The spatial pattern of R&D personnel concentration in China National High-tech Industrial Development Zone and its influencing factors

doi:10.3969/j.issn.1004-9479.2023.01.2021005

Abstract

Abstract:

Attracting R&D personnel is a crucial measure to upgrade National High-Tech Industrial Development Zones (NHDZs). This paper uses location entropy to analyze the spatial patterns of the concentration of R&D personnel in NHDZs, and then applies Geodetector to detect its influencing factors. The results show that: (1) Those NHDZs with plenty of R&D personnel are mainly distributed in urban agglomerations. The distribution of R&D personnel concentration in national high-tech zone is relatively balanced. (2) The explanatory power of high-tech zone factor is overall stronger than that of city. But in different regions, the explanatory power gap of the two kinds of factors is different. In eastern and central regions, the concentration of R&D personnel of NHDZs is affected by both two kinds of factors, while in western regions, high-tech zone factors is more significant. (3) The economic scale of high-tech zones and the R&D personnel capacity of high-tech zones are the core factors for the concentration of R&D personnel in high-tech zones in all regions. In addition, the cost of urban housing, the attention of research in city and high-tech zone foreign trade level are the core factors that dominate the concentration of R&D personnel in high-tech zones in eastern, central and western countries respectively. (4) The interaction between two factors presents the relationship of nonlinear enhancement and two-factor enhancement. In addition, there are regional differences in enhancement relationship. The advanced level of high-tech zones, the economic scale of high-tech zones, and urban transportation are the more significant factors that interact with other factors in the eastern, central, and western regions respectively. In the end, this article provides some policy suggestions for the human capital construction of the NHDZs.

Key words: National High-Tech Zones, human capital concentration, Geodetector, R&D personnel, talent

摘要：

吸引研发人员是推动国家高新区创新发展的关键举措之一。本文采用区位熵和地理探测器等方法，刻画国家高新区研发人员集聚的空间特征，探究其影响因子及作用机理。研究发现：（1）国家高新区研发人员数量呈现出以城市群为核心的空间分布格局，而研发人员集聚程度的空间分布较均衡。（2）整体上，高新区因子的解释力比城市因子更强，这说明以往只关注城市因子的研究存在不足。但在不同地区，两个层面因子解释力有所差异。东、中部地区，国家高新区研发人员集聚由城市因子和高新区因子共同作用，而高新区因子在西部地区影响更为显著。（3）高新区经济规模和高新区容纳人才能力是所有国家高新区研发人员集聚的核心因子。此外，城市住房成本、城市科研重视度和高新区外贸水平分别是主导东、中、西部国家高新区研发人员集聚的核心因子。（4）不同因子之间交互作用均呈现出增强关系，且具有区域差异性，具体表现为：高新区先进程度、高新区经济规模、城市交通便捷度分别是东、中、西部地区与其他因子的交互强化作用较为显著的因子。

关键词: 国家高新区, 人力资本集聚, 地理探测器, 研发人员, 人才

Pengxin CHEN, Gang ZENG, Hao HU, Jinliao HE, Shishuai GE. The spatial pattern of R&D personnel concentration in China National High-tech Industrial Development Zone and its influencing factors[J]. World Regional Studies, 2023, 32(1): 80-91.

陈鹏鑫, 曾刚, 胡浩, 何金廖, 葛世帅. 国家高新区研发人员集聚的空间特征与影响因子探究[J]. 世界地理研究, 2023, 32(1): 80-91.

Figures/Tables 7

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表达式	作用结果
q(X₁∩X₂) < min{q(X₁), q(X₂)}	非线性减弱
min{q(X₁), q(X₂)} < q(X₁∩X₂) < max{q(X₁), q(X₂)}	单因子非线性减弱
q(X₁∩X₂) =q(X₁) + q(X₂)	两因子相互独立
q(X₁∩X₂) > max{q(X₁), q(X₂)}	双因子增强
q(X₁∩X₂) > q(X₁) + q(X₂)	非线性增强

表达式	作用结果
q(X₁∩X₂) < min{q(X₁), q(X₂)}	非线性减弱
min{q(X₁), q(X₂)} < q(X₁∩X₂) < max{q(X₁), q(X₂)}	单因子非线性减弱
q(X₁∩X₂) =q(X₁) + q(X₂)	两因子相互独立
q(X₁∩X₂) > max{q(X₁), q(X₂)}	双因子增强
q(X₁∩X₂) > q(X₁) + q(X₂)	非线性增强

序号	探测因子	具体指标	分级
H₁	高新区成熟度	批准时间长短	5
H₂	高新区经济规模	园区企业工业总产值	5
H₃	高新区盈利水平	园区企业净利润	5
H₄	高新区外贸规模	园区企业出口总额	5
H₅	高新区科研重视度	园区研发人员人均科技活动经费支出	5
H₆	高新区等级	是否属于国家级自主创新示范区	2
H₇	高新区容纳人才能力	高新技术企业数	5
H₈	高新区先进程度	高新技术企业数与园区企业总数之比	5
C₉	城市经济发展水平	市辖区人均GDP	5
C₁₀	城市产业支撑能力	市辖区第三产业占比	5
C₁₁	城市生活环境	建成区绿化覆盖率	5
C₁₂	城市交通便捷性	人均道路面积	5
C₁₃	城市住房成本	职工平均工资/房价	5
C₁₄	城市科研重视度	市辖区人均科学技术支出	5
C₁₅	城市创新能力	每万人专利授权量	5

序号	探测因子	具体指标	分级
H₁	高新区成熟度	批准时间长短	5
H₂	高新区经济规模	园区企业工业总产值	5
H₃	高新区盈利水平	园区企业净利润	5
H₄	高新区外贸规模	园区企业出口总额	5
H₅	高新区科研重视度	园区研发人员人均科技活动经费支出	5
H₆	高新区等级	是否属于国家级自主创新示范区	2
H₇	高新区容纳人才能力	高新技术企业数	5
H₈	高新区先进程度	高新技术企业数与园区企业总数之比	5
C₉	城市经济发展水平	市辖区人均GDP	5
C₁₀	城市产业支撑能力	市辖区第三产业占比	5
C₁₁	城市生活环境	建成区绿化覆盖率	5
C₁₂	城市交通便捷性	人均道路面积	5
C₁₃	城市住房成本	职工平均工资/房价	5
C₁₄	城市科研重视度	市辖区人均科学技术支出	5
C₁₅	城市创新能力	每万人专利授权量	5

探测指标	q值
探测指标	全国	东部	中部	西部
H₁	0.239	0.386	0.143	0.255
H₂	0.350	0.405	0.354	0.720
H₃	0.308	0.427	0.343	0.643
H₄	0.350	0.360	0.428	0.755
H₅	0.237	0.097	0.299	0.288
H₆	0.281	0.277	0.212	0.577
H₇	0.329	0.445	0.374	0.648
H₈	0.223	0.321	0.238	0.134
C₉	0.131	0.182	0.167	0.297
C₁₀	0.057	0.220	0.058	0.324
C₁₁	0.038	0.091	0.164	0.207
C₁₂	0.042	0.173	0.138	0.127
C₁₃	0.247	0.433	0.156	0.328
C₁₄	0.280	0.257	0.470	0.073
C₁₅	0.213	0.362	0.363	0.635