TY - GEN
T1 - Resilient Governance in Tourism Urbanization
T2 - 2025 International Conference on Management Science and Computer Engineering, MSCE 2025
AU - Tang, Chi Fong
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s)
PY - 2025/9/23
Y1 - 2025/9/23
N2 - With the rapid advancement of tourism urbanization, Macao faces multiple challenges including economic transformation, social restructuring, and cultural preservation. Traditional government-led models struggle to effectively respond to the increasingly diverse demands of multiple stakeholders, creating an urgent need for innovative governance paradigms to enhance urban resilience. Based on stakeholder theory, this research explores the construction of a”government-market-society” collaborative innovation model for resilient governance through questionnaire surveys of local residents, Hong Kong and Taiwan tourists, mainland Chinese tourists, and international tourists. The findings reveal significant differences among groups in tourism perception, cultural identity, and community participation. To establish a quantitative model and explore the complex relationships between the stakeholder perceptions and governance expectations, XGBoost regression algorithm is used in this study. The study finds that there are significant differences in perceptual aspects between the above-mentioned groups, and there is consensus on some key issues such as promoting sustainable development and improving urban competitiveness. The study finds that resilient governance in tourism urbanization relies on the empowerment to reach stakeholder consensus, constructing diversified collaborative governance mechanism, and continuously improving institutional supply in dynamic environment. Taking Macao as the case study, this study uses machine learning method and stakeholder analysis to explore the new theoretical ideas and provide empirical support for constructing resilient and innovative “tourism+” collaborative governance mechanism, which promote urban sustainable development.
AB - With the rapid advancement of tourism urbanization, Macao faces multiple challenges including economic transformation, social restructuring, and cultural preservation. Traditional government-led models struggle to effectively respond to the increasingly diverse demands of multiple stakeholders, creating an urgent need for innovative governance paradigms to enhance urban resilience. Based on stakeholder theory, this research explores the construction of a”government-market-society” collaborative innovation model for resilient governance through questionnaire surveys of local residents, Hong Kong and Taiwan tourists, mainland Chinese tourists, and international tourists. The findings reveal significant differences among groups in tourism perception, cultural identity, and community participation. To establish a quantitative model and explore the complex relationships between the stakeholder perceptions and governance expectations, XGBoost regression algorithm is used in this study. The study finds that there are significant differences in perceptual aspects between the above-mentioned groups, and there is consensus on some key issues such as promoting sustainable development and improving urban competitiveness. The study finds that resilient governance in tourism urbanization relies on the empowerment to reach stakeholder consensus, constructing diversified collaborative governance mechanism, and continuously improving institutional supply in dynamic environment. Taking Macao as the case study, this study uses machine learning method and stakeholder analysis to explore the new theoretical ideas and provide empirical support for constructing resilient and innovative “tourism+” collaborative governance mechanism, which promote urban sustainable development.
KW - Collaborative innovation
KW - Macao
KW - Multiple stakeholders
KW - Resilient governance
KW - Tourism urbanization
KW - XGBoost Regression
UR - https://www.scopus.com/pages/publications/105021565146
U2 - 10.1145/3760023.3760039
DO - 10.1145/3760023.3760039
M3 - Conference contribution
AN - SCOPUS:105021565146
T3 - Proceedings of 2025 International Conference on Management Science and Computer Engineering, MSCE 2025
SP - 86
EP - 92
BT - Proceedings of 2025 International Conference on Management Science and Computer Engineering, MSCE 2025
PB - Association for Computing Machinery, Inc
Y2 - 6 June 2025 through 8 June 2025
ER -