SPATIAL CORRELATION CHARACTERISTICS AND FUNCTIONING MECHANISM OF INTER-PROVINCIAL INDUSTRIAL STRUCTURE

doi:10.13776/j.cnki.resourcesindustries.20241008.003

Abstract

Abstract: Industries are key to economy, fundamentally for a nation's basis. Advancing industrial structures is a vital approach to modernized industrial system, industrial core competitiveness and entering middle-upper end of global value chains. This paper uses industrial commonality index to measure China's 31 provinces' 2012 to 2021 similarity matrix of industrial structures, and applies social network analysis (SNA) and secondary assignment procedure (QAP) to study the spatial correlation characteristics and functioning mechanism. Industrial commonality index can effectively show the asymmetry between inter-provincial industrial structural similarity and regional relation. Spatial correlation network of inter-provincial industrial structures can be divided into 4 domains, the first domain includes Beijing, Tianjin, Jiangsu, Guangdong, Zhejiang, Shanghai and Chongqing, at the top of industrial structural network which plays a leading role in optimizing industrial structures. The second domain includes Shanxi, Liaoning, Fujian and Shandong, playing a bridging and mediating role amid industrial migration, interactive with the first domain and outflowing to the third domain. The third domain includes Inner Mongolia, Hebei, Jiangxi, Sichuan, Henan, Hubei, Hunan, Anhui, Guangxi, Shaanxi and Jilin, both receiving the second domain's outflowing and outflowing to the forth domain. The forth domain includes the rest, which needs to receive industries from more developed areas in industrial structural adjustment. QAP suggests that labor inputs, human capital, capital types, and end consumption and geographic neighboring may be partially interpretated as spatially correlated, and path to inter-provincial industrial migration and receiving may be optimized.

Key words: industrial commonality, industrial structures, spatial correlation, network analysis, industrial migration and receiving

摘要： 产业是经济发展的关键所在，是一个国家的立国之本。推动产业结构调整是建设现代化产业体系、增强产业核心竞争力、促进产业迈向全球价值链中高端的重要举措。本文通过构建产业共同度指标测度了2012—2021年31个省份产业结构的相似性矩阵，并运用社会网络分析（SNA）和二次指派程序（QAP），解析省际产业结构空间关联网络特征及其作用机制。研究发现：1）产业共同度指标能有效展现省际产业结构相似性及区域间关系的不对称性。2）省际产业结构空间关联网络可以分为4个板块，其中第一板块包括北京、天津、江苏、广东、浙江、上海、重庆7个省份块，处于产业结构网络关系的顶端，是产业结构优化升级的“领头羊”角色；第二板块包括山西、辽宁、福建、山东4个省份，在产业转移和承接中发挥“中介”和“桥梁”的作用，既与第一板块双向互动，又能向第三板块溢出；第三板块包括内蒙古、河北、江西、四川、河南、湖北、湖南、安徽、广西、陕西、吉林11个省份，既接收第二板块的溢出，又向第四板块溢出；其余9省属于第四板块，产业结构调整需要承接比自身发达区域的产业。3）QAP分析得出，各省份劳动力投入、人力资本、资本类型、最终消费构成的关系以及地理邻接关系可以部分解释产业结构的空间关联；中国省际的产业转移和承接存在一些优化的路径。

关键词: 产业共同度, 产业结构, 空间关联, 网络分析, 产业转移承接

CLC Number:

F205

CHEN Chen. SPATIAL CORRELATION CHARACTERISTICS AND FUNCTIONING MECHANISM OF INTER-PROVINCIAL INDUSTRIAL STRUCTURE[J]. Resources & Industries, 2024, 26(5): 90-100.

陈晨. 省际产业结构空间关联特征及作用机制研究[J]. 资源与产业, 2024, 26(5): 90-100.

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