Determinants Impacting Consumers’ Purchase Intention: The Case of Fast Food in Vietnam
Bibliographic record
Abstract
The purpose of this case study is to explore and study the determinants impacting Vietnamese students’ food choice and the pattern of consumption of fast food in university students. The objective set for this research was conduct with the following objectives respectively getting an insight of fast food market in Vietnam and explore the attributes that Vietnamese students in perceive to be important in the selection of fast food restaurants and the study results provide a better understanding about the industry and consumer food choice variables The model and the design of the questionnaire content in this study was based on the measures of previous related research and literatures and several constructs were measured by single item scale, E-S-QUAL scale (Parasuraman et al., 2005) that has been developed and used in the present study has been shown to be a valid instrument for the measurement with four main factors (Health Consciousness, Value Perceived, Food Safety and Price) toward with Purchase Intention. In this regard, other questions were also applied in the survey to get an insight about demographic information and consumption habits of students in this research. Moreover, we found significant positive relationship between the purchase intentions and food safety, subsequently price and value perceived with similar positive relationships. Hence we can say that managers have to keep these factors in mind to perform better.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".