Zhu Lei, Hu Jing, Jiahui Xu, Yannan Li, Zhihua Ma, Mangmang Liang, Hongping Teng
{"title":"Spatial-Temporal Evolution Patterns and Influencing Factors of Educational Tourism Resources in China from 1997 to 2021","authors":"Zhu Lei, Hu Jing, Jiahui Xu, Yannan Li, Zhihua Ma, Mangmang Liang, Hongping Teng","doi":"10.5814/j.issn.1674-764x.2024.03.021","DOIUrl":null,"url":null,"abstract":"Abstract: This study systematically explored the spatial evolution characteristics and influencing factors of China's educational tourism resources using a system of spatial analysis techniques. The results show that educational tourism resources can be divided into four types: historical sites, museums, science museums and technology venues, former residences of celebrities, and cultural and educational venues. Among them, former residences of celebrities account for the highest proportion at about 35%, while museums, science museums and technology venues account for the lowest proportion at only about 15%. Educational tourism resources present a condensed distribution trend, forming a “dual-core structure” with the Beijing-Tianjin-Hebei and Yangtze River Delta urban agglomeration as high-density cores. The probability distribution of educational tourism resources is spatially uneven, with distinct fractal characteristics. Hot spots gradually spread from the Yangtze River Delta to the western provinces, and the number of hot spots is increasing. Cold spots are mainly distributed in the southwest of China, and the number remains unchanged, while the phenomenon of polarization is becoming increasingly more prominent. The main factors affecting the distribution of educational tourism resources are as follows, listed in order of their intensity of influence: policy orientation > traffic conditions > tourism resource endowment > source market > social and cultural factors > natural factors. The findings will help in the high-quality development of China's educational tourism.","PeriodicalId":53414,"journal":{"name":"Journal of Resources and Ecology","volume":" 31","pages":"754 - 768"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Resources and Ecology","FirstCategoryId":"1091","ListUrlMain":"https://doi.org/10.5814/j.issn.1674-764x.2024.03.021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 1
Abstract
Abstract: This study systematically explored the spatial evolution characteristics and influencing factors of China's educational tourism resources using a system of spatial analysis techniques. The results show that educational tourism resources can be divided into four types: historical sites, museums, science museums and technology venues, former residences of celebrities, and cultural and educational venues. Among them, former residences of celebrities account for the highest proportion at about 35%, while museums, science museums and technology venues account for the lowest proportion at only about 15%. Educational tourism resources present a condensed distribution trend, forming a “dual-core structure” with the Beijing-Tianjin-Hebei and Yangtze River Delta urban agglomeration as high-density cores. The probability distribution of educational tourism resources is spatially uneven, with distinct fractal characteristics. Hot spots gradually spread from the Yangtze River Delta to the western provinces, and the number of hot spots is increasing. Cold spots are mainly distributed in the southwest of China, and the number remains unchanged, while the phenomenon of polarization is becoming increasingly more prominent. The main factors affecting the distribution of educational tourism resources are as follows, listed in order of their intensity of influence: policy orientation > traffic conditions > tourism resource endowment > source market > social and cultural factors > natural factors. The findings will help in the high-quality development of China's educational tourism.