摘要
数据是形成新质生产力的新型生产要素。选取2011—2022年中国A股上市公司面板数据,从效应分解视角考察数据要素对企业新质生产力的影响。研究发现:①就直接效应而言,数据要素能有效赋能企业新质生产力发展,且研究结论稳健;②就间接效应而言,企业新质创新与劳动力技能结构在数据要素推动企业新质生产力发展中发挥中介效应;③就乘数效应而言,在新质创新与劳动力技能结构推动企业新质生产力发展过程中,数据要素具有放大、叠加与倍增作用;④数据要素赋能效应在竞争激烈、高新技术与非重污染行业明显,且在数字基础设施完备、数据人才高水平集聚与数据开放地区更加有效。研究结论可为发挥数据要素乘数效应赋能新质生产力发展提供理论依据和政策启示。
The high-quality development of China's economy necessitates the unlocking of the potential of data elements,the advancement of productivity reforms and innovation,and the creation of new forms of high quality productive forces.However,current research fails to elucidate the mechanisms by which data elements influence the development of new high-quality productive forces within enterprises.It also falls short in addressing how traditional production factors interact with these data elements.As a result,enterprises struggle to understand how to leverage both data elements and traditional production factors to foster the development of their new high-quality productive forces in their day-to-day operations Therefore,this paper comprehensively constructs a theoretical analysis model of the data elements on the development of enterprises'new quality productive forces from three aspects:direct effect,indirect effect and multiplier effect.Using the panel data of Chinese listed companies from 2011 to 2022,this study examines the impact of the data elements on the development of new quality productive forces from the perspective of effect decomposition.The results show that(1)data elements can effectively empower the development of new quality productive forces of enterprises,and the conclusion is robust;(2)enterprises'new quality innovation and labor skill structure have a mediating effect in the development of enterprises'new quality productive forces empowered by data elements;(3)data elements has a multiplier effect in the process of new quality innovation and labor skill structure promoting the development of enterprise new quality productive forces;(4)the enabling effect of data elements is only obvious in highly competitive,high-tech and non-heavy pollution industries,and is more effective in regions with complete digital infrastructure,high level of data talent agglomeration and open data.According to the derived conclusions,data elements exert multiple influences on the development of new high-quality productive forces within enterprises.In terms of direct effects,firstly,data elements can improve the decision-making efficiency and quality of enterprises by driving their management decisions.Secondly,through data sharing and integration,on the one hand,enterprises can improve the communication efficiency among various departments;on the other hand,enterprises can improve the collaborative production efficiency within their respective supply chains.Thirdly,the application of enterprise data elements can promote the transparency of enterprise information to alleviate the information asymmetry between enterprises and investors,thus improving the financing efficiency of enterprises.Finally,the intricacy of a company's production processes can be significantly streamlined through the application of data elements.In terms of indirect effects,first of all,on the one hand,enterprises can realize the efficient connection between innovation supply and demand through the application of data elements,reducing the cost and risk of R&D innovation,and thus improving the efficiency of new quality innovation of enterprises.On the other hand,the application of data elements can optimize the technological process and product design of enterprises to ensure the improvement of the quality of new quality innovation.Secondly,through the application of data elements,enterprises will create jobs of high-skilled labor and have a substitution effect on low-skilled labor,which can improve the skill structure of enterprises'labor and thus promote the formation and development of enterprises'new quality productive forces.In terms of the multiplier effect of data factors,the core logic is that it can help enterprises re-understand the traditional factors of production,expand the allocation space of traditional factors,improve the efficiency of traditional resource allocation,and thus magnify the role of other factors in the development of new quality productive forces.This study specifically focuses on the multiplier effects of data elements on two key traditional factors:technology and labor.It finds that the multiplier effect of data elements on technology is reflected in the expansion of innovation boundary and the acceleration of technology iteration,and the multiplier effect on labor is reflected in the further improvement of the comprehensive quality of labor.To summarize,by constructing the analysis model of“direct effect—indirect effect—multiplier effect”,this paper provides empirical evidence and policy implications for clarifying the enabling effect of data elements on enterprises'new quality productive forces and releasing the potential of data elements'new quality productive forces.
作者
李丹
李旭浦
Li Dan;Li Xupu(Business School,Liaoning Technical University,Huludao 125100,China)
出处
《科技进步与对策》
北大核心
2025年第8期1-12,共12页
Science & Technology Progress and Policy
基金
辽宁省教育厅高校基本科研项目(JYIMS20230826)。
关键词
数据要素
新质生产力
新质创新
劳动力技能结构
乘数效应
Data Elements
New Quality Productive Forces
New Quality Innovation
Skill Structure of the Workforce
Multiplier Effect
作者简介
李丹(1984-),女,吉林长春人,博士,辽宁工程技术大学工商管理学院副教授、硕士生导师、博士生副导师,研究方向为数字经济学与产业转型升级;李旭浦(1998-),男,内蒙古包头人,辽宁工程技术大学工商管理学院硕士研究生,研究方向为数字经济学。
