Web-Based GIS in Tourism Information Search : An analysis of the effect of socioeconomic characteristics on perception and behavior
Bibliographic record
Abstract
Among the Internet applications, Web-based spatial data service (WebGIS), e.g. Google Maps, Yahoo Maps, and Bing Maps, has promised a new generation of information platforms and expanded the ways in which travel information can be accessed. However, we know little about the population who seeks tourism and recreation information through WebGIS. Therefore, the purpose of this study was to delineate the tourism-information seekers’ perceptions toward WebGIS and their use behaviors associated with tourism situations and patterned by user socioeconomic characteristics. An electronic self-administered survey was developed for the investigation. ANOVA was employed to conduct analyses. Sex showed to be influential in information search behavior. In comparison to other factors, the factor of age differentiated the behaviors and perceptions toward WebGIS in a wide spectrum. In general, education as a factor distinguished the use motive and interest areas. The factor of income levels among respondents showed little influence in the attitude toward or preference for WebGIS services.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".