Investigating potential tourists' attitudes toward artificial intelligence services: a market segmentation approach

Ja Young (Jacey) Choe*, Emmanuel Kwame Opoku, Javier Calero Cuervo, Raymond Adongo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Purpose: This study profiles and segments potential tourists on the basis of their various attitudes toward artificial intelligence (AI) services. Furthermore, this study distinguishes descriptors among the different clusters, such as preference for using diverse AI services, overall image of AI services, willingness to use AI services (WUAI), willingness to pay more for AI services (WPAI) in tourism and hospitality, and characteristics of respondents.

Design/methodology/approach: An online survey was conducted in South Korea. Data on 758 potential tourists were used for K-means cluster analysis.

Findings: This study identified three distinct tourist segments with differentiated attitudes toward AI services: the group aspiring to use or fantasizing about AI services (Cluster 1), the group being knowledgeable and supportive of AI services (Cluster 2), and the group having low interest about AI services (Cluster 3).

Practical implications: Members of Cluster 2 were the most marketable as this segment exhibited the greatest knowledge of and support for AI services, while Cluster 1 would be an ideal segment to launch and test novel AI services.

Originality/value: This study extends the authors’ knowledge of AI scholarship by unpacking the existing market segments, which could be tapped to sustain AI penetration in the tourism industry. Hence, this study contributes to existing debates on AI scholarship, which is predominated by conceptual reflections and issues of AI services in the tourism and hospitality field.

Original languageEnglish
JournalJournal of Hospitality and Tourism Insights
Early online date10 Oct 2023
DOIs
Publication statusE-pub ahead of print - 10 Oct 2023

Keywords

  • Artificial intelligence
  • Cluster analysis
  • Overall image
  • Service preference
  • Willingness to pay more
  • Willingness to use

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management

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