Entrepreneurial, Market and Technology Orientations in Korean Technology Intensive SMEs
Bibliographic record
Abstract
This study investigated the relationships between entrepreneurial-market orientations and entrepreneurial-technology orientations and the impact of market and technology orientations on firm performance in Korean technology intensive small and medium-sized business (SMEs). To conduct the analysis, the study applies structural equation modeling (SEM) to understand the direct effects of entrepreneurial on market and technology orientations and the direct effects of market and technology orientations on firm performance. This research is based on a study of 347 technologies intensive Korean SMEs and the major results are as follows: The results indicate that entrepreneurial orientation directly affects market and technology orientations. This result implies that entrepreneurial orientation is key factors that influence market and technology orientation in Korean SMEs. Another finding suggests that market and technology orientations positively affect firm performance. It appears that Korean companies require the capability to serve technology well, but also need to recognize new business opportunities from within their current market relationships. The implication here is that for Korean technology intensive small firms, entrepreneurial orientation can improve market and technology orientations. The results suggest that to achieve high levels of firm performance, Korean companies need to balance the elements of entrepreneurial, technology and market orientations.
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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 | 0.000 | 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 | 0.002 |
| 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 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".