Determinants of Marketing Performance on Durian Product for Exporting: Study in South of Thailand
Bibliographic record
Abstract
Thailand is the major exporter of durian products worldwide. Durian is the most important fruit and it’s called the king of fruits in Thailand. The economy of Thailand majorly bases on the exporting of durian to other related countries. The major objective of this study to find out the determinants of marketing performance that affect the durian product exporting in the south of Thailand. Respondents of this study are employees working in exporting companies working in the south of Thailand. Data is collected through a drop-down survey method and a questionnaire is used. After it, Smart PLS used for analysis. Results revealed that determinants of marketing performance like (Product capability, Promotion, and Distribution capability) have a positive, significant impact on exporting of durian. Two mediators including attitude towards exporting have a positive effect but the second motivation to export has no effect on durian export. Attitude towards exporting mediates the relationship between distribution capability and exporting of durian. Motivation to export has no mediation between promotion capability and export of durian. The study recommends to exporters that for increasing export to other countries they should focus on marketing performance determinants.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".