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Record W2938793381 · doi:10.5267/j.msl.2019.3.015

The impact of social network marketing on consumer purchase intention in Pakistan: A study on female apparel

2019· article· en· W2938793381 on OpenAlexvenueno aff
Rozina Imtiaz, Syeda Qurat ul Ain Kazmi, Maheen Amjad, Atif Aziz

Bibliographic record

VenueManagement Science Letters · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsClothingBusinessMarketingAdvertising

Abstract

fetched live from OpenAlex

The main objective of this study is to explore and investigate the impact of social network marketing on purchase intention of female's consumers in fashion apparel and how it is affected by mediating role of brand engagement and consumer motivation. Deductive approach is used to determine the variables influencing purchase intention of female fashion apparel's consumer. The study is conducted in Karachi, the hub of Pakistan's economy. A total 150 questionnaires were distributed using random sampling technique among females of Karachi, out of which 127 responded. Data is analyzed using mean, frequencies and standard deviation with the help of SPSS. The study reports that social network marketing was significantly associated with consumer purchase intention. The study further reveals that brand engagement and customer motivation act as a partial mediator on how social network marketing impact on purchase intention of females' fashion apparels.

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 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)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.338
Teacher spread0.320 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2019
Admission routes1
Has abstractyes

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