Spatial-temporal Pattern and Influencing Factors of Listed Enterprises in China’s Strategic Emerging Industries
DOI:
https://doi.org/10.24002/ijieem.v7i2.10561Keywords:
ellipse standard deviation, emerging industries , gravity center, industrial diversity index, kernel density modelAbstract
This study analyzes the structure and spatial distribution of listed companies in China's strategic emerging industries
(SEIs) from 2010 to 2021, using a quantitative approach. An industrial diversity index is created to assess provincial
structures, and spatial agglomeration is examined through a spatial autocorrelation model. The distribution is visualized
with kernel density estimation (KDE), and migration patterns of the gravity center are tracked. The key findings are as
follows: (1) Significant regional disparities in SEI development exist, with greater diversity in the Yangtze River Delta
(YRD), Beijing-Tianjin-Hebei (BTH), and the Pearl River Delta (PRD) compared to other regions; (2) The distribution
shows strong positive spatial autocorrelation, indicating a pronounced agglomeration effect; (3) The spatial center of
gravity primarily shifts within Central China; (4) The distribution follows a pattern of decreasing concentration from the
eastern coastal areas to the western inland regions, with scattered presence in the central and northeastern regions; (5)
Key factors such as economic development (DN values), policy support, R&D investments, passenger turnover, and
technology market activity play a significant role in shaping the number of listed companies in each region. This analysis
offers valuable insights for policymakers aiming to guide regional industrial development.
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