Spatiotemporal interaction characteristics and transition mechanism of tourism environmental efficiency in China.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
30 Aug 2023
Historique:
received: 08 03 2023
accepted: 03 08 2023
medline: 31 8 2023
pubmed: 31 8 2023
entrez: 30 8 2023
Statut: epublish

Résumé

High-quality development is the theme of China's economic and social development in the new era, and it is also an objective need for tourism development in the 14th Five-Year Plan period. This study presents an investigation of China's patterns of tourism environmental efficiency from the perspective of spatiotemporal interactions. A nested analytical framework of quantile regression and spatiotemporal leaps was used to explore the driving mechanism patterns of tourism environmental efficiency under different leap types. Based on various spatial analysis methods, we posit that the patterns of tourism environmental efficiency differ through spatial associations, dynamic evolutions, and transition mechanisms. Our results indicate that there is a dynamic convergence trend of the overall differences in tourism environmental efficiency in China from 2000 to 2020 where a significant clustering phenomenon is observed in space and the level of spatial clustering gradually tends to be stable. In terms of local spatial structures and the dependence directions of tourism environmental efficiency, China's northwest and northeast regions are more volatile, while eastern coastal regions are relatively stable. Spatiotemporal leaps of tourism environmental efficiency show certain transfer inertia with strong spatial dependence or path-locked characteristics, among which most central and western regions always maintain high carbon emission attributes. These regions are the most limited in the synergy of tourism environmental efficiency. The spatiotemporal network patterns of tourism environmental efficiency are mainly based on positive correlations and show strong spatial integration. However, a few neighboring provinces still have a certain degree of spatiotemporal competition. Driving patterns of the spatiotemporal leaps in tourism environmental efficiency among regions differ greatly. The eastern coastal provinces are driven by population-urbanization constraint patterns, and the northwest, southwest, and northeast regions are driven by technology regulation patterns. From the southeast to the northwest, the leap in the environmental efficiency of China's tourism gradually shows a stepwise pattern of "congruent constraint-reverse development-congruent development." Therefore, the government should not only consider these various driving/constraining factors but also combine different environmentally-efficient tourism clustering types and transition paths to emphasize differentiated environmental tourism measures. This can help avoid the closure of inter-provincial tourism policies through inter-regional synergy.

Identifiants

pubmed: 37648699
doi: 10.1038/s41598-023-40047-2
pii: 10.1038/s41598-023-40047-2
pmc: PMC10469166
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

14196

Subventions

Organisme : a grant from the Guangzhou Huashang College
ID : No.2022HSKT02
Organisme : a grant from the Guangzhou Huashang College
ID : No.2021HSXK10
Organisme : the Philosophy and Social Sciences of Guangzhou in the 14th Five-year Period
ID : 2021GZGJ73
Organisme : the Philosophy and Social Sciences of Guangdong Province in the 13th Five-year Period
ID : GD20XGL06
Organisme : a grant from the Guangzhou Science Plan Project
ID : No.202201011273

Informations de copyright

© 2023. Springer Nature Limited.

Références

PLoS One. 2021 Nov 15;16(11):e0257400
pubmed: 34780492
PLoS One. 2022 Oct 26;17(10):e0276175
pubmed: 36288341

Auteurs

Zhenjie Liao (Z)

Guangzhou Huashang College, Guangzhou, 511300, China.

Lijuan Zhang (L)

Guangzhou Huashang College, Guangzhou, 511300, China. 281746568@qq.com.

Classifications MeSH