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

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.

KEYWORDS:

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

Acknowledgements

The authors would like to acknowledge the editors and anonymous reviewers for their time and contributions to this study. The authors also thank Ms. Yeni Kim for her dedicated help in managing this grant project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by a grant from Kyung Hee University in 2022 [grant number KHU-20220778].