Wave by Wave, Quantile by Quantile
Unmasking the Tourism‐Carbon‐Growth Nexus in Global Tourism Powerhouses
Dados Bibliográficos
| ID | 21604792 |
|---|---|
| Autores | C M Wang (0000-0002-6804-8145, Department of International Business Ming Chuan University Taipei Taiwan, autor correspondente), Tsung‐Pao Wu (Faculty of Social Science Beijing Institute of Technology Zhuhai China) |
| Ano | 2026 |
| Data de publicação | 2026-03-25 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Sustainable Development (JOURNAL) |
| Identificadores do periódico | ISSN: 0968-0802 • E-ISSN: 1099-1719 |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/sd.70997 |
| OpenAlex | W7140285394 |
| Idioma | EN |
| Citações recebidas | 1 |
| Referências citadas | 62 |
This study applies wavelet quantile correlation (WQC) analysis to examine relationships between CO 2 emissions, GDP, and tourism across 10 major tourist destinations. Findings demonstrate that these relationships vary significantly across countries, quantiles, and time scales. Rapidly industrializing economies (China, Turkey, Mexico, and Thailand) maintain strong positive correlations between GDP and emissions throughout all periods, with tourism exacerbating environmental pressures long‐term. Advanced economies (France, UK, and Germany) successfully decouple economic growth from emissions, exhibiting negative correlations, with tourism's environmental impact improving over time. Diversified economies (USA, Spain, and Italy) show non‐linear relationships, reflecting their transitional stage. The research indicates that sustainable development requires context‐specific policy approaches, with different strategies needed at various economic development stages to balance tourism's economic benefits with environmental costs
Panel data · Quantile · Sustainability · Sustainable development · Sustainable tourism · Tourism · COVID-19 impact on air quality · Diverse Aspects of Tourism Research · Energy, Environment, Economic Growth
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| Obras citantes distintas | 1 |
|---|---|
| Citações por ano | 1 |
| Intervalo de citações | 2026 - 2026 (1) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 1 |