1. 广东工业大学 管理学院,广东,广州,510520
2. 广东第二师范学院 数学学院,广东,广州,510303
吴小节(1980–),男,教授,博士,博士生导师,主要研究方向为企业管理,E-mail:xiaojie_wu@163.com
童乾(1972–),女,副教授,博士,主要研究方向为企业管理,E-mail:tongqian@gdei.edu.cn
网络首发:2022-11-10,
纸质出版:2022
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吴小节, 卢荣秀, 谭晓霞, 童乾. 全球七大产业发展水平的空间分异与动态演化——基于2000~2020年世界500强的实证分析[J]. 广东工业大学学报, 2022, 39(6): 10-25.
Wu Xiao-jie, Lu Rong-xiu, Tan Xiao-xia, et al. Spatial Divergence and Dynamic Evolution of the Development Levels of Seven Major Industries in Global —Empirical Analysis Based on the Fortune Global 500 from 2000 to 2020[J]. 2022, 39(6): 10-25.
吴小节, 卢荣秀, 谭晓霞, 童乾. 全球七大产业发展水平的空间分异与动态演化——基于2000~2020年世界500强的实证分析[J]. 广东工业大学学报, 2022, 39(6): 10-25. DOI: 10.12052/gdutxb.220112.
Wu Xiao-jie, Lu Rong-xiu, Tan Xiao-xia, et al. Spatial Divergence and Dynamic Evolution of the Development Levels of Seven Major Industries in Global —Empirical Analysis Based on the Fortune Global 500 from 2000 to 2020[J]. 2022, 39(6): 10-25. DOI: 10.12052/gdutxb.220112.
为测度北美、东亚和欧洲七大产业的发展现状、时空分异及发展趋势,采用Dagum基尼系数、Kernel密度估计、Markov链方法进行实证分析。研究发现三大区域内七大产业发展水平存在区域差异,不同区域内差异从高到低排序不一,总体差距的主要来源是区域间差异;此外,七大产业发展水平发生跨阶段转移的概率比较小,具有一定的邻接依赖性。基于时间和空间双重维度,评估了全球七大产业的发展现状,并预测区域的产业发展趋势,为关键产业的发展现状分析提供证据支持,为国家对关键产业的全球区域布局以及发展方向决策提供参考。
To measure the development status
spatial and temporal divergence and development trend of the seven industries in North America
East Asia and Europe
Dagum Gini coefficient
Kernel density estimation and Markov chain method were used for empirical analysis. It is found that there are regional differences in the development levels of the seven industries in the three major regions
and the differences within different regions are ranked from high to low
and the main source of the overall gap is inter-regional differences; in addition
the probability of inter-stage transfer of the development levels of the seven industries is relatively small
with a certain degree of neighbor dependence. Based on both temporal and spatial dimensions
the current development status of the seven global industries is assessed
and the regional industrial development trends are predicted to provide evidence to support the current development status of key industries
and to provide a reference for the national decision on the global regional layout of key industries as well as the development direction.
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