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Record W3135211035 · doi:10.1080/08911762.2021.1891359

Facebook advertising, eWOM and consumer purchase intention-Evidence from a collectivistic emerging market

2021· article· en· W3135211035 on OpenAlexaff
Youssef Chetioui, Irfan Butt, Hind Lebdaoui

Bibliographic record

VenueJournal of Global Marketing · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCollectivismAdvertisingBusinessMarketingPsychologyEconomicsIndividualism

Abstract

fetched live from OpenAlex

Despite a growing body of work on the impact of cultural orientation on consumers’ attitudes and behavior, research investigating the effects of individualism-collectivism in social media advertising remains limited. Based on a theoretical framework founded on the theory of planned behavior, Ducoffes’s web advertising model, and further variables from related literature, this study aims to investigate how Facebook advertisements contribute to consumers’ purchase intention in an emerging market marked by high levels of collectivism. Through a sequence of research propositions that elucidate how individuals from a collectivistic culture make purchase decisions when exposed to Facebook advertisements, our study makes a significant contribution to attitudinal research as it establishes a better understanding of the use of advertising on Facebook to market products and services. Our findings confirm the necessity and importance of taking into account consumers’ cultural differences when advertising on social media sites.

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)0.005
metaresearch head score (Gemma)0.058
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.307
Teacher spread0.290 · 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.

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

Citations103
Published2021
Admission routes1
Has abstractyes

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