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<p>Existing studies on China’s high-quality development (HQD) predominantly focus on evaluations of typical river basin economic zones and key urban agglomerations, lacking systematic analysis of multi-dimensional synergies, long-term spatiotemporal evolution, and heterogeneous driving mechanisms at the provincial scale. This study utilizes panel data from 31 provinces spanning 2011–2021 to construct an ICGOS-SBM coupling model integrating innovation, coordination, green development, openness, and sharing dimensions. Through spatial autocorrelation analysis, standard deviational ellipse, random forest classification, and co-occurrence network analysis, we elucidate the spatiotemporal heterogeneity and underlying drivers of HQD. Key findings reveal: (1) Provincial HQD exhibited a “V-shaped” recovery trajectory (2015 as the inflection point), forming a gradient pattern of eastern region (1.125) ≈ western region (1.124) &gt; central region (0.957), with provinces of population &lt; 40 million showing the highest mean HQD (1.157) yet significant internal disparities; (2) Spatial agglomeration intensified by 28.0% (Moran’s I), with high-high clusters shifting westward and low-low clusters expanding centrally, while the standard deviational ellipse shifted southeastward; (3) Regional driving mechanisms diverged markedly: the east forms an “ecology-innovation dual-core + openness nexus” network; the central region suffers “dual pressure between social welfare and environmental constraints”; the west transitions from ecology-dominated to openness-driven dynamics (contribution increased by 9.0%) but faces ecological risks. This study pioneers the deep integration of multi-dimensional efficiency evaluation and spatiotemporal dynamic analysis, unveiling region-specific developmental logics across China’s eastern, central, and western regions, and provides spatially targeted policy foundations for addressing developmental imbalances.</p>

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Analysis of spatiotemporal evolution characteristics and driving mechanisms of provincial high-quality development in China’s eastern, central, and western regions

  • 期刊论文

  • 发表日期：

    2026年3月15日

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  • Shijia Xu,
  • Wei Zhang,
  • Lili Zhang,
  • Yidong Wang,
  • Qiang Li,
  • Shufang Wang,
  • Bin Wang,
  • Xinyue Liu

摘要

Existing studies on China’s high-quality development (HQD) predominantly focus on evaluations of typical river basin economic zones and key urban agglomerations, lacking systematic analysis of multi-dimensional synergies, long-term spatiotemporal evolution, and heterogeneous driving mechanisms at the provincial scale. This study utilizes panel data from 31 provinces spanning 2011–2021 to construct an ICGOS-SBM coupling model integrating innovation, coordination, green development, openness, and sharing dimensions. Through spatial autocorrelation analysis, standard deviational ellipse, random forest classification, and co-occurrence network analysis, we elucidate the spatiotemporal heterogeneity and underlying drivers of HQD. Key findings reveal: (1) Provincial HQD exhibited a “V-shaped” recovery trajectory (2015 as the inflection point), forming a gradient pattern of eastern region (1.125) ≈ western region (1.124) > central region (0.957), with provinces of population < 40 million showing the highest mean HQD (1.157) yet significant internal disparities; (2) Spatial agglomeration intensified by 28.0% (Moran’s I), with high-high clusters shifting westward and low-low clusters expanding centrally, while the standard deviational ellipse shifted southeastward; (3) Regional driving mechanisms diverged markedly: the east forms an “ecology-innovation dual-core + openness nexus” network; the central region suffers “dual pressure between social welfare and environmental constraints”; the west transitions from ecology-dominated to openness-driven dynamics (contribution increased by 9.0%) but faces ecological risks. This study pioneers the deep integration of multi-dimensional efficiency evaluation and spatiotemporal dynamic analysis, unveiling region-specific developmental logics across China’s eastern, central, and western regions, and provides spatially targeted policy foundations for addressing developmental imbalances.