Suchergebnisse

Purpose
The Metaverse is rapidly reshaping the understanding of tourism, yet the public perception of this new domain remains largely uncharted empirically. This paper aims to build on the technology acceptance model (TAM) and diffusion of innovations theory (DIT) to fill this gap, offering crucial insights that could inform scholars and practitioners in both the tourism and technology sectors.


Design/methodology/approach
Using a big-data approach, the authors applied machine learning to scrape comments made by social media users on recent popular posts or videos related to tourism in the Metaverse from three prominent social media platforms. The cleaning process narrowed down 15,461 comments to 2,650, which were then analysed using thematic, emotion and sentiment analysis techniques.


Findings
The thematic analysis revealed that virtual tourism evokes a complex range of public beliefs. While many express awe and excitement toward its immersive capabilities, others remain sceptical about authenticity compared to physical travel. Additional themes show people draw comparisons to real-world tourism, discuss technology's role and note educational value and novelty. However, some comments raise concerns about potential societal harms, exploitation and mental health impacts. Sentiment analysis found over half of the comments positive, though some were negative. Emotion analysis showed contentment, happiness and excitement as most frequent, though sadness, worry and loneliness also featured. Overall, perceptions of Metaverse tourism encompass enthusiasm yet substantial ambivalence.


Originality/value
To the best of the authors' knowledge, this study is one of the first to comprehensively analyse public discussions on Metaverse tourism. It takes TAM and Rogers's DIT a step further and provides fresh insights into how these theories can be employed in the emerging field of Metaverse tourism. The themes revealed new conceptual insights into multidimensional factors shaping public beliefs about Metaverse tourism and thus informing scholarly research on virtual interaction and technology acceptance regarding Metaverse tourism. In addition, the results can help tourism providers, platforms and marketers address salient public beliefs and sentiments/attitudes in developing marketing offerings, experiences and communications. Over time, this analysis methodology can be used to track the evolving public perceptions of Metaverse tourism.

This study addresses the effectiveness of political advertising in an extreme context, during war-time. A self-administered cross-sectional survey was used to collect data during the 2016 parliamentary elections in Syria. Structural equation modelling was utilized to test the hypothetical model and its invariance related to political involvement. The results indicated that beliefs are a four-dimensional structure consisting of information, veracity, sarcasm, and cynicism. Furthermore, war-time perceptions were found to negatively affect attitude towards political advertising via sarcasm among less politically involved voters. Negative attitude was found to be linked to lower levels of veracity among such voters and to higher levels of cynicism for those who are highly involved in politics. Negative attitudes regarding political advertising were found for lowering the chances for watching advertisements, for supporting a candidate, and for willingness to vote. The results also revealed that paying attention to political advertising does not relate to voters' intention to vote. This study is the first of its kind to empirically validate a conceptual model predicting voters' turnout behaviour based on voters' war-time perceptions, beliefs and attitudes regarding political advertising in an authoritarian setting. In addition, this study investigates whether the effects of the proposed model may be moderated by voters' political involvement.

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