Electronic word-of-mouth (eWOM) on WeChat: examining the influence of sense of belonging, need for self-enhancement, and consumer engagement on Chinese travellers’ eWOM
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.
Bibliographic record
Abstract
‘Friends’ circles’ on WeChat have helped make eWOM more easily accessible and influential than ever. Drawing from the social identity theory, literature on consumer engagement and eWOM, this study presents the first research that examines the influence of two personality traits, sense of belonging and need for self-enhancement, on consumer engagement and in turn leads to eWOM intention. The results suggest that the need for self-enhancement positively influences Chinese travellers’ engagement with WeChat. In addition, a partial positive relationship between consumer engagement and eWOM intention was identified: only dedication towards WeChat is directly related to travellers’ intention to engage in eWOM on WeChat. Dedication was found to mediate the influence of need for self-enhancement on eWOM intentions. Sense of belonging, however, does not have a significant impact on consumer engagement. These mixed results demonstrate changing cultural values of contemporary Chinese society. Theoretical and practical implications are discussed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it