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Analysis on the Temporal and Spatial Heterogeneity of Factors Affecting Urbanization Development Based on the GTWR Model: Evidence from the Yangtze River Economic Belt

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  • Wenbo Ma
  • Weiteng Tian
  • Qian Zhou
  • Qianqian Miao
  • Wei Zhang

Abstract

Revealing the key influencing factors in urbanization is of great significance to the operability of national urbanization planning and decision-making. Taking 110 cities in the Yangtze River Economic Belt (YREB) as the sample, this paper explores the driving mechanism of urbanization development during 2007–2016 by using Geographically and Temporally Weighted Regression Model (GTWR). The results show that the effects of the four dominant factors of social economy, education, secondary industry, and living environment are in line with expectations, with strong time fluctuation, obvious spatial nonstationarity, and a certain spatial gradient distribution. The formulation and implementation of the urbanization strategy should be based on the driving mechanism shown by the four models, coordinate the use of relevant policies, and give priority to ensuring the effective play of the primary driving factors.

Suggested Citation

  • Wenbo Ma & Weiteng Tian & Qian Zhou & Qianqian Miao & Wei Zhang, 2021. "Analysis on the Temporal and Spatial Heterogeneity of Factors Affecting Urbanization Development Based on the GTWR Model: Evidence from the Yangtze River Economic Belt," Complexity, Hindawi, vol. 2021, pages 1-11, October.
    • Handle: RePEc:hin:complx:7557346
    DOI: 10.1155/2021/7557346
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    Cited by:

    1. Yazhu Wang & Hui Zou & Xuejun Duan & Lingqing Wang, 2022. "Coordinated Evolution and Influencing Factors of Population and Economy in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(21), pages 1-19, November.
    2. Guangliang Zhou & Di Zhang & Qian Zhou & Tao Shi, 2022. "Study on the Spatiotemporal Evolution Characteristics of the “Production–Living–Ecology” Space in the Yellow River Basin and Its Driving Factors," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    3. Yaliu Yang & Yuan Wang & Yingyan Zhang & Conghu Liu, 2022. "Data-Driven Coupling Coordination Development of Regional Innovation EROB Composite System: An Integrated Model Perspective," Mathematics, MDPI, vol. 10(13), pages 1-25, June.
    4. Yiwen Liu & Jian Li & Yi Xu, 2022. "Quantitative Evaluation of High-Tech Industry Policies Based on the PMC-Index Model: A Case Study of China’s Beijing-Tianjin-Hebei Region," Sustainability, MDPI, vol. 14(15), pages 1-17, July.

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