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中国工业智能化的时空跃迁及其驱动机制

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[目的]本文旨在厘清中国工业智能化的时空跃迁特征,探索其时空跃迁的驱动机制,为推动工业智能化区域协调发展提供参考依据.[方法]在测度2010-2021年中国30个省(市、区)工业智能化水平的基础上,利用探索性时空数据分析方法(ESTDA)、分位数回归与时空跃迁镶嵌模型探究工业智能化时空跃迁特征及其驱动机制.[结果]①2010-2021年中国工业智能化水平整体呈上升趋势,增速呈波动型增长趋势,并呈现出"东部占优,中西低平"空间不均衡格局.②时空跃迁分析显示,中国工业智能化具有较强的路径锁定和空间依赖特征,其中多数西部省(市、区)始终锁定在低水平"俱乐部";空间格局演化具有较强的整合性,其中正向协同跃迁为主要发展模式.③机制分析显示,各地区工业智能化时空跃迁的驱动模式各异,其中,多数东部沿海省(市、区)的跃迁动力主要来自"经济水平-对外开放-区域创新"驱动模式,多数中西部内陆省(市、区)的跃迁阻力主要来自"产业结构"制约模式.在空间上,工业智能化时空跃迁模式自东向西呈现出"同向发展→同向制约"梯式演变格局.[结论]中国工业智能化发展仍存在较大提升空间,亟需因地制宜填补地缘劣势,突破空间路径锁定,强化工业数智融合,形成工业发展合力.
Spatiotemporal transition of China's industrial intelligence and the driving mechanism
[Objective]The objective of this study was to clarify the characteristics of the spatiotemporal transition of industrial intelligence in China and its driving mechanism,and provided a reference basis for promoting the coordinated regional development of industrial intelligence.[Methods]On the basis of measuring the industrial intelligence level of 30 provinces in China from 2010 to 2021,this study investigated the spatiotemporal transition characteristics of industrial intelligence by using exploratory spatiotemporal data analysis(ESTDA).We then used quantile regression with spatiotemporal transition mosaic model to explore the driving mechanism of the spatiotemporal transition.[Results]The results show that:(1)From 2010 to 2021,China's industrial intelligence level as a whole showed an upward trend,and the growth rate exhibited a fluctuating growth trend.Spatially,the distribution exhibited an unbalanced pattern of"advanced in the east and weak in the central region and the west".(2)The results of spatiotemporal transition analysis indicated that China's industrial intelligence had powerful path-locking and spatial dependence characteristics.Most western provinces were always locked in the"club"of low intelligence attributes.The change of spatial pattern of industrial intelligence in China showed strong integration characteristics,in which positive synergistic transition was the main development mode.(3)Mechanism analysis revealed that the driving and restricting modes of spatiotemporal transition of industrial intelligence varied among different regions.The spatiotemporal transition in most eastern coastal provinces was mainly"economic level,opening up,and regional innovation"driven,while the resistance of spatiotemporal transition in most central and western provinces primarily arose from the restricting mode of"industrial structure".The spatiotemporal transition pattern of industrial intelligence from the east to the west presented a trapezoidal evolution pattern from"same direction development"to"same direction constraints".[Conclusion]China's industrial intelligence still has a large room for improvement.Therefore,in the future,there is an urgent need to address the geographical disadvantages according to local conditions,break through the spatial path of locking in.Meanwhile,it is also necessary to strengthen the integration of industrial digitalization and intelligence,and form industrial development synergies to promote the development of industrial intelligence.

industrial intelligencetemporal changespatiotemporal transitiondriving mecha-nismexploratory spatiotemporal data analysis(ESTDA)quantile regressionChina

李莉萍、邓宗兵、肖沁霖

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上海财经大学城市与区域科学学院,上海 200433

西南大学经济管理学院,重庆 400715

工业智能化 时序演化 时空跃迁 驱动机制 探索性时空数据分析方法(ESTDA) 分位数回归 中国

教育部人文社会科学研究规划基金项目重庆市社会科学规划项目西南大学中央高校基本科研业务费专项资金项目

19YJA7900052021NDYB058SWU2009221

2024

10.18402/resci.2024.05.07

资源科学
中国科学院地理科学与资源研究所 中国自然资源学会

资源科学

CSTPCDCSSCICHSSCD北大核心
影响因子：2.408
ISSN：1007-7588
年,卷(期)：2024.46(5)
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