中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Research on the spatial correlation network and its driving factors for synergistic development of pollution reduction, carbon reduction, greening, and growth in China's tourism industry

文献类型:期刊论文

作者Li, Ying3,4,5; Hao, Shizhuan1,5; Liu, Yaping5; Chen, Beilei5; Zou, Tongqian2,5
刊名JOURNAL OF ENVIRONMENTAL MANAGEMENT
出版日期2025-03-01
卷号377页码:124579
关键词Tourism industry Social network analysis Coupled coordination degree model Modified gravity model
ISSN号0301-4797
DOI10.1016/j.jenvman.2025.124579
产权排序3
文献子类Article
英文摘要The integrated development of pollution reduction, carbon reduction, greening, and growth (PR-CR-G-G) has become a crucial component of China's green transformation. Encouraging a virtuous cycle of these elements within the tourism sector not only supports the goals of carbon peak and carbon neutrality but also improves the overall quality of tourism and accelerates its green transformation. This study covers 30 provinces in China and develops an index system for Tourism PR-CR-G-G from 2011 to 2022. The coupled coordination degree model (CCD) is utilized to assess the level of synergistic development in these areas. Additionally, a modified gravity model is applied to establish a Tourism PR-CR-G-G Spatial correlation network. Social network analysis is then used to examine the characteristics and formation mechanisms of this network. The findings indicate that: 1) The overall coupling coordination value for tourism pollution reduction, carbon reduction, green expansion, and growth in China is on an upward trajectory, but significant spatial disparities exist, with the ranking being East (0.444) > Central (0.425) > Northeast (0.369) > West (0.365); 2) The spatial correlation within the synergistic development network of Tourism PR-CR-G-G in China is strong, displaying a high-level characteristic. A small number of provinces hold central positions, exerting a noticeable siphoning effect that reduces the overall network efficiency; 3) The network shows distinct grouping patterns, with each province having a clear functional role, creating a well-defined operational chain; 4) Quadratic assignment procedure (QAP) analysis shows that the generation of PR-CR-G-G network in China's tourism industry is positively correlated with the level of economic development, industry structure, external openness, and urbanization level and negatively correlated with technological development and geographical distance.
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WOS关键词ENERGY-CONSUMPTION ; FOOTPRINT ; EMISSIONS
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:001431153800001
出版者ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
源URL[http://ir.igsnrr.ac.cn/handle/311030/213320]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Li, Ying; Hao, Shizhuan
作者单位1.Management & Sci Univ, Sch Hospitality & Creat Arts, Shah Alam 40100, Malaysia
2.Silk Rd Int Univ Tourism & Cultural Heritage, Samarkand 140100, Uzbekistan;
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China;
4.Stuttgart Univ, High Performance Comp Ctr Stuttgart, D-70569 Stuttgart, Germany;
5.Beijing Int Studies Univ, China Acad Culture & Tourism, Beijing 100024, Peoples R China;
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GB/T 7714
Li, Ying,Hao, Shizhuan,Liu, Yaping,et al. Research on the spatial correlation network and its driving factors for synergistic development of pollution reduction, carbon reduction, greening, and growth in China's tourism industry[J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT,2025,377:124579.
APA Li, Ying,Hao, Shizhuan,Liu, Yaping,Chen, Beilei,&Zou, Tongqian.(2025).Research on the spatial correlation network and its driving factors for synergistic development of pollution reduction, carbon reduction, greening, and growth in China's tourism industry.JOURNAL OF ENVIRONMENTAL MANAGEMENT,377,124579.
MLA Li, Ying,et al."Research on the spatial correlation network and its driving factors for synergistic development of pollution reduction, carbon reduction, greening, and growth in China's tourism industry".JOURNAL OF ENVIRONMENTAL MANAGEMENT 377(2025):124579.

入库方式: OAI收割

来源:地理科学与资源研究所

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