Information, Experience and Destination Marketing - The Influence of Interactivity on Tourism Website
Bibliographic record
Abstract
This study focuses on the tourism websites that are doing destination marketing for some remote areas. This study proposes that when interactivity is put into the website to create users' virtue experience with the remote areas, different user may response differently. Two kinds of user's personal factors are investigated in this study: Susceptibility to Interpersonal Influence and Personal Involvement. The research findings support the ideas proposed by Vogt et al. that values sought by information searchers are not limited to functional needs but include hedonic, innovative, aesthetic, and sign needs. The findings also indicate that interactivity feature can generate better intention to visit on users with higher personal involvement on the tour, or lower susceptibility to interpersonal influence. While on traditional tourism website, these two factors (personal involvement and susceptibility to interpersonal influence) have no significant impact on users' satisfaction. Based on these findings, marketers and advertisers can design more effective tourism website for various potential visitors to enhance their intention to visit the destination.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".