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Record W4311784673 · doi:10.5267/j.ijdns.2022.8.012

Examining the effect of social media interaction, E-WOM, and public relations: Assessing the mediating role of brand awareness

2022· article· en· W4311784673 on OpenAlexvenueno aff
Ahmad Ibrahim Aljumah

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsUSableSocial mediaPsychologyWord of mouthSimple random sampleData collectionCompetitive advantageMarketingStructural equation modelingBusinessBrand awarenessAdvertisingComputer scienceSociology

Abstract

fetched live from OpenAlex

The development of trust among the customers of the organization is a key objective and critical to obtaining a competitive advantage. Therefore, this study was examined to assess the effect of social media interaction, public relations, and electronic word of mouth on brand awareness and trust. This study also examined the mediating role of brand awareness as well. For this purpose, the data was collected from the customers of the retail sector in UAE. This study adopted a quantitative research approach and cross-sectional design. The data was collected in the form of a research questionnaire by adopting simple random sampling. The questionnaire was distributed among 512 respondents. The usable response rate was 69.72%. For the analysis of data, the SEM technique was adopted and the tool used for this purpose was Smart PLS. The findings of the study revealed that all proposed hypotheses are accepted. The findings of the study are helpful for the academicians for further research and development of policies.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations85
Published2022
Admission routes1
Has abstractyes

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