The role of xiaohongshu in dietary acculturation and its influence on Chinese international students’ purchase intention for Malaysian traditional food
Bibliographic record
Abstract
This study investigates the role of Xiaohongshu in shaping Chinese international students’ purchase intentions (PI) toward Malaysian traditional food. Drawing on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), the research examines the direct effects of information quality, electronic word of mouth (eWOM), perceived usefulness (PU), and perceived enjoyment (PE) on PI, as well as the mediating roles of attitude and trust and the moderating role of food neophobia. A quantitative research design was employed, and data were collected through a structured questionnaire distributed among Chinese international students studying in Malaysia. A total of 380 valid responses were obtained, with established scales adapted from prior research to measure the constructs. The data were analyzed using SPSS, including reliability testing, correlation analysis, regression analysis, and mediation and moderation tests. The results revealed that all four independent variables significantly influenced PI, with both attitude and trust mediating these relationships. Furthermore, food neophobia was found to moderate the effects of attitude and trust on PI, weakening these positive associations among students with higher levels of neophobia. These findings confirm the importance of cognitive and affective factors in food-related consumer behavior within a cross-cultural context. This study extends TAM and TPB by applying them to the context of social media–driven cross-cultural food consumption. It provides theoretical insights into the role of trust, attitude, and individual differences in shaping consumer behavior, while also offering practical recommendations for marketers and cultural promoters seeking to enhance the acceptance of Malaysian traditional food among international students.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".