摘要
近年来数字经济的蓬勃发展引起学术界广泛讨论,数据作为数字经济的衍生要素,为区域创新发展注入新动能。聚焦要素融合发展视角,以2012-2021年省际面板数据为样本,深入探讨数据+人力资本要素组合对区域创新发展的影响及作用路径。研究发现:(1)我国数据要素与人力资本的耦合协调度总体呈上升趋势,但仍处于磨合阶段且不同经济区域差异明显;(2)基准回归结果表明,数据要素与人力资本作为单独要素时均具有创新驱动效能,当二者结成要素组合时对创新的赋能强度更显著,该结论经过系列稳健性检验后依然成立;(3)异质性分析发现,在不同数字产业化与产业数字化地区要素组合的创新赋能效应存在显著差异,其中,数字产业化是数字经济背景下推动区域创新发展的“加速器”;(4)机制检验结果表明,数据要素与人力资本匹配可以通过溢出效应赋能区域创新发展,具体表现为技术转移、R&D人员流动两条路径,且前者中介效应占比为6.10%,后者中介效应占比为7.68%;(5)门槛检验结果表明,产业结构转型升级对要素组合赋能区域创新存在门槛效应,且作用效果具有显著区域异质性。
Data,as a derivative element of the digital economy,has injected new impetus into regional innovation and development.In this process,the coupling and coordinated development of human capital and data elements are crucial.In recent years,the vigorous development of the digital economy has sparked widespread discussion in academic circles.To further expand the existing research boundaries,this paper focuses on the perspective of factor combination and uses inter-provincial panel data to explore their impact and mechanism on regional innovation.In the characteristic fact statement,preliminary discussion is made based on the valid patent authorization information of the five major intellectual property offices from 2010 to 2021.During the statistical period,the total number of patents doubled,indicating that in the process of historical evolution,innovation-driven innovation is still an important engine to promote the progress of the Times.From the perspective of spatial and temporal distribution characteristics,the degree of coupling and coordination between data elements and human capital in China is generally on the rise,but it is still in the immature type,with significant regional differences.Specifically,the degree of coupling coordination between data elements and human capital is still low,and the overall stage is still developing.According to the coupling coordination type,the eight economic regions can be divided into the development pattern of inland regions driven by the growth pole of coastal areas.Furthermore,the benchmark regression results show that both data factors and human capital as individual factors have significant innovation-driving effects,but as combination factors,innovation empowering effects are stronger.After a series of robustness tests,this conclusion is still valid.Heterogeneity analysis shows that there are significant differences in empowering effects of factor combination innovation in different digital industrialization and industrial digitalization regions.The mechanism test results show that the matching of data elements and human capital can promote regional innovation development through spillover effects,which are mainly reflected in the two paths of technology transfer and R&D personnel flow.From the analysis of the test results of technology transfer,when other factors remain unchanged,the factor coupling degree D increases by 1 unit,resulting in an indirect increase of 0.31 units in regional innovation capability,and the indirect effect accounts for 6.10%.According to the analysis of the test results of R&D personnel flow,the factor coupling degree D increases by 1 unit,the R&D personnel flow level increases by 0.789 points,resulting in an indirect increase of 0.24 units in regional innovation capability,with the indirect effect accounting for 7.68%.The results of three-dimensional spatial fitting show that the transformation and upgrading of industrial structures have differential impacts on the regional innovation development of factor combination,so the threshold model is introduced for further analysis.Threshold regression results show that,on the whole,the transformation and upgrading level of industrial structure shows a dynamic role of marginal increase before and after crossing the threshold value,which fully indicates that the digital economy is a strong innovation driving force in the stage of high-quality development.However,from the perspective of sub-regions,before and after the transformation and upgrading of industrial structures crossed the threshold value,the eastern region has shown a promoting effect of marginal growth,with the factor coupling coordination coefficient passing the 1%significance test;while the central and western regions have exhibited a non-linear pattern of initial promotion followed by inhibition.The findings suggest that it is essential to encourage deep coupling between data elements and human capital to create sustainable regional innovation competitive advantages,focus on cultivating development engines centered around the digital industry,and form a positive feedback mechanism that promotes innovation through technology.Moreover,the channel effect of knowledge spillover should be valued to strengthen technological exchange between regions,and it is critical to encourage the free flow of R&D personnel between regions,enhance the level of industrial structure transformation and upgrading,and fully stimulate the"Metcalfe’s power"of the combination of data and human capital formation elements.
作者
范德成
肖文雪
Fan Decheng;Xiao Wenxue(School of Management,Harbin Institute of Technology,Harbin 150001,China)
出处
《科技进步与对策》
北大核心
2025年第5期69-81,共13页
Science & Technology Progress and Policy
基金
国家社会科学基金重点项目(19AGL007)
黑龙江省高等学校智库开放课题项目(3072023WJG0910)。
关键词
数据要素
人力资本
耦合协调模型
区域创新
门槛回归
Data Element
Human Capital
Coupling Coordination Model
Regional Innovation
Threshold Regression
