Selection and empirical study of sustainable development indicators for ecotourism in the Li River Basin under the context of culture–tourism–creativity agglomeration: based on improved Spearman relevance-combined weighting

Accurately assessing the sustainability of ecotourism in fragile karst areas is crucial, but it is often hindered by indicator collinearity and weighted bias. A pressure state response assessment framework was constructed using the Lijiang River Basin (2010–2023) as a case study. To improve evaluation accuracy, variance inflation factor (VIF) and enhanced Spearman rank correlation are used to screen structural indicators, while game theory models are used to balance subjective and objective weights. The results show that the optimized method has been proven to be very effective. Removing 37.5% of redundant indicators still maintains a cumulative variance contribution rate of 89.42%, reducing the average VIF to 2.35, with a correlation of 0.945 with the official evaluation ranking. In terms of time, the sustainable development index of ecological tourism in the watershed has significantly increased from 0.471 to 0.710, and the system coupling coordination has increased from 0.520 to 0.760. However, there is still a clear spatial imbalance, with scores ranging from 0.812 in Xiufeng District to 0.582 in Pingle County in 2023. Although the watershed is showing a positive trend of evolution, the persistent regional differences require differentiated governance. Ultimately, this improved model provides a effective tool for future ecological.

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Journal
La Houille Blanche
Published
2026-09-17
DOI
https://doi.org/10.1080/27678490.2026.2697473
Primary Topic
Diverse Aspects of Tourism Research
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article
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article

Selection and empirical study of sustainable development indicators for ecotourism in the Li River Basin under the context of culture–tourism–creativity agglomeration: based on improved Spearman relevance-combined weighting

Tiantian Jia
La Houille Blanche
Diverse Aspects of Tourism Research
article

Selection and empirical study of sustainable development indicators for ecotourism in the Li River Basin under the context of culture–tourism–creativity agglomeration: based on improved Spearman relevance-combined weighting

Tiantian Jia
article en

Abstract

Accurately assessing the sustainability of ecotourism in fragile karst areas is crucial, but it is often hindered by indicator collinearity and weighted bias. A pressure state response assessment framework was constructed using the Lijiang River Basin (2010–2023) as a case study. To improve evaluation accuracy, variance inflation factor (VIF) and enhanced Spearman rank correlation are used to screen structural indicators, while game theory models are used to balance subjective and objective weights. The results show that the optimized method has been proven to be very effective. Removing 37.5% of redundant indicators still maintains a cumulative variance contribution rate of 89.42%, reducing the average VIF to 2.35, with a correlation of 0.945 with the official evaluation ranking. In terms of time, the sustainable development index of ecological tourism in the watershed has significantly increased from 0.471 to 0.710, and the system coupling coordination has increased from 0.520 to 0.760. However, there is still a clear spatial imbalance, with scores ranging from 0.812 in Xiufeng District to 0.582 in Pingle County in 2023. Although the watershed is showing a positive trend of evolution, the persistent regional differences require differentiated governance. Ultimately, this improved model provides a effective tool for future ecological.

La Houille BlancheVol. 112(1)
Shanxi University of Finance and Economics (CN)
Decent work and economic growth
Openalex Percentile: Top 5%
Diverse Aspects of Tourism Research
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Selection and empirical study of sustainable development indicators for ecotourism in the Li River Basin under the context of culture–tourism–creativity agglomeration: based on improved Spearman relevance-combined weighting — Tiantian Jia · La Houille Blanche (2026) | TGRS Research Map | TGRS