Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China
Abstract Marathon events play a crucial role in promoting the synergistic development of sports and tourism economies, significantly influencing the construction of a new “sports + events + tourism” development model and serving as a key driver of regional economic growth. This study analyzed POI da...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-11339-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849343874861891584 |
|---|---|
| author | Xinlong Zhao Yan Wang Junjin Chen |
| author_facet | Xinlong Zhao Yan Wang Junjin Chen |
| author_sort | Xinlong Zhao |
| collection | DOAJ |
| description | Abstract Marathon events play a crucial role in promoting the synergistic development of sports and tourism economies, significantly influencing the construction of a new “sports + events + tourism” development model and serving as a key driver of regional economic growth. This study analyzed POI data from marathon events in Shandong Province, China, from 2018 to 2024, using spatial analysis tools such as the nearest neighbor index, standard deviational ellipse, and kernel density estimation in geographic information systems to explore the spatiotemporal distribution patterns of marathon events. Additionally, the geographic detector method was employed to identify key factors influencing marathon event development. The results indicate: (1) Regionally, marathon events exhibit significant distribution disparities, with a dispersed spatial layout and a diffusion trend along the northeast-southwest axis, gradually shifting toward inland western areas. This forms a hierarchical spatial structure characterized by a multi-core cluster-based layout. (2) Marathon events are strongly influenced by five key factors: number of universities, GDP per capita, proportion of tertiary industry, policy intensity, and tourism revenue. Among these, policy intensity, number of universities, and proportion of tertiary industry are identified as dynamic factors, showing increasing influence over time. Road mileage, elevation, and river systems represent static factors, maintaining relatively stable effects. Meanwhile, population density, sports-related intangible cultural heritage, tourism revenue, and average temperature are potential factors, exhibiting fluctuating but growing impact trends. (3) Dual-factor interaction analysis reveals three types of interactions: independent, dual-factor enhancement, and nonlinear enhancement. Tourism revenue and road mileage exhibit no interaction. The core interaction factors are sports-related intangible cultural heritage and the number of universities, with the secondary core interaction being sports-related intangible cultural heritage and tourism revenue. |
| format | Article |
| id | doaj-art-486c68c0ea4541d7a25ee2b02a8ba7d3 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-486c68c0ea4541d7a25ee2b02a8ba7d32025-08-20T03:42:49ZengNature PortfolioScientific Reports2045-23222025-07-0115111410.1038/s41598-025-11339-6Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, ChinaXinlong Zhao0Yan Wang1Junjin Chen2College of Physical Education, Ludong UniversityCollege of Physical Education, Ludong UniversityCollege of Physical Education, Ludong UniversityAbstract Marathon events play a crucial role in promoting the synergistic development of sports and tourism economies, significantly influencing the construction of a new “sports + events + tourism” development model and serving as a key driver of regional economic growth. This study analyzed POI data from marathon events in Shandong Province, China, from 2018 to 2024, using spatial analysis tools such as the nearest neighbor index, standard deviational ellipse, and kernel density estimation in geographic information systems to explore the spatiotemporal distribution patterns of marathon events. Additionally, the geographic detector method was employed to identify key factors influencing marathon event development. The results indicate: (1) Regionally, marathon events exhibit significant distribution disparities, with a dispersed spatial layout and a diffusion trend along the northeast-southwest axis, gradually shifting toward inland western areas. This forms a hierarchical spatial structure characterized by a multi-core cluster-based layout. (2) Marathon events are strongly influenced by five key factors: number of universities, GDP per capita, proportion of tertiary industry, policy intensity, and tourism revenue. Among these, policy intensity, number of universities, and proportion of tertiary industry are identified as dynamic factors, showing increasing influence over time. Road mileage, elevation, and river systems represent static factors, maintaining relatively stable effects. Meanwhile, population density, sports-related intangible cultural heritage, tourism revenue, and average temperature are potential factors, exhibiting fluctuating but growing impact trends. (3) Dual-factor interaction analysis reveals three types of interactions: independent, dual-factor enhancement, and nonlinear enhancement. Tourism revenue and road mileage exhibit no interaction. The core interaction factors are sports-related intangible cultural heritage and the number of universities, with the secondary core interaction being sports-related intangible cultural heritage and tourism revenue.https://doi.org/10.1038/s41598-025-11339-6 |
| spellingShingle | Xinlong Zhao Yan Wang Junjin Chen Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China Scientific Reports |
| title | Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China |
| title_full | Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China |
| title_fullStr | Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China |
| title_full_unstemmed | Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China |
| title_short | Spatiotemporal distribution patterns and influencing factors of marathon events: A case study of Shandong province, China |
| title_sort | spatiotemporal distribution patterns and influencing factors of marathon events a case study of shandong province china |
| url | https://doi.org/10.1038/s41598-025-11339-6 |
| work_keys_str_mv | AT xinlongzhao spatiotemporaldistributionpatternsandinfluencingfactorsofmarathoneventsacasestudyofshandongprovincechina AT yanwang spatiotemporaldistributionpatternsandinfluencingfactorsofmarathoneventsacasestudyofshandongprovincechina AT junjinchen spatiotemporaldistributionpatternsandinfluencingfactorsofmarathoneventsacasestudyofshandongprovincechina |