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数字经济与城市生态韧性协同演化特征及驱动因素
摘要点击 256  全文点击 4  投稿时间:2025-04-04  修订日期:2025-07-08
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中文关键词  数字经济  城市生态韧性  协同演化  时空特征  动态演进  驱动因素
英文关键词  digital economy  urban ecological resilience  coordinated evolution  spatiotemporal characteristics  dynamic evolution  driving factors
DOI  10.13227/j.hjkx.202504057
作者单位E-mail
刘秀丽 山西财经大学资源型经济转型发展研究院, 太原 030006 lxl820113@163.com 
贾昕炽 山西财经大学资源型经济转型发展研究院, 太原 030006  
郭丕斌 山西经济管理干部学院管理系, 太原 030006  
申俊 山西财经大学资源型经济转型发展研究院, 太原 030006  
史琴琴 山西财经大学资源型经济转型发展研究院, 太原 030006  
中文摘要
      明晰数字经济与城市生态韧性的协同发展特征及演进趋势是实现我国高质量发展的重要要求. 基于2011~2022年中国275个地级市数据,利用耦合协同度模型测算数字经济与城市生态韧性的协同发展度,借助核密度估计、Markov链以及地理探测器模型探析二者协同发展的演化特征及驱动因素. 结果表明:①从时序特征看,数字经济与城市生态韧性的协同发展度稳中有升,考察期内提升14.97%. ②从空间分布看,二者协同发展逐渐呈现出“濒临失调区逐渐减少,勉强协调区集聚发展”的演化特征. ③从动态分布看,二者协同发展度呈稳步提升态势,但四大地区内部协同发展水平呈现不均衡特征;协同发展具有较强的等级稳定性,空间邻域效应显著. ④从驱动因素看,二者的协同发展受经济发展水平、产业结构、科技支出、人力资本和外商直接投资这5个因素的影响,且不同因素的影响程度存在显著差异.
英文摘要
      Clarifying the synergistic development characteristics and evolutionary trends of the digital economy and urban ecological resilience is essential for promoting high-quality development in China. Based on panel data from 275 prefecture-level cities from 2011 to 2022, this study measures the degree of synergistic development between the digital economy and urban ecological resilience using a coupling coordination model. It further explores their spatial-temporal evolution and influencing factors through kernel density estimation, Markov chains, and the geographical detector model. The results show that: ① In terms of temporal trends, the synergistic development level has steadily increased, with a 14.97% rise during the study period. ② In terms of spatial patterns, the synergistic development degree gradually evolved from a scattered pattern of “near disorder” to a more clustered distribution of “barely coordinated” zones. ③ In terms of dynamic distribution, the overall level continued to improve, but significant disparities existed within the four major regions; the synergy development degree exhibited strong grade stability and pronounced spatial neighborhood effects. ④ In terms of influencing factors, the synergy development degree was influenced by five key variables: economic development, industrial structure, science and technology expenditure, human capital, and foreign direct investment, with notable differences in their explanatory power.

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