IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i16p7193-d1720641.html
   My bibliography  Save this article

The Spatiotemporal Pattern Evolution Characteristics and Affecting Factors for Collaborative Agglomeration of the Yellow River Basin’s Tourism and Cultural Industries

Author

Listed:
  • Yihan Chi

    (School of Management Administration, Xi’an University of Architecture and Technology, 13 Yanta Road, Xi’an 710055, China)

  • Yongheng Fang

    (School of Public Administration, Xi’an University of Architecture and Technology, 13 Yanta Road, Xi’an 710055, China)

Abstract

Seeking to advance mutual clustering of the tourism economy and cultural industries while safeguarding cultural sustainability in tourism, this paper delves into the patterns of co-development and the contributing forces across spatial and temporal dimensions in the Yellow River Basin. Using a combined spatial and temporal analytical lens, along with spatial autocorrelation testing and a spatial Durbin model embedded in a synergetic systems approach, the present study analyzes the evolutionary characteristics of the spatiotemporal pattern of the collaborative agglomeration of the Yellow River Basin’s tourism and cultural industries in 2011 and 2021 and the internal mechanism of its influencing factors. We then propose countermeasures and suggestions to boost the quality–efficiency synergy agglomeration of the basin’s tourism and cultural industries. The results showed the following: ① From 2011 to 2021, a positive overall spatial autocorrelation was noted in the basin’s tourism and cultural industries. Temporally, it presented a variation trend of “rise–fall–rise”, and spatially, it presented a distribution characteristic of “higher in the central and eastern regions versus in its western parts”. ② From 2011 to 2021, the local spatial autocorrelation (LSA) of the basin’s tourism and cultural industries remained at a low level. Moreover, significant differences were noted in the LSA among different regions. In spatial terms, the clustering intensity of tourism and cultural industries was stronger in the central and eastern parts of the basin versus in its western parts. ③ Influencing variables for tourism–culture collaborative agglomeration across the basin involve both temporal superposition effects and spatial radiation driving effects. The industrial economy, policies, and innovation exert enduring effects on the development and cross-regional spillover outcomes of the two collaborative agglomerations. Serving as a theoretical reference and policy resource, this study addresses how to promote the quality–efficiency synergy in the Yellow River Basin’s tourism and cultural industries while enhancing cultural sustainability in the tourism industry. Moreover, it can also provide experiences and references for other similar regions.

Suggested Citation

  • Yihan Chi & Yongheng Fang, 2025. "The Spatiotemporal Pattern Evolution Characteristics and Affecting Factors for Collaborative Agglomeration of the Yellow River Basin’s Tourism and Cultural Industries," Sustainability, MDPI, vol. 17(16), pages 1-26, August.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7193-:d:1720641
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/16/7193/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/16/7193/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shihong Zeng & Mimi Hu & Bin Su, 2016. "Research on Investment Efficiency and Policy Recommendations for the Culture Industry of China Based on a Three-Stage DEA," Sustainability, MDPI, vol. 8(4), pages 1-15, March.
    2. Mao, Jie & Tang, Shiping & Xiao, Zhiguo & Zhi, Qiang, 2021. "Industrial policy intensity, technological change, and productivity growth: Evidence from China," Research Policy, Elsevier, vol. 50(7).
    3. Yun Yang & Rong Wang & Junlan Tan & Jose Luis Calvo-Rolle, 2021. "Coupling Coordination and Prediction Research of Tourism Industry Development and Ecological Environment in China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-15, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haiwen Zhou, 2023. "State Capacity and Leadership: Why Did China Take off?," Chinese Economy, Taylor & Francis Journals, vol. 56(1), pages 50-68, January.
    2. Wei Hu & Jingsong Liu, 2023. "The Coupling and Coordination of Urban Modernization and Low-Carbon Development," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    3. Pengyu Ren & Zhaoxia Liu, 2021. "Efficiency Evaluation of China’s Public Sports Services: A Three-Stage DEA Model," IJERPH, MDPI, vol. 18(20), pages 1-12, October.
    4. Junguo Shi & Bert M. Sadowski & Xinru Zeng & Shanshan Dou & Jie Xiong & Qiuya Song & Sihan Li, 2023. "Picking winners in strategic emerging industries using government subsidies in China: the role of market power," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    5. Keren Chen, 2022. "Industrial Policy’s Effect on Cross-Border Mergers’ Decisions—Theoretical and Empirical Analysis," Sustainability, MDPI, vol. 14(20), pages 1-25, October.
    6. Alessio Terzi & Monika Sherwood & Aneil Singh, 2023. "European industrial policy for the green and digital revolution," Science and Public Policy, Oxford University Press, vol. 50(5), pages 842-857.
    7. Yihan Chi & Yongheng Fang & Jiamin Liu, 2022. "Spatial–Temporal Evolution Characteristics and Economic Effects of China’s Cultural and Tourism Industries’ Collaborative Agglomeration," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    8. Godinho, Manuel Mira & Simões, Vítor Corado, 2023. "The Tech Cold War: What can we learn from the most dynamic patent classes?," International Business Review, Elsevier, vol. 32(6).
    9. Fengge Yao & Ying Song & Xiaomei Wang, 2023. "How the Digital Economy Empowers the Structural Upgrading of Cultural Industries—An Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 15(19), pages 1-17, October.
    10. Shi An & Shaoliang Zhang & Huping Hou & Yiyan Zhang & Haonan Xu & Jie Liang, 2022. "Coupling Coordination Analysis of the Ecology and Economy in the Yellow River Basin under the Background of High-Quality Development," Land, MDPI, vol. 11(8), pages 1-19, August.
    11. Xushuai Li & Jiayu Zhang & Xiang Chen & Ching‐Cheng Lu, 2023. "Evaluation of innovation efficiency in China's cultural industry: A meta‐frontier with non‐radial directional distance function approach," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(5), pages 3709-3720, October.
    12. Wu, Yueh-Cheng & Lin, Sheng-Wei, 2022. "Efficiency evaluation of Asia's cultural tourism using a dynamic DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    13. Lee Branstetter & Guangwei Li, 2024. "The Challenges of Chinese Industrial Policy," Entrepreneurship and Innovation Policy and the Economy, University of Chicago Press, vol. 3(1), pages 77-113.
    14. Klemen Knez, 2023. "Technology diffusion and uneven development," Journal of Evolutionary Economics, Springer, vol. 33(4), pages 1171-1195, September.
    15. Ruohan Wang & Qingjin Wang & Renbo Shi & Kaiyun Zhang & Xueling Wang, 2023. "How the Digital Economy Enables Regional Sustainable Development Using Big Data Analytics," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
    16. Linqing Fang & Zhihao Liu & Caiyu Jin, 2023. "How Does the Integration of Cultural Tourism Industry Affect Rural Revitalization? The Mediating Effect of New Urbanization," Sustainability, MDPI, vol. 15(14), pages 1-22, July.
    17. Xing, Zeyu & Yalçin, Haydar & Daim, Tugrul, 2024. "Digital Economy's influence on R&D Network configurations: Integrating resource dependence theory and institutional theory," Technovation, Elsevier, vol. 137(C).
    18. Sun, Yutao & Jiang, Lin & Cao, Cong & Tseng, Fang-Mei, 2024. "From contributors to boundary spanners: Evolving roles of government agencies in China’s innovation policy network (1980–2019)," Technovation, Elsevier, vol. 132(C).
    19. Rodríguez-Huerta, Edgar & Rosas-Casals, Martí & Sorman, Alevgul H., 2017. "A societal metabolism approach to job creation and renewable energy transitions in Catalonia," Energy Policy, Elsevier, vol. 108(C), pages 551-564.
    20. Yuqing Geng & Hongwei Zhu & Renjun Zhu, 2022. "Coupling Coordination between Cultural Heritage Protection and Tourism Development: The Case of China," Sustainability, MDPI, vol. 14(22), pages 1-22, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7193-:d:1720641. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.