The consumer trail: Applying best-worst scaling to classical wine attributes
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/20.500.11960/3333 |
Resumo: | The main goal of this study is to gain a better understanding of the buying behavior of wine consumers in Portugal. More specifically, the study identifies extrinsic attributes that influence wine purchase choices in a retail store, crossing-tabulating the results with six classification variables. The authors use the best-worst scaling method with eighteen reference attributes for designing, implementing, and analyzing responses to a survey of 250 wine buyers. Results reveal that the most significant reference attribute is whether consumers had tasted the wine previously. These findings for Portugal are in accordance with what has been observed in other Western countries. The second most important attribute, region of origin, is also commonly identified in the literature as a significant attribute. The classification variables of age and gender help to explain the behavior of the majority attributes. Using a latent class analysis, the authors obtained a set of three segments that are representative of Portuguese wine consumers. The findings presented here have important implications for wineries and wine distributors in their efforts to know their consumers better in an off-premise context and thereby to maximize profit. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
spelling |
The consumer trail: Applying best-worst scaling to classical wine attributesWine attributesConsumer choiceOff-premise settingBest-worst scalingWine consumerThe main goal of this study is to gain a better understanding of the buying behavior of wine consumers in Portugal. More specifically, the study identifies extrinsic attributes that influence wine purchase choices in a retail store, crossing-tabulating the results with six classification variables. The authors use the best-worst scaling method with eighteen reference attributes for designing, implementing, and analyzing responses to a survey of 250 wine buyers. Results reveal that the most significant reference attribute is whether consumers had tasted the wine previously. These findings for Portugal are in accordance with what has been observed in other Western countries. The second most important attribute, region of origin, is also commonly identified in the literature as a significant attribute. The classification variables of age and gender help to explain the behavior of the majority attributes. Using a latent class analysis, the authors obtained a set of three segments that are representative of Portuguese wine consumers. The findings presented here have important implications for wineries and wine distributors in their efforts to know their consumers better in an off-premise context and thereby to maximize profit.2023-05-30T15:23:17Z2016-10-27T00:00:00Z2016-10-272022-12-14T16:03:28Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/20.500.11960/3333eng2212-977410.1016/j.wep.2016.10.002Nunes, FernandoMadureira, TeresaOliveira, José VidalMadureira, Helenainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-06-01T06:45:13Zoai:repositorio.ipvc.pt:20.500.11960/3333Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:59:33.560479Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
The consumer trail: Applying best-worst scaling to classical wine attributes |
title |
The consumer trail: Applying best-worst scaling to classical wine attributes |
spellingShingle |
The consumer trail: Applying best-worst scaling to classical wine attributes Nunes, Fernando Wine attributes Consumer choice Off-premise setting Best-worst scaling Wine consumer |
title_short |
The consumer trail: Applying best-worst scaling to classical wine attributes |
title_full |
The consumer trail: Applying best-worst scaling to classical wine attributes |
title_fullStr |
The consumer trail: Applying best-worst scaling to classical wine attributes |
title_full_unstemmed |
The consumer trail: Applying best-worst scaling to classical wine attributes |
title_sort |
The consumer trail: Applying best-worst scaling to classical wine attributes |
author |
Nunes, Fernando |
author_facet |
Nunes, Fernando Madureira, Teresa Oliveira, José Vidal Madureira, Helena |
author_role |
author |
author2 |
Madureira, Teresa Oliveira, José Vidal Madureira, Helena |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Nunes, Fernando Madureira, Teresa Oliveira, José Vidal Madureira, Helena |
dc.subject.por.fl_str_mv |
Wine attributes Consumer choice Off-premise setting Best-worst scaling Wine consumer |
topic |
Wine attributes Consumer choice Off-premise setting Best-worst scaling Wine consumer |
description |
The main goal of this study is to gain a better understanding of the buying behavior of wine consumers in Portugal. More specifically, the study identifies extrinsic attributes that influence wine purchase choices in a retail store, crossing-tabulating the results with six classification variables. The authors use the best-worst scaling method with eighteen reference attributes for designing, implementing, and analyzing responses to a survey of 250 wine buyers. Results reveal that the most significant reference attribute is whether consumers had tasted the wine previously. These findings for Portugal are in accordance with what has been observed in other Western countries. The second most important attribute, region of origin, is also commonly identified in the literature as a significant attribute. The classification variables of age and gender help to explain the behavior of the majority attributes. Using a latent class analysis, the authors obtained a set of three segments that are representative of Portuguese wine consumers. The findings presented here have important implications for wineries and wine distributors in their efforts to know their consumers better in an off-premise context and thereby to maximize profit. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-10-27T00:00:00Z 2016-10-27 2022-12-14T16:03:28Z 2023-05-30T15:23:17Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/20.500.11960/3333 |
url |
http://hdl.handle.net/20.500.11960/3333 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2212-9774 10.1016/j.wep.2016.10.002 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131665133469696 |