Exploring consumer attitudes: Organic herb cordyceps and intention to purchase
Bibliographic record
Abstract
Cordyceps are a form of herb that is nurtured and propagated utilizing organic farming techniques. This study investigated consumers’ intention towards adopting the organic herb cordyceps, also referred to as “Thungchao” in Thai language. The research was driven by increased health awareness among people, and skewness towards use of organic as compared to conventional medication. In Thailand, the herb has been consumed traditionally for years, because of its medical benefits. The Theory of Planned Behavior (TPB) was applied to investigate the outcomes of users’ perceptions (perceived experience with organic product, perceived health benefit, information awareness) and TPB aspects (subjective norm, perceived behavioral control, attitude towards organic herb) to examine intentions of consumers’ towards adopting codyceps. The research collected primary data from 452 Thai respondents. Collected data were evaluated utilizing Structural Equation Modeling analysis. Results revealed that for the perceived customers’ experience, intention to use organic herb cordyceps was positively and significantly influenced by perceived experience with organic hers and information awareness. All the TPB variables – subjective norm, perceived behavior control, and attitude towards organic herbs – significantly and positively influence consumers’ intention towards organic herb cordyceps. The research recommended that organic herb cordyceps “Thungchao” has many medical benefits, and its consumption should be encouraged. Information awareness and sharing of the knowledge of the herb’s medical requirement and benefits, resources and dosage are necessary to encourage or rather influence consumers intention.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".