Spatial Distribution Characteristics and Accessibility of Educational Tourism Along the Yellow River Region from the Perspective of Sustainable Development

Educational tourism serves as a vital avenue for enhancing students’ practical skills and knowledge acquisition. As key components of educational tourism, the spatial distribution and accessibility of educational tourism bases significantly influence the effectiveness of study tour programs. Here, we employed stepwise regression analysis and geographically weighted regression (GWR) to analyze the spatial distribution characteristics, accessibility, and driving factors of educational tourism bases along the Yellow River region. The results indicate that museums accounted for the greatest proportion at 25.14% of the nine types of educational tourism bases. The educational tourism bases show a pattern of “dense in the southeast and sparse in the northwest.” Furthermore, they demonstrate clustered distributions centered around provincial capitals. The key factors influencing the distribution of educational tourism bases, ranked from highest to lowest based on the absolute value of the GWR coefficient, are as follows: 4A and above scenic spots > urbanization rate > internet broadband users > length of classified roads > education expenditure. The accessibility of educational tourism bases is basically consistent in terms of time and spatial distance, both showing better accessibility in the southeast than in the northwest. However, where Sichuan Province and Gansu Province meet, time accessibility is better, while distance accessibility is worse. These findings provide valuable insights for promoting the sustainable development of educational tourism in the Yellow River region.

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Journal
Sustainability
Published
2025-09-09
DOI
https://doi.org/10.3390/su17188095
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Spatial Distribution Characteristics and Accessibility of Educational Tourism Along the Yellow River Region from the Perspective of Sustainable Development

Chuan-hao Yang, Qipeng Zhang, Qian Wang, Dichen Zhao
Sustainability
Diverse Aspects of Tourism Research
article

Spatial Distribution Characteristics and Accessibility of Educational Tourism Along the Yellow River Region from the Perspective of Sustainable Development

Chuan-hao Yang, Qipeng Zhang, Qian Wang, Dichen Zhao
article en

Abstract

Educational tourism serves as a vital avenue for enhancing students’ practical skills and knowledge acquisition. As key components of educational tourism, the spatial distribution and accessibility of educational tourism bases significantly influence the effectiveness of study tour programs. Here, we employed stepwise regression analysis and geographically weighted regression (GWR) to analyze the spatial distribution characteristics, accessibility, and driving factors of educational tourism bases along the Yellow River region. The results indicate that museums accounted for the greatest proportion at 25.14% of the nine types of educational tourism bases. The educational tourism bases show a pattern of “dense in the southeast and sparse in the northwest.” Furthermore, they demonstrate clustered distributions centered around provincial capitals. The key factors influencing the distribution of educational tourism bases, ranked from highest to lowest based on the absolute value of the GWR coefficient, are as follows: 4A and above scenic spots > urbanization rate > internet broadband users > length of classified roads > education expenditure. The accessibility of educational tourism bases is basically consistent in terms of time and spatial distance, both showing better accessibility in the southeast than in the northwest. However, where Sichuan Province and Gansu Province meet, time accessibility is better, while distance accessibility is worse. These findings provide valuable insights for promoting the sustainable development of educational tourism in the Yellow River region.

SustainabilityVol. 17(18)
Liaocheng University (CN), China University of Geosciences (Beijing) (CN), Beijing Academy of Artificial Intelligence (CN), Gansu Normal University for Nationalities (CN)
Openalex Percentile: Top 67%
Diverse Aspects of Tourism Research
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