Social media experience, attitude and behavioral intention towards umrah package among generation X and Y
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
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).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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