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Optimizing Sustainable Tourism: A Multi-Objective Framework for Juneau and Beyond

文献类型： 外文期刊

作者： Pan, Jing 1 ; Yang, Haoran 3 ; Wang, Zihao 4 ; Peng, Bo 5 ; Li, Shaoning 2 ;

作者机构： 1.Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan 430074, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Inst Forestry & Pomol, Beijing 100093, Peoples R China

3.Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, Wuhan 430074, Peoples R China

4.Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan 430074, Peoples R China

5.Beijing Forestry Univ, Sch Ecol & Nat Conservat, Beijing 100083, Peoples R China

关键词： sustainable tourism; multi-objective optimization; economic-environmental-social balance; AHP-entropy weighting; tourist carrying capacity

期刊名称：SUSTAINABILITY （ 影响因子：3.3； 五年影响因子：3.6 ）

ISSN：

年卷期： 2025 年 17 卷 16 期

页码：

收录情况： SCI

摘要： This study develops a multi-dimensional sustainable tourism optimization framework for Juneau, Alaska, integrating economic, social, and environmental dimensions to balance tourism-driven prosperity with ecological and socio-cultural integrity. Utilizing a hybrid Analytic Hierarchy Process and entropy weighting method, the model assigns robust indicator weights. Optimized via the NSGA-II algorithm, it identifies an optimal tourist threshold, achieved through a strategic tax adjustment. This policy not only sustains economic revenue at USD 325 million but also funds a critical feedback loop: revenue reinvestment into environmental conservation and social infrastructure, which stabilizes cost indices and enhances community well-being. The model's projections show this approach significantly mitigates environmental degradation, notably glacier retreat, and alleviates social pressures such as infrastructure overload and resident dissatisfaction. A key contribution of this research is the framework's adaptability, which was validated through its application to Barcelona, Spain. There, the framework was recalibrated with social indicators tailored to address urban overtourism, achieving substantial reductions in housing and congestion costs alongside environmental improvements, while economic recovery was maintained. Sensitivity analyses confirm the model's stability, though data limitations and subjective weighting suggest future enhancements via real-time analytics and dynamic modeling. Key policy recommendations include dynamic tourist caps, diversified attractions, and community engagement platforms, offering scalable solutions for global tourism destinations. This framework advances sustainable tourism by providing a blueprint to decouple economic growth from ecological and social harm, ensuring the longevity of natural and cultural assets amidst climate challenges.

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