中国制造业企业信息技术投资存在“生产率悖论”吗?——基于技能偏向性视角的分析

摘要/Abstract

摘要： 加快新一代信息技术与实体经济深度融合是培育新质生产力、推动制造业高质量发展和实现新型工业化的必由之路。基于信息技术的通用目的性和技能偏向性特征，本文分析了信息技术投资影响制造业企业全要素生产率的直接机制和互补机制，并使用2007—2022年中国A股制造业上市公司数据进行实证检验。研究发现，信息技术投资能够显著提高企业全要素生产率，并且，信息技术投资与劳动技能结构之间存在互补效应，能够强化信息技术投资对企业全要素生产率的促进作用。同时，异质性分析发现，高教育水平劳动力与信息技术软件投资之间存在较强互补效应，有利于提高非国有企业和战略性新兴产业企业的全要素生产率水平；高技术水平劳动力与信息技术硬件投资和软件投资均能形成互补效应，可以显著提升不同所有制企业和战略性新兴产业企业的全要素生产率。因此，为进一步发挥信息技术投资对优化供给结构的关键作用，本文建议持续推进信息化和工业化深度融合，加大企业信息技术投资支持力度，引导企业优化要素资源配置，加快建设高技能人才队伍。

关键词: 信息技术投资, 劳动技能结构, 全要素生产率, 两化融合

Abstract: Accelerating the deep integration of new-generation information technology with the real economy is an essential path to foster new quality productive forces, promote the high-quality development of manufacturing industry, and achieve new industrialization. Based on the general-purpose and skill-biased characteristics of information technology (IT), this paper analyzes the direct mechanism and complementary mechanism through which IT investment influences the total factor productivity (TFP) of manufacturing enterprises, and conducts an empirical analysis using the data of A-share listed companies in China's manufacturing industry from 2007 to 2022. Study results show that IT investment can significantly improve enterprise TFP, and there exists a complementary effect between IT investment and the structure of labor skills, which can strengthen the promoting effect of IT investment on enterprise TFP. Furthermore, heterogeneous analysis reveals that there is a strong complementary effect between highly educated labors and IT software investment, which is beneficial to improving the TFP level of non-state-owned enterprises and enterprises in strategic emerging industries. Highly skilled labors exhibit a complementary effect with both IT hardware and software investment, significantly enhancing the enterprise TFP across different ownership structures and those in strategic emerging industries. Therefore, to further leverage the critical role of IT investment in optimizing the supply structure, this paper recommends continuously promoting the deep integration of informatization and industrialization, enhancing support for enterprise IT investments, guiding enterprises to optimize resource allocation, and accelerating the development of a highly skilled workforce.

Key words: information technology investment, labor skill structure, total factor productivity, integration of informatization and industrialization

付晨玉, 杨艳琳. 中国制造业企业信息技术投资存在“生产率悖论”吗?——基于技能偏向性视角的分析[J]. 管理评论, 2026, 38(3): 55-67.

Fu Chenyu, Yang Yanlin. Does the “Productivity Paradox” Exist in IT Investment of Chinese Manufacturing Enterprises?—An Analysis from the Perspective of Skill-biased Technical Change[J]. Management Review, 2026, 38(3): 55-67.

参考文献

[1] 孙早,刘李华.信息化提高了经济的全要素生产率吗——来自中国1979-2014年分行业面板数据的证据[J].经济理论与经济管理, 2018,(5):5-18 Sun Z., Liu L. H. Does Informatization Improve the TFP of Chinese Economy-Evidence from China's 1979-2014 Sectorial Panel Data[J]. Economic Theory and Business Management, 2018,(5):5-18
[2] Acemoglu D., Restrepo P. Artificial Intelligence, Automation and Work[R]. NBER Working Paper No.24196, 2018
[3] Acemoglu D., Restrepo P. Robots and Jobs:Evidence from US Labor Markets[J]. Journal of Political Economy, 2020,128(6):2188-2244
[4] 王林辉,胡晟明,董直庆.人工智能技术、任务属性与职业可替代风险:来自微观层面的经验证据[J].管理世界, 2022,38(7):60-79 Wang L. H., Hu S. M., Dong Z. Q. Artificial Intelligence Technology, Task Attribute and Occupational Substitutable Risk:Empirical Evidence from the Micro-Level[J]. Journal of Management World, 2022,38(7):60-79
[5] Autor D. H., Salomons A. Robocalypse Now-Does Productivity Growth Threaten Employment?[M]. Chicago:University of Chicago Press, 2017
[6] 王永钦,董雯.机器人的兴起如何影响中国劳动力市场?——来自制造业上市公司的证据[J].经济研究, 2020,55(10):159-175 Wang Y. Q., Dong W. How the Rise of Robots Has Affected China's Labor Market:Evidence from China's Listed Manufacturing Firms[J]. Economic Research Journal, 2020,55(10):159-175
[7] 蔡跃洲,陈楠.新技术革命下人工智能与高质量增长、高质量就业[J].数量经济技术经济研究, 2019,36(5):3-22 Cai Y. Z., Chen N. Artificial Intelligence and High-Quality Growth&Employment in the Era of New Technological Revolution[J]. Journal of Quantitative&Technological Economics, 2019,36(5):3-22
[8] 郭美晨,杜传忠. ICT提升中国经济增长质量的机理与效应分析[J].统计研究, 2019,36(3):3-16 Guo M. C., Du C. Z. Mechanism and Effect of Information and Communication Technology on Enhancing the Quality of China's Economic Growth[J]. Statistical Research, 2019,36(3):3-16
[9] 邵文波,匡霞,林文轩.信息化与高技能劳动力相对需求——基于中国微观企业层面的经验研究[J].经济评论, 2018,(2):15-29 Shao W. B., Kuang X., Lin W. X. Informationization and the Demand for Skilled Labor:Empirical Evidence Based on Micro-level Enterprises in China[J]. Economic Review, 2018,(2):15-29
[10] 李小平,李小克.偏向性技术进步与中国工业全要素生产率增长[J].经济研究, 2018,53(10):82-96 Li X. P., Li X. K. Biased Technological Change and the Total Factor Productivity Growth of China's Industry[J]. Economic Research Journal, 2018,53(10):82-96
[11] 余东华,张鑫宇,孙婷.资本深化、有偏技术进步与全要素生产率增长[J].世界经济, 2019,42(8):50-71 Yu D. H., Zhang X. Y., Sun T. Capital Deepening, Biased Technological Progress and Total Factor Productivity Growth[J]. The Journal of World Economy, 2019,42(8):50-71
[12] Berndt E. R., Morrison C. J. High-tech Capital Formation and Economic Performance in U.S. Manufacturing Industries an Exploratory Analysis[J]. Journal of Econometrics, 1995,65(1):9-43
[13] Stiroh K. J. Information Technology and the U. S. Productivity Revival:What do the Industry Data Say?[J]. American Economic Review, 2002,92(5):1559-1576
[14] Acemoglu D., Autor D., Dorn D., et al. Return of the Solow Paradox?IT, Productivity, and Employment in US Manufacturing[J]. American Economic Review, 2014,104(5):394-399
[15] 谢莉娟,陈锦然,王诗桪. ICT投资、互联网普及和全要素生产率[J].统计研究, 2020,37(9):56-67 Xie L. J., Chen J. R., Wang S. X. ICT Investment, Internet Penetration and Total Factor Productivity[J]. Statistical Research, 2020,37(9):56-67
[16] 王贵东,杨德林.互联网提升了制造企业的全要素生产率吗?——我国信息通信技术生产率悖论的再探讨[J].统计研究, 2023,40(6):63-76 Wang G. D., Yang D. L. Has the Internet Improved the TFP of Manufacturing Enterprises:A Re-discussion of China's ICT Productivity Paradox?[J]. Statistical Research, 2023,40(6):63-76
[17] Brynjolfsson E., Rock D., Syverson C. Artificial Intelligence and the Modern Productivity Paradox:A Clash of Expectations and Statistics[M]. Chicago:University of Chicago Press, 2019
[18] 孙早,侯玉琳.人工智能发展对产业全要素生产率的影响——一个基于中国制造业的经验研究[J].经济学家, 2021,(1):32-42 Sun Z., Hou Y. L. The Influence of Artificial Intelligence Development on Industrial Total Factor Productivity-An Empirical Research Based on Manufacturing Industries in China[J]. Economist, 2021,(1):32-42
[19] 黄群慧,余泳泽,张松林.互联网发展与制造业生产率提升:内在机制与中国经验[J].中国工业经济, 2019,(8):5-23 Huang Q. H., Yu Y. Z., Zhang S. L. Internet Development and Productivity Growth in Manufacturing Industry:Internal Mechanism and China Experiences[J]. China Industrial Economics, 2019,(8):5-23
[20] 赵宸宇,王文春,李雪松.数字化转型如何影响企业全要素生产率[J].财贸经济, 2021,42(7):114-129 Zhao C. Y., Wang W. C., Li X. S. How does Digital Transformation Affect the Total Factor Productivity of Enterprises?[J]. Finance&Trade Economics, 2021,42(7):114-129
[21] 丁相安,王晓岭,韩少杰.数字化转型、员工责任和企业全要素生产率[J].管理评论, 2024,36(10):199-211 Ding X. A., Wang X. L., Han S. J. Digital Transformation, Employee Responsibility and Total Factor Productivity[J]. Management Review, 2024,36(10):199-211
[22] 左晖,艾丹祥.技术变化方向异性和全要素生产率——来自中国制造业信息化的证据[J].管理世界, 2022,38(8):132-159 Zuo H., Ai D. X. Directional Heterogeneity of Technological Change and the Total Factor Productivity:Evidence from China's Manufacturing Informatization[J]. Journal of Management World, 2022,38(8):132-159
[23] Dos Santos B., Sussman L. Improving the Return on IT Investment:The Productivity Paradox[J]. International Journal of Information Management, 2000,20(6):429-440
[24] 汪淼军,张维迎,周黎安.信息化、组织行为与组织绩效:基于浙江企业的实证研究[J].管理世界, 2007,(4):96-104 Wang M. J., Zhang W. Y., Zhou L. A. Informationization, the Organizational Behavior and Performance:A Case Study Based on Zhejiang's Enterprises[J]. Journal of Management World, 2007,(4):96-104
[25] 王宇,王铁男,易希薇. R&D投入对IT投资的协同效应研究——基于一个内部组织特征的情境视角[J].管理世界, 2020,36(7):77-89 Wang Y., Wang T. N., Yi X. W. Research on the Synergistic Effect of R&D Expenditures for IT Investment:A Contingent View of Internal Organizational Factors[J]. Journal of Management World, 2020,36(7):77-89
[26] Bresnahan T. F., Brynjolfsson E., Hitt L. M. Information Technology, Workplace Organization, and the Demand for Skilled Labor:Firm-level Evidence[J]. The Quarterly Journal of Economics, 2002,117(1):339-376
[27] 何小钢,梁权熙,王善骝.信息技术、劳动力结构与企业生产率——破解"信息技术生产率悖论"之谜[J].管理世界, 2019,35(9):65-80 He X. G., Liang Q. X., Wang S. L. ICT, Labor Structure and Productivity:Resolve the Puzzle of "Information Technology Productivity Paradox" [J]. Journal of Management World, 2019,35(9):65-80
[28] 潘毛毛,赵玉林.互联网融合、人力资本结构与制造业全要素生产率[J].科学学研究, 2020,38(12):2171-2182 Pan M. M., Zhao Y. L. Internet Convergence, Labor Structure, and Total Factor Productivity in Manufacturing[J]. Studies in Science of Science, 2020,38(12):2171-2182
[29] 鲁晓东,连玉君.中国工业企业全要素生产率估计:1999-2007[J].经济学(季刊), 2012,11(2):541-558 Lu X. D., Lian Y. J. Estimation of Total Factor Productivity of Industrial Enterprises in China:1999-2007[J]. China Economic Quarterly, 2012,11(2):541-558
[30] 张辽,王俊杰.信息化密度、信息技术能力与制造业全球价值链攀升[J].国际贸易问题, 2020,(6):111-126 Zhang L., Wang J. J. Information Density, Information Technology Capability and Global Value Chain Climbing of Manufacturing Industry[J]. Journal of International Trade, 2020,(6):111-126
[31] 蔡跃洲,付一夫.全要素生产率增长中的技术效应与结构效应——基于中国宏观和产业数据的测算及分解[J].经济研究, 2017,52(1):72-88 Cai Y. Z., Fu Y. F. The Technical and Structural Effects of TFP Growth:Measurement and Decomposition Based on China's Macro and Sector Data[J]. Economic Research Journal, 2017,52(1):72-88
[32] 韩先锋,惠宁,宋文飞.信息化能提高中国工业部门技术创新效率吗[J].中国工业经济, 2014,(12):70-82 Han X. F., Hui N., Song W. F. Can Informatization Improve the Technology Innovation Efficiency of Chinese Industrial Sectors[J]. China Industrial Economics, 2014,(12):70-82
[33] 王永进,匡霞,邵文波.信息化、企业柔性与产能利用率[J].世界经济, 2017,40(1):67-90 Wang Y. J., Kuang X., Shao W. B. Informatization, Firm's Flexibility and Capacity Utilization[J]. The Journal of World Economy, 2017,40(1):67-90
[34] Brynjolfsson E., Milgrom P. Complementarity in Organizations[A]. Gibbons R., Roberts J. The Handbook of Organizational Economics (Volume Ⅰ)[C]. Princeton:Princeton University Press, 2013
[35] Antonelli C. Technological Congruence and the Economic Complexity of Technological Change[J]. Structural Change and Economic Dynamics, 2016,38:15-24
[36] 诸竹君,袁逸铭,焦嘉嘉.工业自动化与制造业创新行为[J].中国工业经济, 2022,(7):84-102 Zhu Z. J., Yuan Y. M., Jiao J. J. Industrial Automation and Manufacturing Innovation Behavior[J]. China Industrial Economics, 2022,(7):84-102
[37] 孙伟增,郭冬梅.信息基础设施建设对企业劳动力需求的影响:需求规模、结构变化及影响路径[J].中国工业经济, 2021,(11):78-96 Sun W. Z., Guo D. M. The Impact of Information Infrastructure on Enterprise Labor Demand:Change of Labor Demand Scale and Structure, and Its Influence Channel[J]. China Industrial Economics, 2021,(11):78-96
[38] 钱雪松,康瑾,唐英伦,等.产业政策、资本配置效率与企业全要素生产率——基于中国2009年十大产业振兴规划自然实验的经验研究[J].中国工业经济, 2018,(8):42-59 Qian X. S., Kang J., Tang Y. L., et al. Industrial Policy, Efficiency of Capital Allocation and Firm's Total Factor Productivity-Evidence from a Natural Experiment in China[J]. China Industrial Economics, 2018,(8):42-59
[39] 肖文,薛天航.劳动力成本上升、融资约束与企业全要素生产率变动[J].世界经济, 2019,42(1):76-94 Xiao W., Xue T. H. Rising Labour Costs, Financial Constraints and Changing TFP of Enterprises in China[J]. The Journal of World Economy, 2019,42(1):76-94
[40] 王铁男,王宇.信息技术投资、CEO过度自信与公司绩效[J].管理评论, 2017,29(1):70-81 Wang T. N., Wang Y. IT Investment, CEO Overconfidence, and Firm Performance[J]. Management Review, 2017,29(1):70-81