The Moderating Role of Technological Knowledge in the Relationship Between Perceived Sustainable Marketing and Intention to Agritourism
Bibliographic record
Abstract
Agritourism is a key component of sustainable tourism, focusing on minimizing environmental impacts. This study evaluates how technological knowledge influences tourist behavior and intentions within agritourism, employing the Theory of Planned Behavior for a structured quantitative analysis. Data from 348 visitors to orchards, farms, and aquaculture sites in agritourism settings were analyzed using partial least squares structural equation modeling. Results show a significant impact of perceived environmental factors on attitudes, subjective norms, perceived behavioral control, and perceptions of sustainable marketing. Importantly, technological knowledge plays a vital moderating role in linking sustainable marketing perceptions to the intention to engage in agritourism. This research sheds light on the dynamic relationship between sustainable marketing, technological knowledge, and tourist behavior in agritourism, offering insights for businesses and policymakers to foster sustainable practices and enhance the appeal of agritourism experiences.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".