Comparative Analysis of DMO Website Features: A Case Study of Three Asian Tourism Destinations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the digital era, more and more people tend to look for travel-related information on the Internet. Hence, destination marketing organization (DMO) websites can play a decisive role in affecting people’s destination choices. Based on the study of Pai, Xia, and Wang, Macao’s DMO website received the lowest score in the effectiveness when compared to the other four tourism destinations: Japan, Korea, Hong Kong, and Thailand. This paper aimed to carry out a comparative analysis on the functionality among three DMO websites in Asia. Each website was examined in great detail, and the features were categorized according to a well-established conceptual framework pioneered by Li and Wang. Consequently, the results of this study gave useful information and new insights to destination marketing managers in terms of gap analysis and the development of new features for their websites. The results of this research could be used as benchmarking purposes in regards to website functionality. In addition, DMO websites in western countries, such as Canada, were also examined for a better understanding of the comprehensiveness of the available website functionality aimed for prospective visitors. Business and managerial implications were also discussed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| 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 it