<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, China’s tourism sector has experienced rapid growth. Ecological economic resilience, a crucial metric for assessing urban comprehensive strength, has increasingly garnered attention from academics and governmental bodies. In this study, we assess the resilience of tourism cities’ ecological economies using 28 selected indicators. By employing the entropy value method, we establish the weights for these indicators, facilitating an exploration of their temporal evolution. Spatial evolution characteristics are examined through spatial autocorrelation analysis, incorporating the global Moran’s I index. Utilizing a coupled coordination model, we calculate the ecological, economic resilience, and urban tourism development levels across various cities. Our findings indicate a significant increase in ecological resilience, rising from 0.2129 in 2014 to 0.2807 in 2023. The Moran’s I index rises from the trough value of 0.0532 to the peak value of 0.0951 and then steadily declines to 0.0738, presenting a fluctuating trend of alternately increasing and decreasing development. The coupling coordination degree is more significant than 0.5 in 2023, which is at a highly developed stage. This study serves as a reference for the sustainable development of urban tourism.</p>
</abstract>

In recent years, China’s tourism sector has experienced rapid growth. Ecological economic resilience, a crucial metric for assessing urban comprehensive strength, has increasingly garnered attention from academics and governmental bodies. In this study, we assess the resilience of tourism cities’ ecological economies using 28 selected indicators. By employing the entropy value method, we establish the weights for these indicators, facilitating an exploration of their temporal evolution. Spatial evolution characteristics are examined through spatial autocorrelation analysis, incorporating the global Moran’s I index. Utilizing a coupled coordination model, we calculate the ecological, economic resilience, and urban tourism development levels across various cities. Our findings indicate a significant increase in ecological resilience, rising from 0.2129 in 2014 to 0.2807 in 2023. The Moran’s I index rises from the trough value of 0.0532 to the peak value of 0.0951 and then steadily declines to 0.0738, presenting a fluctuating trend of alternately increasing and decreasing development. The coupling coordination degree is more significant than 0.5 in 2023, which is at a highly developed stage. This study serves as a reference for the sustainable development of urban tourism.

Spatio-temporal evolutionary analysis of ecological economic resilience in typical Chinese tourist cities

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, China’s tourism sector has experienced rapid growth. Ecological economic resilience, a crucial metric for assessing urban comprehensive...

Spatio-temporal evolutionary analysis of ecological economic resilience in typical Chinese tourist cities

Pubblicato online: 22 mag 2024

Pagine: -

Ricevuto: 01 feb 2024

Accettato: 14 apr 2024

DOI: https://doi.org/10.2478/amns-2024-1185

Parole chiave
Entropy value method, Spatial autocorrelation method, Moran’s I index, Coupled coordination model, Ecological and economic resilience

© 2024 Jing Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Spatio-temporal evolutionary analysis of ecological economic resilience in typical Chinese tourist cities

Pubblicato online: 22 mag 2024

Pagine: -

Ricevuto: 01 feb 2024

Accettato: 14 apr 2024

DOI: https://doi.org/10.2478/amns-2024-1185

Parole chiaveEntropy value method, Spatial autocorrelation method, Moran’s I index, Coupled coordination model, Ecological and economic resilience

© 2024 Jing Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Entropy value method, Spatial autocorrelation method, Moran’s I index, Coupled coordination model, Ecological and economic resilience