定性比较分析
结构方程建模
旅游
持续性
公司治理
背景(考古学)
业务
可持续发展
环境经济学
环境资源管理
政治学
经济
生态学
地理
计算机科学
考古
财务
机器学习
法学
生物
作者
Myung Ja Kim,C. Michael Hall,Namho Chung,Minseong Kim,Kwonsang Sohn
标识
DOI:10.1080/10941665.2023.2247099
摘要
The study of public transport and tourism, especially domestic tourism, is relatively under-researched, particularly in relation to emerging transport technologies, such as artificial intelligence (AI), and environmental, social, and governance (ESG). To bridge this gap, an integrated research model is created and tested with ESG, air quality, climate change, and AI, applying multi-analysis methods of partial least squares-structural equation modelling (PLS-SEM), multi-group analysis (MGA), and fuzzy-set qualitative comparative analysis (fsQCA) in an Asian context. The three methods provide a well-rounded perspective of the factors that influence tourists' public transport use. Symmetric methods of SEM and MGA identifies key variables and their relationships, while the fsQCA reveals complex combinations of conditions. Results reveal that environmental and social ESG as well as climate change mitigation and sustainable mobility are significant for use of public transport by domestic tourists. High and low AI knowledge groups also have distinctive public transport use characteristics.
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