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Record W7154151344 · doi:10.3126/fwr.v3i2.92807

Impact of Facebook Marketing on Apparel Purchase Intention of Generation Z in Nepal

2025· article· W7154151344 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFar Western Review · 2025
Typearticle
Language
FieldSocial Sciences
TopicGenerational Differences and Trends
Canadian institutionsWestern University
Fundersnot available
KeywordsClothingSocial mediaStructural equation modelingGeneration yComputer-assisted web interviewingOrder (exchange)

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.068
GPT teacher head0.396
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it