Publicação
The role of social networks for decision-making about tourism destinations
| 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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| Autores principais: | Vieira, Bruno Miguel |
| Outros Autores: | Borges, Ana Pinto; Vieira, Elvira Pacheco |
| Assunto: | 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 |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso a metadados |
| Instituição associada: | Instituto Politécnico de Viana do Castelo |
| Idioma: | inglês |
| Origem: | Repositório Científico IPVC |
| 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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