Gıda Kalitesi, Sağlık Bilinci ve Fiyat Duyarlılığının Fast-Food Satın Alma Niyetine Etkisi: Türkiye ve Kanada’daki Tüketicilerin Karşılaştırması
Bibliographic record
Abstract
The aim of this study is to investigate the effects of perceptions of food quality of fast-food products, health consciousness and price sensitivity of customers on purchase intention in fast-food restaurants. Also, within the context of these variables, the study examines whether differences exist between customers in Turkey and Canada. To achieve this aim, the hypotheses in the proposed model were tested with online survey data from 291 college students in Ankara and Toronto. Confirmatory factor analysis was used to test the model fit between the survey data and the food quality, health consciousness, price sensitivity and purchase intention scales. Path analysis and independent samples t-Tests are used to test the research hypotheses. According to the results of the path analysis, food quality and price sensitivity positively influence purchase intention while health consciousness negatively influences purchase intention of fast-food products in Canada. Similarly, in Turkey, food quality positively influences purchase intention of fast-food products. However, health consciousness and price sensitivity do not influence fast-food purchase intentions in Turkey. \nAlso, results from the independent samples t-Test reveal that college students in Canada are more price sensitive towards fast-food products than those in Turkey. However, the independent samples t-Tests did not reveal any differences in food quality perceptions, health consciousness levels and fast-food purchase intentions between college students in Turkey and those in Canada. Finally, limitations of the study, suggestions for future research, recommendations for managers and policymakers are also presented.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".