Green Marketing to Customer Need and Customer Satisfaction in Herbal City Community: Case of the North of Thailand
Bibliographic record
Abstract
Herbal medicine companies have essential role among the community. It has unique role in the medicine companies to fulfill the health-related needs of people. However, herbal city community was neglected by the literature. Especially, the role of green marketing was not examined in relation to the customer needs and customer satisfaction. Hence, the current study filled this literature gap by examining the role of green marketing in customer needs and customer satisfaction. This objective was achieved by examining the relationship between green marketing, green environment, customer needs and customer satisfaction. The survey questionnaire was effective tool for data collection which was used in this study and 210 valid responses were used in data analysis. Data were collected from North of Thailand. Results of the study shows that green marketing has positive effect on customer needs. Green marketing also has positive effect on customer satisfaction. Moreover, green marketing promotes green environment which further shows positive influence on customer needs and customer satisfaction.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".