Factors influencing Generation Y consumers’ perceptions of eWOM credibility: a study of the fast-food industry
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".