Like, tag and share: bolstering social media marketing to improve intention to visit a nature-based tourism destination

Gaffar, Vanessa; Tjahjono, Benny; Abdullah, Tamrin; Sukmayadi, Vidi

doi:10.1108/tr-05-2020-0215

Cited by 48 publications

(44 citation statements)

References 63 publications

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“…For example, when the policymakers try to encourage tourism, it is important to know that social media only allow them to effectively reach younger audiences. Also, social media is efficient in disseminating information (Gaffar et al , 2021) and sometimes with false information. This could explain why younger respondents showed higher level of subjective norm to travel intention link.…”

Section: Conclusion Contribution Implication Limitation and Future Re...mentioning

confidence: 99%

Tourists’ travel intention: revisiting the TPB model with age and perceived risk as moderator and attitude as mediator

Wang

Yeh

Chen

et al. 2022

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Purpose This study aims to understand tourists’ travel intention during the COVID-19 pandemic by using the theory of planned behavior (TPB) with additional causal links and moderators. The three research objectives of this study are to explore basic causality, mediating effects of attitude and moderating effects of age and perceived risk, of the extended TPB model, respectively. Design/methodology/approach An online survey was conducted in Taiwan during the COVID-19 pandemic. In total, the survey generated 351 responses. The structural model analysis was performed to test the cause-and-effect relationships in the traditional TPB model and the mediating role of an individual’s attitude regarding travel during the COVID-19 pandemic. The SmartPLS multi-group analysis procedure was applied to test the moderation effects of age and perceived risk. Findings It is found that the perceived behavioral control is the main contributor of travel intention for the traditional TPB while attitude partially mediates the relationship between subjective norm and travel intention for the test of mediation. Also, moderation tests confirm that both age and perceived risk show significant moderating effect only on subjective norm to travel intention relationship. Originality/value The novelty of this research is that this study proposed and verified the mediating influence of attitude and two additional paths, the moderating influence of age and perceived risk, which deepened the understanding of the TPB model and the impact of COVID-19 on travel intention. Because TPB model is context-dependent, using one mediating and two moderating variables allows the study to understand how TPB functions in a different situation.

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Section: Conclusion Contribution Implication Limitation and Future Re...mentioning

confidence: 99%

Tourists’ travel intention: revisiting the TPB model with age and perceived risk as moderator and attitude as mediator

Wang

Yeh

Chen

et al. 2022

View full text Add to dashboard Cite

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“…Social media has gained momentum in tourism marketing to gain insights into consumer experience (Gaffar et al , 2021; Peco-Torres et al , 2021). While analysing UGC on social media has become more commonplace in recent years, a strong focus is placed on Facebook, followed by YouTube and Twitter (Shawky et al , 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying hidden semantic structures in Instagram data: a topic modelling comparison

Egger

2021

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Purpose Intrigued by the methodological challenges emerging from text complexity, the purpose of this study is to evaluate the effectiveness of different topic modelling algorithms based on Instagram textual data. Design/methodology/approach By taking Instagram posts captioned with #darktourism as the study context, this research applies latent Dirichlet allocation (LDA), correlation explanation (CorEx), and non-negative matrix factorisation (NMF) to uncover tourist experiences. Findings CorEx outperforms LDA and NMF by classifying emerging dark sites and activities into 17 distinct topics. The results of LDA appear homogeneous and overlapping, whereas the extracted topics of NMF are not specific enough to gain deep insights. Originality/value This study assesses different topic modelling algorithms for knowledge extraction in the highly heterogeneous tourism industry. The findings unfold the complexity of analysing short-text social media data and strengthen the use of CorEx in analysing Instagram content.

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“…Logical and persuasive reviews shape the purchase intention (Park et al, 2007). Positively balanced reviews increase customer attraction and travel intentions (Gaffar et al, 2021). Bahja et al (2019) advocated the critical role of online reviews in the cruise vacations.…”

Section: Ewom and Travel Intentionsmentioning

confidence: 99%

“…According to Roozen and Raedts (2018), online reviews are crucial influencers in travelers' destination preferences. The quality of online reviews elicits positive feelings about the destination (Gaffar et al, 2021). Despite the growing importance of online communications in the tourism industry, scant studies addressed the role of eWOM in shaping DP (Litvin et al, 2008;Park and Lee, 2008).…”

Section: Ewom and Destination Preferencementioning

confidence: 99%

eWOM, destination preference and consumer involvement – a stimulus-organism-response (SOR) lens

Yadav

Verma

Chikhalkar

2021

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Purpose This study aims to examine the moderated-mediation impact of consumer involvement and destination preference on travel intentions. Stimulus-Organism-Response (SOR) and elaboration likelihood model (ELM) guided the conceptual framework of this study. Design/methodology/approach Churchill’s (1979) guidelines instrumentalize the scientific development and validation of measurement scales for data collection. The authors used higher-order multivariate analyzes such as structural equation modeling (SEM) and the Hayes process model for evaluating the hypotheses. The study uses Bauer et al. (2006) method to assess the conditional indirect effects of Electronic word of mouth (eWOM) on travel intention through destination preference at varying levels of consumer involvement. Findings SOR and ELM model successfully explained the moderated-mediation effect of eWOM, consumer involvement and destination preference in influencing the travel intentions. Results broaden the applicability of SOR and ELM in tourism marketing. Results indicate that consumer involvement moderated the direct and indirect influence of eWOM on travel intention via destination preference, such that the eWOM influence in shaping travel intention is stronger for highly involved consumers. Research limitations/implications The present study broadens the applicability of integrated SOR and ELM models to explain the moderated-mediation network between eWOM and travel intentions. Study findings offer new avenues to tourism marketers for the magnified effect of eWOM for promoting tourism. Tourism marketers may use customer journeys to build destination preference through organic information exchange with prospective travelers. Future researchers and practitioners can build prescriptive and predictive models based on altered levels of consumer involvement. Originality/value Present study pioneers in examining the interactive effect of moderated mediation network of consumer involvement and destination preference in shaping the travel intention. Grounded in SOR and ELM model, the present study is a trailblazer to offer the integrated moderated-mediation model between eWOM, destination preference, consumer involvement and travel intention.

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Like, tag and share: bolstering social media marketing to improve intention to visit a nature-based tourism destination

Cited by 48 publications

References 63 publications

Tourists’ travel intention: revisiting the TPB model with age and perceived risk as moderator and attitude as mediator

Tourists’ travel intention: revisiting the TPB model with age and perceived risk as moderator and attitude as mediator

Identifying hidden semantic structures in Instagram data: a topic modelling comparison

eWOM, destination preference and consumer involvement – a stimulus-organism-response (SOR) lens

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