Social media experience, attitude and behavioral intention towards umrah package among generation X and Y
Bibliographic record
Abstract
The development of Islamic tourism such as Umrah does not get much attention in the literature though there are 6 million people all around the world performing Umrah every year. Nowadays, social media has been recognized as an important tool in building and maintaining the image of tourist destination especially in the Umrah context. Thus, the purpose of this study was to examine the effect of social media experiences (interactions and sharing of contents) on attitudes and behavioral intentions towards Umrah package (booking decisions and electronic Word of Mouth) among generation X and Y. Sums of three hundred eighty-four respondents were engaged as the respondents. The population of this study was among Malaysian Muslim citizens who had social media experiences in seeking online information and knowledge about Umrah and already performed Umrah. The data then was analyzed using the Statistical Package for Social Science (SPSS) and Partial Least Squares (PLS) software. The findings of this study confirmed that sharing of contents of social media experiences has significant and positive relationship on behavioral intentions (booking decisions and electronic Word of Mouth).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".