工业智能化对制造业高质量发展的影响研究

摘要/Abstract

摘要： 推动制造业高质量发展是当下中国面临的重要问题。以中国工业智能化与制造业加速融合为契机,利用2005—2017年省级面板数据,实证检验了工业智能化对制造业高质量发展的影响,研究发现：工业智能化与制造业发展质量之间呈“U型”关系,在更换指标和模型以及考虑内生性后这一结果依然稳健,且存在较强的行业异质性及区域异质性;工业智能化助推制造业高质量发展的主要渠道为优化劳动力结构、提升生产效率以及改善产品质量,而且影响效果随着时间推移愈发显著。政策启示在于：加强制造业领域的工业智能化应用;形成精准支撑的政策体系;发挥劳动力结构、生产效率以及产品质量的正向效应,引导工业智能化推动制造业高质量发展。

关键词: 工业智能化, 制造业高质量发展, 劳动力结构, 生产效率, 产品质量

Abstract: To promote the high-quality development of the manufacturing industry is an important issue that China is faced with at the moment. Taking advantage of the accelerated integration of China's industrial intelligence and manufacturing industry, this paper makes use of the provincial panel data from 2005 to 2017 to conduct an empirical test on the impact of industrial intelligence on the high-quality development of the manufacturing industry and its transmission mechanism. The findings show that there is a U-shaped relationship between the industrial intelligence and the quality of the manufacturing development; this result is still robust when the indicators and models are changed and the endogenousness is considered, and there exist stronger industrial heterogeneity and regional heterogeneity. The main channel for industrial intelligence to promote the high-quality development of the manufacturing industry is to optimize the structure of the labor force, increase production efficiency and improve product quality, and the influence becomes more and more significant over time. The policy enlightenment lies in: strengthening the application of industrial intelligence in the manufacturing sector, forming a policy system with precise support, giving full play to the positive effects of labor structure, production efficiency and product quality, and guiding industrial intelligence to promote the high-quality development of the manufacturing industry.

Key words: industrial intelligence, high-quality development of the manufacturing industry, labor structure, production efficiency, product quality

中图分类号:

F424

唐晓华, 迟子茗. 工业智能化对制造业高质量发展的影响研究[J]. 当代财经, 2021, 0(5): 102-114.

TANG Xiao-hua, CHI Zi-ming. The Impact of Industrial Intelligence on the High-Quality Development of Manufacturing Industry[J]. Contemporary Finance & Economics, 2021, 0(5): 102-114.

参考文献

[1] 韩江波. 智能工业化:工业化发展范式研究的新视角[J]. 经济学家,2017,(10):21-30.
[2] 李廉水,石喜爱,刘军. 中国制造业40年:智能化进程与展望[J]. 中国软科学,2019,(1):1-9+30.
[3] Frey C.B., Osborne M. A. The Future of Employment: How Susceptible Are Jobs to Computerisation[J]. Technological Forecasting and Social Change, 2017, 114(1): 254-280.
[4] Cheng H., Jia R.X., Li D. D., Li H. B. The Rise of Robots in China[J]. Journal of Economic Perspectives, 2019, 33(2): 71-88.
[5] 韩民春,韩青江. 机器人技术进步对劳动力市场的冲击——基于动态随机一般均衡模型的分析[J]. 当代财经,2020,(4):3-16.
[6] Acemoglu D., Lelarge C., Restrepo P.Competing with Robots: Firm-Level Evidence from France[R]. NBER Working Paper No. 26738, 2020.
[7] 李丫丫,潘安. 工业机器人进口对中国制造业生产率提升的机理及实证研究[J]. 世界经济研究,2017,(3):87- 96+136.
[8] 陈彦斌,林晨,陈小亮. 人工智能、老龄化与经济增长[J]. 经济研究,2019,(7):47-63.
[9] 林晨,陈小亮,陈伟泽,陈彦斌. 人工智能、经济增长与居民消费改善:资本结构优化的视角[J]. 中国工业经济,2020,(2):61-83.
[10] Cockburn I.M., Henderson R., Stern S. The Impact of Artificial Intelligence on Innovation[R]. NBER Working Paper No. 24449, 2018.
[11] 薛澜,姜李丹,黄颖,梁正. 资源异质性、知识流动与产学研协同创新——以人工智能产业为例[J]. 科学学研究,2019,(12):2241-2251.
[12] 吕越,谷玮,包群. 人工智能与中国企业参与全球价值链分工[J]. 中国工业经济,2020,(5):80-98.
[13] Mahalakshmi S., Arokiasamy A., Ahamed J.F. A. Productivity Improvement of an Eco Friendly Warehouse Using Multi-Objective Optimal Robot Trajectory Planning[J]. International Journal of Productivity and Quality Management, 2019, 27(3): 305-328.
[14] 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,(5):3-22.
[15] 师博. 人工智能助推经济高质量发展的机理诠释[J]. 改革,2020,(1):30-38.
[16] Liu J., Chang H.H., Forest J. Y. L., Yang B. H. Influence of Artificial Intelligence on Technological Innovation: Evidence from the Panel Data of China's Manufacturing Sectors[J]. Technological Forecasting and Social Change, 2020, 158: 120-142.
[17] 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,(10):159-175.
[18] Cords D., Prettner K.Technological Unemployment Revisited: Automation in a Search and Matching Framework[R]. GLO Discussion Paper Series 308, 2019.
[19] 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,(9):65-80.
[20] Furman J., Seamans R.AI and the Economy[R]. NBER Working Paper No. 24689, 2018.
[21] Graetz G., Michaels G.Robots at Work[J]. Review of Economics and Statistics, 2018, 100(5): 753-768.
[22] 孔高文,刘莎莎,孔东民. 机器人与就业——基于行业与地区异质性的探索性分析[J]. 中国工业经济,2020,(8):80-98.
[23] 杨光,侯钰. 工业机器人的使用、技术升级与经济增长[J]. 中国工业经济,2020,(10):138-156.
[24] 史丹,李鹏. 中国工业70年发展质量演进及其现状评价[J]. 中国工业经济,2019,(9):5-23.
[25] 郭然,原毅军. 生产性服务业集聚能够提高制造业发展质量吗?——兼论环境规制的调节效应[J]. 当代经济科学,2020,(2):120-132.
[26] 高运胜,杨阳. 全球价值链重构背景下我国制造业高质量发展目标与路径研究[J]. 经济学家,2020,(10):65-74.
[27] 魏敏,李书昊. 新时代中国经济高质量发展水平的测度研究[J]. 数量经济技术经济研究,2018,(11):3-20.
[28] 吴志军,梁晴. 中国经济高质量发展的测度、比较与战略路径[J]. 当代财经,2020,(4):17-26.
[29] 宋旭光,左马华青. 工业机器人投入、劳动力供给与劳动生产率[J]. 改革,2019,(9):45-54.
[30] 范洪敏,穆怀中. 环境规制对城镇二元劳动力就业的影响——基于劳动力市场分割视角[J]. 经济理论与经济管理,2017,(2):34-47.
[31] Borland J., Coelli M.Are Robots Taking Our Jobs?[J]. Australian Economic Review, 2017, 50(4): 377-397.
[32] 王瑞瑜,王森. 老龄化、人工智能与产业结构调整[J]. 财经科学,2020,(1):80-92.
[33] 王文,牛泽东,孙早. 工业机器人冲击下的服务业:结构升级还是低端锁定[J]. 统计研究,2020,(7):54-65.
[34] Edwards J.R., Lambert L. S. Methods for Integrating Moderation and Mediation: A General Analytical Framework Using Moderated Path Analysis[J]. Psychological Methods, 2007, 12(1): 1-22.
[35] Baron R.M., Kenny D. A. The Moderator-mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations[J]. Journal of Personality and Social Psychology, 1986, 51(6): 1173-1182.
[36] 温忠麟,叶宝娟. 中介效应分析:方法和模型发展[J]. 心理科学进展,2014,(5):731-745.