MétaCan
Menu
Back to cohort
Record W4226490156 · doi:10.5267/j.ijdns.2022.1.015

The effect of social media marketing on brand trust, brand equity and brand loyalty

2022· article· en· W4226490156 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior and Marketing Influence
Canadian institutionsnot available
Fundersnot available
KeywordsBrand equityBrand loyaltyBusinessBrand awarenessSocial mediaAdvertisingMarketingStructural equation modelingBrand managementSocial media marketingDigital marketingMathematicsComputer scienceStatistics

Abstract

fetched live from OpenAlex

This study aims to determine the effect of social media marketing activities on brand trust, brand equity and brand loyalty in social media. The study uses the Structural Equation Modeling (SEM) method with SPSS 3.3.3 software with a sample of 450 respondents determined by the simple random sampling method who had experience of using social media for at least six months. Data was obtained by distributing online questionnaires using google form. The results show that social media marketing has a positive effect on brand trust, social media marketing has a positive influence on brand equity, and social media marketing has a positive influence on brand loyalty. Brand trust has a positive influence on SMEs Performance, Brand equity has a positive influence on SMEs Performance and finally brand loyalty has a positive influence on SMEs Performance.

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)0.009
metaresearch head score (Gemma)0.001
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 score0.688
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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