Export Market Orientation and Organizational Knowledge Enhance Export Market Performance
Bibliographic record
Abstract
Exporters exporting to the Arab Countries should focus on market orientation and organizational knowledge activities to enhance their export performance. Marketing concept suggests that the long term purpose of an organization is to satisfy customer needs for the purpose of maximizing profits. Thus, this study investigated the relationship between export market orientation, organizational knowledge and export market performance. The hypothesized relationships between export market orientation, organizational knowledge and export market performance were empirically tested through structure equation modeling. A total of 223 duly completed self-administrated survey questionnaires collected from each representative manufacturers who export to the Arab market were analyzed. The result shows that export market orientation and organizational knowledge positively influence export market performance. The square multiple correlations between the exogenous constructs and endogenous construct was found to be 49%. It means that when there is one unit of increase in export market orientation and organizational knowledge, there will be 49 units of increase of export market performance for Malaysian manufacturers exporting to Arab countries. Result implies that exporters exporting to Arab countries should focus on market orientation and organizational knowledge activities in their organization to enhance export performance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".