The role of social networks for decision-making about tourism destinations

Detalhes bibliográficos
Autor(a) principal: Vieira, Bruno Miguel
Data de Publicação: 2022
Outros Autores: Borges, Ana Pinto, Vieira, Elvira Pacheco
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/20.500.11960/3355
Resumo: The influence of social networks (SN) on destination selection was studied as part of tourism management/marketing strategy. It also presented the new extension of technology acceptance model (TAM), considering the constructs of perceived usefulness (PU), perceived ease of use (PEOU) attitude towards the use (ATU), perceived enjoyment (PE), e-word-of-mouth (eWOM) and previous influence factors (PIF) to assess tourists' behavioural intention (BI) towards the use of SN for choosing the tourism destination. For such, we performed confirmatory factor analysis (CFA) and the hypotheses were tested by structural equation modelling (SEM). Logistic regression was conducted to explain the influence of SN on choosing and finding destination information. Of all the respondents, 66.5% had used SN to get information or decide on their tourist destination. Facebook and Instagram exhibited greater impact on tourist destination selection than LinkedIn. The results provided insights for marketers, governments and tourism related organisations.
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spelling The role of social networks for decision-making about tourism destinationsSocial networksTourism destinationInfluenceTourist behaviourAnalysed theoriesConstructsTechnology acceptance modelTAMPerceived ease of usePEOUAttitude towards the useATUPrevious influence factorsPIFThe influence of social networks (SN) on destination selection was studied as part of tourism management/marketing strategy. It also presented the new extension of technology acceptance model (TAM), considering the constructs of perceived usefulness (PU), perceived ease of use (PEOU) attitude towards the use (ATU), perceived enjoyment (PE), e-word-of-mouth (eWOM) and previous influence factors (PIF) to assess tourists' behavioural intention (BI) towards the use of SN for choosing the tourism destination. For such, we performed confirmatory factor analysis (CFA) and the hypotheses were tested by structural equation modelling (SEM). Logistic regression was conducted to explain the influence of SN on choosing and finding destination information. Of all the respondents, 66.5% had used SN to get information or decide on their tourist destination. Facebook and Instagram exhibited greater impact on tourist destination selection than LinkedIn. The results provided insights for marketers, governments and tourism related organisations.2023-06-02T11:57:11Z2023-01-01T00:00:00Z20232022-11-23T13:29:48Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/20.500.11960/3355eng1741-810010.1504/IJIMA.2023.128148metadata only accessinfo:eu-repo/semantics/openAccessVieira, Bruno MiguelBorges, Ana PintoVieira, Elvira Pachecoreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-06-08T06:45:26Zoai:repositorio.ipvc.pt:20.500.11960/3355Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:59:58.100270Repositório 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 role of social networks for decision-making about tourism destinations
title The role of social networks for decision-making about tourism destinations
spellingShingle The role of social networks for decision-making about tourism destinations
Vieira, Bruno Miguel
Social networks
Tourism destination
Influence
Tourist behaviour
Analysed theories
Constructs
Technology acceptance model
TAM
Perceived ease of use
PEOU
Attitude towards the use
ATU
Previous influence factors
PIF
title_short The role of social networks for decision-making about tourism destinations
title_full The role of social networks for decision-making about tourism destinations
title_fullStr The role of social networks for decision-making about tourism destinations
title_full_unstemmed The role of social networks for decision-making about tourism destinations
title_sort The role of social networks for decision-making about tourism destinations
author Vieira, Bruno Miguel
author_facet Vieira, Bruno Miguel
Borges, Ana Pinto
Vieira, Elvira Pacheco
author_role author
author2 Borges, Ana Pinto
Vieira, Elvira Pacheco
author2_role author
author
dc.contributor.author.fl_str_mv Vieira, Bruno Miguel
Borges, Ana Pinto
Vieira, Elvira Pacheco
dc.subject.por.fl_str_mv Social networks
Tourism destination
Influence
Tourist behaviour
Analysed theories
Constructs
Technology acceptance model
TAM
Perceived ease of use
PEOU
Attitude towards the use
ATU
Previous influence factors
PIF
topic Social networks
Tourism destination
Influence
Tourist behaviour
Analysed theories
Constructs
Technology acceptance model
TAM
Perceived ease of use
PEOU
Attitude towards the use
ATU
Previous influence factors
PIF
description The influence of social networks (SN) on destination selection was studied as part of tourism management/marketing strategy. It also presented the new extension of technology acceptance model (TAM), considering the constructs of perceived usefulness (PU), perceived ease of use (PEOU) attitude towards the use (ATU), perceived enjoyment (PE), e-word-of-mouth (eWOM) and previous influence factors (PIF) to assess tourists' behavioural intention (BI) towards the use of SN for choosing the tourism destination. For such, we performed confirmatory factor analysis (CFA) and the hypotheses were tested by structural equation modelling (SEM). Logistic regression was conducted to explain the influence of SN on choosing and finding destination information. Of all the respondents, 66.5% had used SN to get information or decide on their tourist destination. Facebook and Instagram exhibited greater impact on tourist destination selection than LinkedIn. The results provided insights for marketers, governments and tourism related organisations.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-23T13:29:48Z
2023-06-02T11:57:11Z
2023-01-01T00:00:00Z
2023
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/20.500.11960/3355
url http://hdl.handle.net/20.500.11960/3355
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1741-8100
10.1504/IJIMA.2023.128148
dc.rights.driver.fl_str_mv metadata only access
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rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
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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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