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2025 , Vol. 48 >Issue 6: 1103 - 1114

DOI: https://doi.org/10.12118/j.issn.1000-6060.2024.512

区域发展

基于多维评价方法的沿黄地区经济韧性时空分异规律

  • 薛晨浩 ,
  • 白永平 ,
  • 王生鹏
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  • 1.西北师范大学地理与环境科学学院，甘肃 兰州 730070
    2.西北民族大学管理学院，甘肃 兰州 730030
薛晨浩（1988-），男，博士研究生，讲师，主要从事区域经济韧性等方面的研究. E-mail: xuechenhaovip@126.com
白永平（1961-），男，博士，教授，博士生导师，主要从事区域发展与区域管理等方面的研究. E-mail: baiyp@nwnu.edu.cn

收稿日期: 2024-08-24

  修回日期: 2024-11-24

  网络出版日期: 2025-06-18

基金资助

国家社会科学基金项目(22BMZ068);国家自然科学基金项目(40771054);中央高校基本科研业务费项目(31920220165)

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Spatio-temporal differentiation of economic resilience in the Yellow River region based on multidimensional evaluation methods

  • XUE Chenhao ,
  • BAI Yongping ,
  • WANG Shengpeng
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  • 1. College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, Gansu, China
    2. College of Management, Northwest Minzu University, Lanzhou 730030, Gansu, China

Received date: 2024-08-24

  Revised date: 2024-11-24

  Online published: 2025-06-18

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摘要

对沿黄地区经济韧性进行科学测度是提升区域经济韧性、实现高质量发展的重要步骤。构建指标体系从抵抗力、恢复力、转型力3个维度测度了2003—2022年沿黄地区经济韧性水平，引入泰尔指数和莫兰指数对沿黄地区经济韧性差异和空间相关性进行分析。结果表明：（1） 在研究期内，沿黄地区经济运行总体稳定，显示出较强的经济韧性，但是与全国经济韧性水平相比仍有较大差距。子系统中恢复力维度得分最高，转型力最低。（2） 较高韧性区主要分布在山东半岛、中西部省会城市与矿产资源富集城市，较低韧性地区主要为青海、宁夏、甘肃、陕西、河南大部分地区、内蒙古西部、山东西部，地级尺度的经济韧性具有明显的中心外围结构。（3） 研究期内沿黄地区经济韧性水平的总体差异在多数年份呈缩小趋势，区域内差异贡献率均大于75%，区域内协同发展问题应引起重视。（4） 研究期内沿黄地区经济韧性的莫兰指数均为正值，总体上呈正相关，局部空间聚类分布以低-低集聚区和高-高集聚区为主，前者主要集中在青海、甘肃、宁夏，后者主要分布于山东。

关键词： 经济韧性; 时空分异; 指标体系; 沿黄地区

本文引用格式

薛晨浩 , 白永平 , 王生鹏 . 基于多维评价方法的沿黄地区经济韧性时空分异规律[J]. 干旱区地理, 2025 , 48(6) : 1103 -1114 . DOI: 10.12118/j.issn.1000-6060.2024.512

Abstract

Scientifically measuring economic resilience in the Yellow River region is essential for enhancing regional development quality and sustainability. This study constructed a comprehensive indicator system to evaluate economic resilience across the Yellow River region from 2003 to 2022, examining three critical dimensions: Resistance, resilience, and transformation. We employed the Theil index to quantify regional disparities and the Moran’s index to analyze spatial correlation patterns. Our analysis revealed four key findings: (1) Regional performance: The Yellow River region demonstrated stable economic operation with strong overall resilience during the study period, though a significant gap persists compared to national economic resilience levels. Among the dimensional subsystems, resilience scored highest while transformation scored lowest. (2) Spatial distribution: Economic resilience exhibits a clear center-periphery structure at the prefecture level. Higher resilience areas are concentrated in the Shandong Peninsula, provincial capitals in central and western China, and mineral-rich cities. Lower resilience characterizes Qinghai, Ningxia, most of Gansu, Shaanxi, Henan, western Inner Mongolia, and western Shandong. (3) Temporal trends: The overall difference in economic resilience across the Yellow River region showed a decreasing trend over most of the study year. Regional differences contributed more than 75% to overall inequality, highlighting the need for coordinated intra-regional strategies. (4) Spatial correlation: Positive Moran’s index values throughout the study period indicate significant autocorrelation in economic resilience. Local spatial clustering revealed predominant “low-low” agglomeration (concentrated in Qinghai, Gansu, and Ningxia) and “high-high” agglomeration (primarily in Shandong).

Key words： economic resilience; spatiotemporal differentiation; indicator system method; the Yellow River region

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