Spatial Distribution and Location Determinants of High-Tech Firms in Shenzhen, a Chinese National Innovative City
Abstract
:1. Introduction
2. Literature Review
2.1. Intra-Urban Location Patterns of High-Tech Firms
2.2. Location Determinants for High-Tech Firms
2.3. Research Gap
3. Data and Methodology
3.1. Study Area
3.2. Data and Variables
3.3. Methodology
3.3.1. Spatial Distribution Analysis Methods
- Kernel density estimation
- 2.
- Getis–Ord Gi* Statistic
- 3.
- Bivariable spatial autocorrelation
3.3.2. GeoDetector Model
4. Empirical Results
4.1. Spatial Distribution of High-Tech Firms in Shenzhen
4.2. Regression Analysis of Location Determinants for High-Tech Firms
4.2.1. Single-Factor Detection
4.2.2. Factor Interaction Detection
5. Discussion
5.1. Government Planning and the Distribution of High-Tech Firms
5.2. Production Factors Demand Preferences and Industrial Heterogeneity
5.3. The Important Role of Amenities in High-Tech Firms’ Location
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Category | Factors | Definitions | Unit |
---|---|---|---|
Classic locational factors (A) | Land rent (A1) | the standardized price of residential land | 10 thousand CNY/m2 |
Human capital (A2) | percentage of population with junior college education and above | % | |
Inter-city transportation accessibility (A3) | number of highway entrances and exits | number | |
Agglomeration economies factors (B) | The stock of manufacturers (B1) | number of existing manufacturers in a sub-district | number |
The stock of tech-based firms (B2) | number of existing tech-based firms in a sub-district | number | |
Universities and science development institutions (B3) | number of universities and science development institutions | number | |
Institutional factors (C) | Industrial parks (C1) | accumulative level of industrial parks | number |
Amenity-based factors (D) | Transportation amenities (D1) | number of subway stations | number |
Private consumer services (D2) | density of private consumer services facilities | number/km2 | |
Public services (D3) | density of public services facilities | number/km2 | |
Environment settings (D4) | density of city parks and squares | number/km2 |
Factors | All High-Tech Firms | High-Tech Manufacturing Firms | High-Tech Service Firms |
---|---|---|---|
Classic locational factors (A) | A1 | 0.050 | 0.225 ** |
A2 | 0.103 | 0.293 ** | |
A3 | 0.191 | 0.405 ** | |
Agglomeration economies factors (B) | B1 | 0.231 ** | 0.242 ** |
B2 | 0.572 ** | 0.297 ** | |
B3 | 0.241 | 0.034 | |
Institutional factors (C) | C1 | 0.178 ** | 0.112 ** |
Amenity-based factors (D) | D1 | 0.162 * | 0.083 |
D2 | 0.186 ** | 0.237 ** | |
D3 | 0.035 | 0.155 ** | |
D4 | 0.138 ** | 0.249 ** |
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Cui, L.; Shen, J.; Mai, Z.; Lin, C.; Wang, S. Spatial Distribution and Location Determinants of High-Tech Firms in Shenzhen, a Chinese National Innovative City. Land 2024, 13, 1355. https://doi.org/10.3390/land13091355
Cui L, Shen J, Mai Z, Lin C, Wang S. Spatial Distribution and Location Determinants of High-Tech Firms in Shenzhen, a Chinese National Innovative City. Land. 2024; 13(9):1355. https://doi.org/10.3390/land13091355
Chicago/Turabian StyleCui, Lu, Jing Shen, Zhuolin Mai, Chenghui Lin, and Shaogu Wang. 2024. "Spatial Distribution and Location Determinants of High-Tech Firms in Shenzhen, a Chinese National Innovative City" Land 13, no. 9: 1355. https://doi.org/10.3390/land13091355