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Enregistrement W3202626903 · doi:10.1108/ihr-02-2021-0007

Predicting locally grown food purchase intention of domestic and international undergraduate hospitality management students at a Canadian University

2021· article· en· W3202626903 sur OpenAlexaffabout
Yoonah Kim Conoly, Mike von Massow, Yee Ming Lee

Notice bibliographique

RevueInternational Hospitality Review · 2021
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueOrganic Food and Agriculture
Établissements canadiensUniversity of Guelph
Organismes subventionnairesnon disponible
Mots-clésHospitalityTheory of planned behaviorPsychologyProduct (mathematics)Norm (philosophy)MarketingVariance (accounting)Sample (material)Social psychologyTourismMathematicsBusinessGeographyEconomicsPolitical scienceControl (management)Management

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,200
Score d'incertitude au seuil0,992

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,232
Écart entre enseignants0,220 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations7
Publié2021
Routes d'admission2
Résumé présentoui

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