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The Temporal and Spatial Evolution of Marathons in China from 2010 to 2018

Author

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  • Yifan Zuo

    (School of Management, Jinan University, Guangzhou 510632, China
    Shenzhen Tourism College, Jinan University, Shenzhen 518053, China
    These authors contribute equally to this article.)

  • Liye Zou

    (College of Psychology and Sociology, Shenzhen University, Shenzhen 518061, China
    These authors contribute equally to this article.)

  • Mu Zhang

    (Shenzhen Tourism College, Jinan University, Shenzhen 518053, China)

  • Lee Smith

    (Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, Cambridge CB1 1PT, UK)

  • Lin Yang

    (Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, AB T2S 3C3, Canada
    Departments of Oncology and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4Z6, Canada)

  • Paul D. Loprinzi

    (Department of Health, Exercise Science and Recreation Management, University of Mississippi, Oxford, MS 38655, USA)

  • Zhanbing Ren

    (Department of Physical Education, Shenzhen University, Shenzhen 518061, China)

Abstract

The purpose of this study is to explore the spatial distribution pattern and influencing factors of the Chinese marathon. Geographic Information System (GIS) related spatial analysis tools were used to calculate the following—averaged nearest neighbor index, nuclear density analysis and hot spot analysis among others. The spatial distribution evolution characteristics and the influencing factors of eighteen Chinese marathon events in 2010, 129 in 2015 and 342 in 2018 were analyzed. The results show that (a) in 2010 the nearest neighbor ratio was 1.164714, Moran’s I was −0.010165 (type: Random), in 2015 it was 0.502146, Moran’s I was 0.066267 (type: Clustered) and in 2018 it was 0.531149 and Moran’s I was 0.083485 (type: Clustered); (b) in 2010 there was a 333.6 km search radius; the core circle of the Yangtze River Delta was adopted. In 2015 and 2018, a search radius of 556 km was adopted, which was respectively obtained from the core circle of the Yangtze River Delta, the core circle of Beijing-Tianjin-Hebei and the core circle of East China; (c) according to the Z -value data, East China and North China in 2015 passed 95% confidence in five provinces and municipal hot spots, passed 90% confidence in three hot spots and passed 95% confidence in Chongqing Cold Point. In 2018, East China, North China, Central Region and eight other provinces and cities’ hot spots passed 95% confidence, four hot spots passed 90% confidence, the Tibet Autonomous Region cold spot passed 90% confidence. Conclusion: The overall distribution of marathon events is greater in the eastern region than the western region, greater in the southern region than the northern region and greater in coastal regions than the inland regions; the nuclear density distribution has spread from the Yangtze River Delta mononuclear circle in 2010 to the core circle of the entire East China region. Moreover, it spread to North China, Central China and South China; the distribution of hot spots spread from Shanghai, Jiangsu and Zhejiang to the entire North China and East China regions. During the past thirty-eight years of development of the Chinese marathon, it has been divided into three stages due to different political, economic and social environments.

Suggested Citation

  • Yifan Zuo & Liye Zou & Mu Zhang & Lee Smith & Lin Yang & Paul D. Loprinzi & Zhanbing Ren, 2019. "The Temporal and Spatial Evolution of Marathons in China from 2010 to 2018," IJERPH, MDPI, vol. 16(24), pages 1-17, December.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:24:p:5046-:d:296621
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    References listed on IDEAS

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    1. Tingzhen Chen & Philip L. Pearce, 2012. "Research Note: Seasonality Patterns in Asian Tourism," Tourism Economics, , vol. 18(5), pages 1105-1115, October.
    2. Marie-Hélène Vandersmissen & Anne-Marie Séguin & Marius Thériault & Christophe Claramunt, 2009. "Modeling propensity to move after job change using event history analysis and temporal GIS," Journal of Geographical Systems, Springer, vol. 11(1), pages 37-65, March.
    3. Kurt Brännäs & Jonas Nordström, 2006. "Tourist Accommodation Effects of Festivals," Tourism Economics, , vol. 12(2), pages 291-302, June.
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    Cited by:

    1. Zhanbing Ren & Yifan Zuo & Yudan Ma & Mu Zhang & Lee Smith & Lin Yang & Paul D. Loprinzi & Qian Yu & Liye Zou, 2020. "The Natural Environmental Factors Influencing the Spatial Distribution of Marathon Event: A Case Study from China," IJERPH, MDPI, vol. 17(7), pages 1-17, March.

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