Impact of Facebook Marketing on Apparel Purchase Intention of Generation Z in Nepal
Bibliographic record
Abstract
The study explores impact of Facebook marketing affects the purchase intentions of Generation Z apparel consumers in Nepal. The behaviors and habits of Generation Z, which are online, make it an ideal target of social media marketing. The research design employed in this study was a quantitative, cross-sectional research design. The survey was based on a simple online questionnaire involving the respondents of 399 respondents belonging to Generation Z in Nepal, and the results were analyzed using SmartPLS 4 software and partial least squares structural equation modeling (PLS-SEM). The results of the hypothesis established that the three predictors of the study, Facebook advertisement (Path Coefficient 0.332, p = 0.000), Facebook comments and recommendations (Path Coefficient 0.337, p = 0.000), and Facebook offers (Path Coefficient 0.192, p = 0.001) had statistically significant effects on purchase intention among the Gen Z consumers in Nepal. The findings depict that Facebook marketing affects brand awareness, brand engagement, and purchase intention. These results underscore the essential need to engage in informative social media marketing.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".