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Article

Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China

by 1,2,†, 2,†, 3, 2, 4 and 2,*
1
School of Management, Jinan University, Guangzhou 510632, China
2
Shenzhen Tourism College, Jinan University, Shenzhen 518053, China
3
Department of Physical Education, Guizhou University of Finance and Economics, Guiyang 550000, China
4
School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong, China
*
Author to whom correspondence should be addressed.
The authors contribute equally to this article.
Academic Editors: Wolfgang Kainz, Andrea Marchetti and Angelica Lo Duca
ISPRS Int. J. Geo-Inf. 2021, 10(7), 428; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070428
Received: 22 May 2021 / Revised: 19 June 2021 / Accepted: 21 June 2021 / Published: 23 June 2021
(This article belongs to the Special Issue Geo Data Science for Tourism)
Sports tourism is an emerging tourism product. In the sports and tourism industry, resource mining is the foundation that provides positive significance for theoretical support. This study takes China’s sports tourism boutique projects as the study object, exploring its spatial distribution pattern through the average nearest neighbor index, kernel density, and spatial autocorrelation. On the strength of the wuli–shili–renli system approach, the entropy value method and geographic detector probe model are used to identify the driving factors affecting the spatial distribution pattern. Findings reveal the following: (1) From 2013 to 2014, the sports tourism resources in China present a distribution pattern with the Yangtze River Delta urban agglomeration as the high-density core area and the Guizhou–Guangxi border area and the western Hubei ecological circle as the sub-density core areas. (2) From 2014 to 2018, China’s sports tourism boutique projects increased by 381, and the regional differences among various provinces tended to converge. The high-density core area remained unchanged. The sub-density cores are now the Yunqian border area of the Karst Plateau, the Qinglong border area of the Qilian Mountains, and the Jinji border area of the Taihang Mountains, shaping the distribution trends of “depending on the city, near the scenery” and “large concentration, small dispersion”. (3) The proportion of provincial sports tourism development classified as being in the coordinated stage is 61.29%. (4) The explanatory power of the factors affecting the spatial layout in descending order is natural resource endowment, sports resource endowment, transportation capacity, industrial support and guidance, market cultivation and development, people’s living standards, software and hardware services, and economic benefit effects. The explanatory power of the interaction of two different factors is higher than that of the single factor. View Full-Text
Keywords: sports tourism; spatial distribution; geographic detector; influencing factors; China sports tourism; spatial distribution; geographic detector; influencing factors; China
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MDPI and ACS Style

Zuo, Y.; Chen, H.; Pan, J.; Si, Y.; Law, R.; Zhang, M. Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China. ISPRS Int. J. Geo-Inf. 2021, 10, 428. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070428

AMA Style

Zuo Y, Chen H, Pan J, Si Y, Law R, Zhang M. Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China. ISPRS International Journal of Geo-Information. 2021; 10(7):428. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070428

Chicago/Turabian Style

Zuo, Yifan, Huan Chen, Jincheng Pan, Yuqi Si, Rob Law, and Mu Zhang. 2021. "Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China" ISPRS International Journal of Geo-Information 10, no. 7: 428. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10070428

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