Redai dili (Dec 2022)
The Spatiotemporal Evolution and Influencing Factors of Electronic Information Manufacturing Industry in China
Abstract
After the global economic crisis of 2008, China's electronic information manufacturing industry faced the dual challenge of expanding the scale of agglomeration and improving growth quality. The spatiotemporal pattern of the development of the electronic information industry is constantly changing because of globalization, national policies, and local production networks. To understand the spatiotemporal changes and mechanisms of the Chinese electronic information manufacturing industry in the post-economic crisis period, this study uses electronic information manufacturing enterprises (EIMEs) at the city scale from 2009 to 2018 as the research object, and uses the Gini coefficient, spatial correlation analysis, and negative binomial regression model to analyze the evolution of the spatiotemporal pattern of the Chinese electronic information manufacturing industry and its influencing factors from 2009 to 2018. The main conclusions are: (1) The characteristics of the spatiotemporal evolution of the electronic information manufacturing industry are as follows. On a national scale, the Chinese electronic information manufacturing industry is developing rapidly, but its development is unstable due to the influence of the international situation. At the scale of the city cluster, the electronic information manufacturing industry mainly concentrates on the Pearl River Delta and Yangtze River Delta, and the middle reaches of the Yangtze River are ready for development. At the city level, the ranking of the top ten cities in China is stable. The cities in the central region and Sichuan-Chongqing regions are developing rapidly, while cities in northeast China are in a developmental dilemma. Spatial correlation analysis revealed a significant positive spatial correlation between the distribution of EIMEs in China. (2) The empirical analysis of location choice shows that there is heterogeneity among different city clusters owing to different factors. At the national level, EIMEs are more likely to be located in cities with high labor costs, a high degree of industrial collaborative agglomeration, strong local innovation ability, and low economic development. Enterprises in the Yangtze River Delta region prefer cities with high innovation abilities. In contrast, those in the Chengdu-Chongqing city cluster prefer cities with low innovation abilities. Labor costs have a positive effect in the Beijing-Tianjin-Hebei city cluster and the middle reaches of the Yangtze River. Industrial collaborative agglomeration has a positive impact on the Chengdu-Chongqing region. The level of industrial marketization has a positive effect on the Yangtze River Delta and the Chengdu-Chongqing city clusters. The economic development level negatively affects the middle reaches of the Yangtze River and the Chengdu-Chongqing city cluster. The level of transportation infrastructure has a positive effect on the Yangtze River Delta and Beijing-Tianjin-Hebei. The minor contributions of this study include two aspects: In terms of theoretical contribution, this study enriches the theoretical results of research on the electronic information industry in economic geography and provides a specific reference for research on other sectors. In a practical sense, this study is conducive to an in-depth understanding of the changes and development trends of China's electronic information manufacturing industry in the post-economic crisis period and provides a reference for local governments to formulate corresponding industrial development strategies and policies and promote the upgrading of China's industrial structure and the coordinated development of the regional economy.
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