Attitudes towards machine translation and languages among travelers

Inês Carvalho (), Ana Ramires and Montserrat Iglesias
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Inês Carvalho: Universidade Europeia
Ana Ramires: Universidade Europeia
Montserrat Iglesias: University of Barcelona

Information Technology & Tourism, 2023, vol. 25, issue 2, No 3, 175-204

Abstract: Abstract Machine translation (MT), i.e., automatic translation, is a growing field in artificial intelligence with huge impacts on societies and businesses. Despite its importance for traveling and tourism communication, it has not been approached within tourism research. This study aims to fill this gap in knowledge by analyzing how attitudes toward machine translation are related to tourists’ profiles, travel behaviors, and language mindsets. It comprises two parts. The first one concerns a sample of 2535 individuals, while the second concerns a sub-sample of 907 language tourists (LTs). Specific research goals are set for each study: (1) to compare individuals with opposing viewpoints on the importance of MT in terms of profiles and attitudes toward languages; and (2) to understand how LTs’ profiles and travel experiences differed according to their agreement with the importance of MT in their most significant language trip. Statistical exploratory and inferential analyses have been conducted. We conclude that those with more positive views of MT tend to be younger and less educated, report poorer language skills, and attribute greater importance to the role of English as a lingua franca. Concerning LTs, those who rate MT as less important are more likely to have acquired language skills formally, engage more in cultural activities, and have closer contact with locals during their language trips. Acknowledging the role of MT in their most significant language trip is neither associated with a more unfavorable attitude towards the role of language in tourism nor with perceived diminished travel outcomes.

Keywords: Machine translation; Tourism; Languages; Language tourism (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40558-023-00253-0

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