Does using public transport affect tourist subject well-being and behaviour relevant to sustainability? Value-attitude-behaviour theory and artificial intelligence benefits
(2023) In Current Issues in Tourism- 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... (More)
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.
(Less)
- author
- Kim, Myung Ja ; Hall, C. Michael LU ; Chung, Namho ; Kim, Minseong and Sohn, Kwonsang
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- in press
- subject
- keywords
- AI benefits, multi-analysis methods, Public transport, South Korea, subjective well-being, VAB theory
- in
- Current Issues in Tourism
- publisher
- Taylor & Francis
- external identifiers
-
- scopus:85161556037
- ISSN
- 1368-3500
- DOI
- 10.1080/13683500.2023.2214721
- language
- English
- LU publication?
- yes
- id
- dba85643-2b98-4875-bcb7-9c789b079db6
- date added to LUP
- 2023-08-23 11:13:06
- date last changed
- 2023-08-23 11:13:06
@article{dba85643-2b98-4875-bcb7-9c789b079db6,
abstract = {{<p>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.</p>}},
author = {{Kim, Myung Ja and Hall, C. Michael and Chung, Namho and Kim, Minseong and Sohn, Kwonsang}},
issn = {{1368-3500}},
keywords = {{AI benefits; multi-analysis methods; Public transport; South Korea; subjective well-being; VAB theory}},
language = {{eng}},
publisher = {{Taylor & Francis}},
series = {{Current Issues in Tourism}},
title = {{Does using public transport affect tourist subject well-being and behaviour relevant to sustainability? Value-attitude-behaviour theory and artificial intelligence benefits}},
url = {{http://dx.doi.org/10.1080/13683500.2023.2214721}},
doi = {{10.1080/13683500.2023.2214721}},
year = {{2023}},
}