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Spatial Patterns of Tourist Attractions in the Yangtze River Delta Region

Author

Listed:
  • Yuewei Wang

    (School of Business, Liaoning University, Shenyang 110036, China)

  • Xinyang Wu

    (School of Economics and Management, Northwest University, Xi’an 710127, China)

  • Zhizheng Liu

    (School of Business, Liaoning University, Shenyang 110036, China)

  • Hang Chen

    (School of Tourism Management, Shenyang Normal University, Shenyang 110034, China)

  • Yuyan Zhao

    (School of Management, Shenyang Jianzhu University, Shenyang 110168, China)

Abstract

Tourism is distinctly regional with respect to the regional distribution of tourism resources, tourist attractions and supply, and spatial continuity of tourist activities. Using point-of-interest data from 2166 tourist attractions in the Yangtze River Delta, this study analyzes the spatial distribution pattern of tourist attractions and their influencing factors by applying the methods of nearest proximity index, kernel density analysis, standard deviation ellipse, hotspot analysis, and spatial superposition analysis. The results show that the number of modern recreational tourist attractions accounts for the largest proportion. The spatial distribution pattern shows more attractions in the north than the south and more in the east than the west. The spatial density of tourist attractions in Shanghai is far greater than that in other regions, followed by Jiangsu and Zhejiang. The five types of tourist attractions show a significant aggregation state. Natural ecological tourist attractions are clustered near Nanjing and Huangshan; historical and cultural tourist attractions are formed in a T-shape by Shanghai, Hangzhou, and Nanjing; modern recreational tourist attractions are clustered in Shanghai and Hangzhou; and industrial integration tourist attractions are clustered in Shanghai, Nanjing, and Hangzhou. Physical geography, traffic, and social economy are the main factors affecting the spatial distribution of tourist attractions.

Suggested Citation

  • Yuewei Wang & Xinyang Wu & Zhizheng Liu & Hang Chen & Yuyan Zhao, 2022. "Spatial Patterns of Tourist Attractions in the Yangtze River Delta Region," Land, MDPI, vol. 11(9), pages 1-22, September.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1523-:d:911009
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    References listed on IDEAS

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    1. Leask, Anna, 2016. "Visitor attraction management: A critical review of research 2009–2014," Tourism Management, Elsevier, vol. 57(C), pages 334-361.
    2. Balaguer, Jacint & Pernías, José C., 2013. "Relationship between spatial agglomeration and hotel prices. Evidence from business and tourism consumers," Tourism Management, Elsevier, vol. 36(C), pages 391-400.
    3. Xinyang Wu & Chuying Chen, 2022. "Spatial Distribution and Accessibility of High Level Scenic Spots in Inner Mongolia," Sustainability, MDPI, vol. 14(12), pages 1-13, June.
    4. Byun, Jaemun & Jang, SooCheong (Shawn), 2015. "Effective promotions for membership subscriptions and renewals to tourist attractions: Discount vs. bonus," Tourism Management, Elsevier, vol. 50(C), pages 194-203.
    5. Seidl, Andrew, 2014. "Cultural ecosystem services and economic development: World Heritage and early efforts at tourism in Albania," Ecosystem Services, Elsevier, vol. 10(C), pages 164-171.
    6. Sophie Masson & Romain Petiot, 2009. "Can the High Speed Rail reinforce tourism attractiveness? The case of the High Speed Railway section between Perpignan (France) and Barcelona (Spain)," Post-Print hal-02422659, HAL.
    7. Poria, Yaniv & Reichel, Arie & Cohen, Raviv, 2013. "Tourists perceptions of World Heritage Site and its designation," Tourism Management, Elsevier, vol. 35(C), pages 272-274.
    8. Yuewei Wang & Hang Chen & Xinyang Wu, 2021. "Spatial Structure Characteristics of Tourist Attraction Cooperation Networks in the Yangtze River Delta Based on Tourism Flow," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    9. Canale, Rosaria Rita & De Simone, Elina & Di Maio, Amedeo & Parenti, Benedetta, 2019. "UNESCO World Heritage sites and tourism attractiveness: The case of Italian provinces," Land Use Policy, Elsevier, vol. 85(C), pages 114-120.
    10. repec:hal:journl:hal-03062650 is not listed on IDEAS
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    3. Shengrui Zhang & Lei Chi & Tongyan Zhang & Yingjie Wang, 2022. "Spatial Pattern and Influencing Factors of Tourism Resources in Northwestern Ethnic Areas in China—A Case Study of Longde County," IJERPH, MDPI, vol. 19(24), pages 1-20, December.
    4. Junjie Li & Xiaodong Liu & Zhiyu Feng & Jinjin Liu & Yibo Wang & Mengjie Zhang & Xiangbin Peng, 2025. "Ecological Resilience and Sustainable Development: Dynamic Assessment and Evolution Mechanisms of Landscape Patterns and Ecotourism Suitability in the Yangtze River Delta Region," Sustainability, MDPI, vol. 17(17), pages 1-24, August.
    5. Lin Zhou & Yingyuqing Yin & Xue Liu & Xianjing Xiao & Peiling He, 2025. "Spatiotemporal Evolution and Influencing Factors of A-Level Garden-Type Scenic Areas in Jiangsu Province, China," Land, MDPI, vol. 14(9), pages 1-24, September.

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