Predicting locally grown food purchase intention of domestic and international undergraduate hospitality management students at a Canadian University
Bibliographic record
Abstract
Purpose This study aims to investigate how domestic and international undergraduate students from a university in Ontario, Canada, defined locally grown food and examined the factors behind their locally grown food purchase intentions. Design/methodology/approach Questionnaires were distributed in the School of Hospitality, Food, and Tourism Management undergraduate classes. A total of 196 complete surveys were returned. Using multiple regression analysis and theory of planned behavior (TPB) as a theoretical framework with an additional construct, moral norm, proposed hypotheses were tested. Findings Domestic students narrowly defined locally grown food based on distance (e.g. food grown/raised within 100 km of where a person lives) compared to international students (e.g. food grown in Canada). The multiple regression analysis revealed that 36% of variance in purchase intention is explained by the four independent variables (i.e. student status, attitude, perceived product availability and moral norm), with perceived product availability as the strongest predictor of intention to purchase locally grown food. Research limitations/implications The convenience sampling method limitations are as follows. First, the sample size was small for international students. Second, there was a possibility of underrepresentation of certain origins of international student populations. Third, the undergraduate respondents were from the School of Hospitality, Food and Tourism. Finally, another limitation is that the four variables in this study (i.e. attitudes, subjective norms, perceived product availability, and moral norm) only explained 36% of the variance of this model. Practical implications Perceived product availability, moral norm and attitude constructs positively influenced the locally grown food purchase intention. A perceived product availability construct revealed the strongest influence in locally grown food purchase intention of students. Particularly, five key questions were created based on the major research findings of this study, which can be used as a guideline for locally grown food providers and farmers when promoting locally grown food to students. These questions include: Where can I find it? When can I find it? Who grows it? How can I benefit others? Why is it good for me? Social implications The results of this study shown that which factors influence locally grown food purchase intention of students. Hence, local restaurateurs and university dining facilities may incorporate these factors in their marketing message to serve students population better who might be interested in buying food products using locally grown ingredients. Research results also allow local farmers to communicate and inform their current and potential student consumers about the advantages of locally grown food. Overall, findings can contribute to economy and business of local community. Originality/value Current research findings verified that there is a significant use of a moral norm construct to predict locally grown food purchase intention of students. The moral norm construct positively influenced the locally grown food purchase intention in this study, and this construct seemed useful to predict locally grown food purchase intention of students. Additionally, the research discovered that there were differences in domestic and international undergraduate students' perception in the locally grown food definition.
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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 | 0.000 |
| 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 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".