高技术产业专业集聚、人力资本错配与创新绩效——以医药制造业为例

李拓晨; 梁蕾; 李韫畅

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科研管理 ›› 2021, Vol. 42 ›› Issue (4) : 131-137.

论文

高技术产业专业集聚、人力资本错配与创新绩效——以医药制造业为例

李拓晨，梁蕾，李韫畅

作者信息 +

Specialized agglomeration, human capital mismatch and innovation performance of the high-tech industry—A case study by taking the pharmaceutical manufacturing industry as an example

Li Tuochen, Liang Lei, Li Yunchang

Author information +

文章历史 +

摘要

以医药制造业为例，在运用变系数模型（LSDV）测度各地区医药制造业人力资本错配指数的基础上，构建以人力资本错配为门限的产业集聚驱动创新绩效的面板门限模型，实证研究专业集聚对创新绩效的门限特征及地区异质性。结果显示：医药制造业专业集聚与创新绩效存在非线性关系，专业集聚对创新绩效的作用受限于人力资本错配呈现显著的区间效应；研究将28个地区划分为人力资本高度错配地区、人力资本中度错配地区和人力资本低错配地区三种类型；研发人员投入、研发经费投入和研发机构数量显著促进创新绩效的提升，外资依存度对创新绩效存在一定的抑制作用。

Abstract

Innovation is the first driving force leading development. As a knowledge- and technology-intensive industry, technological innovation in high-tech industries is particularly important. It is not only the internal driving force and fundamental way to promote the transformation and upgrading of traditional industries, but also the key support for the country to occupy the high ground of global competition. Exerting the external characteristics of industrial agglomeration is an important way to improve the performance of technological innovation, and the exertion of externalities depends on the existing conditions in each region. Resource allocation is the basic condition for the development of regional high-tech industries, and its mismatch index will affect the innovation-driven effect of agglomeration. Therefore, considering the mismatch condition of regional human capital and associating it with professional agglomeration and innovation performance, taking the pharmaceutical manufacturing industry in the high-tech industry as an example, based on the use of variable coefficient model (LSDV) to measure the human capital mismatch index of the pharmaceutical manufacturing industry in various regions, this paper constructs a panel threshold model of industry agglomeration driving innovation performance with the threshold of human capital mismatch, and empirically studies the threshold characteristics and regional heterogeneity of professional agglomeration on innovation performance. The purpose is to explore whether there are regional differences in professional agglomeration-driven industrial innovation performance under different levels of human capital mismatch, so as to reveal the "black box" of industrial agglomeration externalities driving innovation and development. Through an empirical testing, the following results are obtained: first, during the inspection period, various regions of China have different levels of human capital mismatch problems, and there are significant differences between regions. Among them, the mismatch of human capital in most parts of the eastern region is relatively light, but all show positive mismatch characteristics. The mismatch of human capital in the central and western regions is more serious, and the mismatch is mainly negative. The impact of professional concentration in the pharmaceutical manufacturing industry on innovation performance is limited by the degree of regional human capital mismatch, and there is a significant double-threshold effect. Different human capital mismatches, innovation performance will be affected by different agglomeration externalities. Specifically, when the human capital mismatch index is low, professional agglomeration has a positive impact on innovation performance at a significant level of 10%. When the human capital mismatch index is a moderate mismatch, professional concentration has a negative impact on innovation performance at a significant level of 1%. When the human capital mismatch index is high, professional concentration has an extremely insignificant inhibitory effect on innovation performance. Therefore, the government should further strengthen the construction of the labor marketization process, reduce unreasonable intervention, and enable the market to give full play to the role of human capital allocation. Second, different regions should adopt differentiated industrial agglomeration policies. The government must re-examine the human capital allocation of the pharmaceutical manufacturing industry in the region, rationally arrange the staffing, and reduce the human capital mismatch index in order to give play to the positive externalities of industrial agglomeration on innovation performance.

导出引用

李拓晨梁蕾李韫畅. 高技术产业专业集聚、人力资本错配与创新绩效——以医药制造业为例[J]. 科研管理. 2021, 42(4): 131-137

Specialized agglomeration, human capital mismatch and innovation performance of the high-tech industry—A case study by taking the pharmaceutical manufacturing industry as an example[J]. Science Research Management. 2021, 42(4): 131-137

参考文献

[1] 杜威剑，李梦洁. 产业集聚会促进企业产品创新吗?——基于中国工业企业数据库的实证研究[J].产业经济研究， 2015(04) :1 - 9 + 20.

Du Weijian，Li Mengjie. Will industrial gathering promote product innovation? - Empirical Research Based on Chinese Industrial Enterprise Database[J]. Industrial Economics Research，2015(04) :1 - 9 + 20.

[2] Beaudry C，Breschi S. Are firms in clusters really more innovative[J]. Economics of Innovation and New Technology，2003，12( 4) :325 - 342.

[3] Combes P P. Economic structure and local growth: France，1984-1993[J]. Journal of Urban Economics，2000，47 ( 3): 329 － 355.

[4] Andersan，Quigley J M，Wilhelmssonm. Agglomeration and the spatial distribution of creativity[C]. Papers in Regional Science，2005，84( 3) : 445－464.

[5] 陈劲，梁靓，吴航. 开放式创新背景下产业集聚与创新绩效关系研究——以中国高技术产业为例[J]. 科学学研究，2013，31(04) :623 - 629 + 577.

Chen Jin，Liang Liang，Wu Hang. Research on the Relationship between Industrial Agglomeration and Innovation Performance under the Background of Open Innovation - Take China's high-tech industry as an example[J]. Studies in Science of Science，2013，31(04) :623 - 629 + 577.

[6] 谢子远. 高技术产业区域集聚能提高研发效率吗?——基于医药制造业的实证检验[J]. 科学学研究，2015，33(02) :215 - 224 + 233.

Xie Ziyuan.Can high-tech industrial clusters increase R&D efficiency? - Empirical test based on pharmaceutical manufacturing. Studies in Science of Science[J]. 2015， 33(02) : 215 - 224 + 233.

[7] 张宗益，李森圣. 高技术产业集聚外部性特征的动态性和差异性研究——基于时变参数估计的分析[J]. 产业经济研究，2014(03) :22 - 31.

Zhang Zongyi， Li Sensheng. Research on the Dynamics and Differences of the Characteristics of the Clustering of High-tech Industry—Based on the Analysis of Time-Varying Parameter Estimation[J]. Industrial Economics Research， 2014(03) :22 - 31.

[8] 沈能. 空间集聚、规模门槛与技术创新:基于中国制造业企业普查数据的实证分析[J].管理工程学报，2014， 28(04) :21 - 27.

Shen Neng. Spatial agglomeration，scale threshold and technological innovation: empirical analysis based on census data of Chinese manufacturing enterprises[J]. 2014，28(04) :21 - 27.

[9] Marshall Alfred.Principles of economics[M]，8 edition，Macmillan & Co, London, 1920.

[10] 季书涵，朱英明，张鑫. 产业集聚对资源错配的改善效果研究[J]. 中国工业经济，2016(06):73-90.

Ji Shuhan， Zhu Yingming， Zhang Xin. Research on the improvement effect of industrial agglomeration on resource mismatch[J]. China Industrial Economics， 2016(06): 73 - 90.

[11] 白俊红，卞元超. 要素市场扭曲与中国创新生产的效率损失[J]. 中国工业经济，2016(11) :39 - 55.

Bai Junhong，Bian Yuanchao. Factor Market Distortion and Efficiency Loss of China's Innovative Production[J]. China Industrial Economics， 2016(11) :39 - 55.

[12] 戴魁早，刘友金. 要素市场扭曲与创新效率—对中国高技术产业发展的经验分析[J]. 经济研究，2016，51(07) :72 - 86.

Dai Kuizao，Liu Youjin. Factor Market Distortion and Innovation Efficiency: An Empirical Analysis of China's High-tech Industry Development [J]. Economic Research， 2016，51(07) :72 - 86.

[13] 戴魁早，刘友金. 要素市场扭曲如何影响创新绩效[J]. 世界经济，2016，39(11) :54 - 79.

Dai Kuizao，Liu Youjin. How does factor market distortion affect innovation performance[J]. The Journal of World Economy，2016，39(11) :54 - 79.

[14] Hansen B. E. Threshold effects in non － dynamic panels: Estimation，testing，and inference[J]. Journal of Econometrics，1999( 93) :345 - 368.

[15] 刘焕鹏，严太华. OFDI 与国内创新能力关系中的“门槛效应”: 区域金融发展视角的实证分析[J]. 科研管理，2015，36( 1) : 1-7.

Liu Huanpeng，Yan Taihua. The "threshold effect" in the relationship between OFDI and domestic innovation capability: an empirical analysis of the perspective of regional financial development [J]. Scientific research management， 2015，36(1) :1 - 7.

[16] Jushan B. ，Pierre P.Estimating and Testing Linear Models with Multiple Structural Changes[J]. Econometrica，1998，66( 1) :47 - 78.

[17] 吴延兵. 中国工业产业创新水平及影响因素-面板数据的实证分析[J]. 产业经济评论，2006，5(02) :155 - 171.

Wu Yanbing. China's industrial industry innovation level and influencing factors - empirical analysis of panel data [J]. Review of Industrial Economics，2006，5(02) :155 - 171.

[18] 吕承超，商圆月. 高技术产业集聚模式与创新产出的时空效应研究[J]. 管理科学，2017，30(02) :64 - 79.

Lv Chengchao， Shang Yuanyue. Research on the time and space effect of high-tech industry agglomeration mode and innovation output [J]. Journal of Management Sciences，2017，30(02) : 64 - 79.

[19] Beaudry C，Schiffauerova A. Who' s right，Marshall or Jacobs? the localization versus urbanization debate[J]. Research Policy，2009，38( 2) : 318 - 337.

[20] 白俊红，刘宇英. 对外直接投资能否改善中国的资源错配[J].中国工业经济,2018(01):60-78.

Bai Junhong， Liu Yuying. Can foreign direct investment improve China's resource mismatch [J]. China Industrial Economics,2018(01):60-78.

[21] Wu，J，Z. X. Zhou， and L. Liang. Measuring the Performance of Chinese Regional Innovation Systems with Two-Stage DEA-Based Model[J]. International Journal of Sustainable Society，2010，2(1) :85 - 99.