Does using public transport affect tourist subject well-being and behaviour relevant to sustainability? Value-attitude-behaviour theory and artificial intelligence benefits

Myung Ja Kim, C. Michael Hall, Namho Chung, Minseong Kim, Kwonsang Sohn

Research output: Contribution to journalArticlepeer-review

Abstract

Increasing tourist use of public transport is a potentially significant means of reducing greenhouse gas emissions. There are limited theoretically informed studies that focus on domestic tourist use of public transport, particularly in an Asian cultural context (e.g. South Korea). To bridge the research gap, this study applies and tests an extended value-attitude-behaviour (EVAB) theory, including personal and social norms and subjective well-being, along with artificial intelligence (AI) benefits as a moderator based on partial least squares-structural equation modelling, multi-group analysis, fuzzy-set qualitative comparative analysis and deep learning in South Korea. The high and low AI benefit groups are compared to each other according to multi-analysis methods. Results revealed that the EVAB model well explains travellers’ behaviour with public transport and AI benefits partially moderate the research model, showing some unique differences.

Original languageEnglish
Pages (from-to)1666-1682
Number of pages17
JournalCurrent Issues in Tourism
Volume27
Issue number10
DOIs
Publication statusPublished - 2024

Subject classification (UKÄ)

  • Transport Systems and Logistics

Free keywords

  • AI benefits
  • multi-analysis methods
  • Public transport
  • South Korea
  • subjective well-being
  • VAB theory

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