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Record W2344875840 · doi:10.1080/09593969.2016.1170065

Factors influencing Generation Y consumers’ perceptions of eWOM credibility: a study of the fast-food industry

2016· article· en· W2344875840 on OpenAlexaff
Roy Shamhuyenhanzva, Estelle van Tonder, Mornay Roberts-Lombard, David Hemsworth

Bibliographic record

VenueThe International Review of Retail Distribution and Consumer Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsNipissing University
Fundersnot available
KeywordsLISRELCredibilityHomophilyStructural equation modelingSource credibilityTrustworthinessContext (archaeology)PsychologyPerceptionSample (material)Meaning (existential)PopulationMarketingAdvertisingBusinessSocial psychologyGeographyPolitical scienceSociologyMathematicsStatistics

Abstract

fetched live from OpenAlex

eWOM communication is certainly one of the most influential drivers of purchase decisions. However, little knowledge is available on the factors that influence the trustworthiness and credibility of eWOM communication. To address this research gap, the study aimed to assess whether the three independent variables (homophily, authority and interestingness) have a significant positive indirect effect on eWOM credibility, as mediated by source trustworthiness. The context of the study was fast-food retailers. A cross-sectional survey was conducted and the target population included all Generation Y consumers that visited the fast-food market leaders in Gauteng province, the economic hub of South Africa. Lisrel version 8.8 was used to analyse the results obtained from a realised sample of 362 respondents and to compile the structural equation model. The findings of the study support the research hypotheses formulated and offer a theoretical contribution by enhancing knowledge of the relationships between the variables investigated as well as the factors that could influence eWOM credibility. The study also has meaning to fast-food retailers, as the model could be applied to formulate appropriate strategies and influence the online conversations and perceptions of consumers.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.162
GPT teacher head0.413
Teacher spread0.251 · 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

Citations42
Published2016
Admission routes1
Has abstractyes

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