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Enregistrement W2761504281 · doi:10.1108/ijwbr-03-2017-0011

Where to visit, what to drink? A cross-national perspective on wine estate brand personalities

2017· article· en· W2761504281 sur OpenAlexaff
Sussie Morrish, Leyland Pitt, Joseph Vella, Elsamari Botha

Notice bibliographique

RevueInternational Journal of Wine Business Research · 2017
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueWine Industry and Tourism
Établissements canadiensSimon Fraser University
Organismes subventionnairesnon disponible
Mots-clésSophisticationAdvertisingPersonalityPersonality psychologyTourismMarketingExtraversion and introversionBig Five personality traitsSincerityBusinessPsychologySociologyGeographySocial psychology

Résumé

récupéré en direct d'OpenAlex

Purpose The purpose of this paper is to illustrate how brand personality and its dimensions can be applied to wine tourism, and how a content analysis of the text taken from a wine estate’s website can be used to derive a snapshot of how brand personality is communicated. Design/methodology/approach The paper uses the text analysis software DICTION to identify the extent to which each estate’s website communicates the brand personality dimensions of excitement, competence, ruggedness, sincerity and sophistication, and then agglomerates the scores of individual estates within a region to overall scores for the country or wine region in which they are located. Findings Major findings are that the southern hemisphere producers, Australia, New Zealand and South Africa, communicate all five brand personality dimensions to a greater extent than do the northern hemisphere regions of Bordeaux and Napa. Furthermore, while the levels of brand personality communication may differ, all countries and regions seem to follow the same pattern, or stated differently, emphasize the same brand personalities as their international counterparts. Excitement is the main dimension communicated, and then sincerity. Ruggedness and competence are communicated to a lesser extent and sophistication is hardly communicated at all. Research limitations/implications The countries/regions selected for the study are among the most popular tourist destination wineries within five of the world’s prominent wine producing countries and regions. However, this selection is arbitrary and were also carefully chosen merely by the simplicity and convenience afforded by a Google search. The results are also an aggregation of the wineries within a region and does not give any indication of the brand personality of a single website for a winery with in a region, which might be very different from the aggregation. Practical implications Wine tourism is a big business for many wine estates as well as regional and national economies, generating huge potential for economic growth and job creation above and beyond the production and sale of wine. The paper offers a practical insight for wineries that want to portray themselves to the world and especially to their target customers. At a general level, the approach illustrated here provides a way for those who manage wine tourism at the national, regional and estate levels to gauge whether the personality of their brand is being communicated online as they intend it to be. Social implications Wine tourism is very social in nature, and the findings in this study offers a unique understanding of how customers could perceive their destination especially where they are looking to experience the wine estate among similar minded people. A wine estate marketer might wish to be conveying a personality of sophistication and competence, and then be informed by a study like this that the brand is instead being communicated as exciting and sincere. Originality/value The paper illustrates the use of powerful content analysis software, DICTION, to determine the extent to which this text specifically communicates dimensions of brand personality, and in broader terms gives a feel for the tone of text. Regular use of the technique helps wine marketing decision makers to track their own brand’s personality as well those of competitors over time.

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)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,508
Score d'incertitude au seuil0,995

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,000
Communication savante0,0060,005
Science ouverte0,0020,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,087
Tête enseignante GPT0,425
Écart entre enseignants0,338 · 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.

Devis d'étudeSans objet
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

Citations14
Publié2017
Routes d'admission1
Résumé présentoui

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