Volume 40 Issue 4
Jul.  2025
Turn off MathJax
Article Contents
LIU Hewang, LI Xiuyu, ZHENG Shilin. The Impact of Intelligent Manufacturing Policies on the New Quality Productive Forces in Enterprises[J]. Journal of Guangdong University of Finance & Economics, 2025, 40(4): 50-65.
Citation: LIU Hewang, LI Xiuyu, ZHENG Shilin. The Impact of Intelligent Manufacturing Policies on the New Quality Productive Forces in Enterprises[J]. Journal of Guangdong University of Finance & Economics, 2025, 40(4): 50-65.

The Impact of Intelligent Manufacturing Policies on the New Quality Productive Forces in Enterprises

  • Received Date: 2025-04-10
    Available Online: 2025-09-09
  • Publish Date: 2025-07-28
  • Leveraging the supportive and leading role of intelligent manufacturing to accelerate the formation of new quality productive forces is an inherent requirement and a crucial focal point for promoting high-quality development. Using the panel data from A-share listed manufacturing companies from 2011 to 2022, this study employs the difference-in-differences (DID) method to examine the impact of China's intelligent manufacturing pilot demonstration projects on new quality productive forces of the enterprises. The findings indicate that the implementation of intelligent manufacturing policies significantly enhances enterprise new quality productive forces, and the conclusion remains robust after a series of tests, including machine learning-based checks. Mechanism analysis reveals that intelligent manufacturing policies primarily foster new quality productive forces by promoting enterprise basic research, facilitating intelligent production transformation, and optimizing the labor structure. Heterogeneity analysis shows that the effect of the policy on improving new quality productive forces of the enterprises is particularly significant in high-tech enterprises, technology-intensive and labor-intensive industries, and regions with higher levels of intellectual property protection. Further analysis reveals that intelligent manufacturing policies also generate positive spillover effects on new quality productive forces of the downstream enterprises. The study provides valuable theoretical support and practical insights for the promotion of national industrial intelligence policies and the leap forward in new quality productive forces of the enterprises.
  • loading
  • [1]
    黄卓, 陶云清, 刘兆达, 等. 智能制造如何提升企业产能利用率——基于产消合一的视角[J]. 管理世界, 2024(5): 40-59. doi: 10.3969/j.issn.1002-5502.2024.05.003
    [2]
    权小锋, 李闯. 智能制造与成本粘性——来自中国智能制造示范项目的准自然实验[J]. 经济研究, 2022(4): 68-84.
    [3]
    LIU C, JI H, WEI J. Smart supply chain risk assessment in intelligent manufacturing[J]. Journal of Computer Information Systems, 2021, 62(3): 609-621.
    [4]
    ZHANG W, LI H, QIAN L, et al. How intelligent manufacturing improves corporate ESG performance: a three-dimensional analysis based on 'Environment', 'Society', and 'Governance'[J]. Journal of Environmental Management, 2025, 380: 125171. doi: 10.1016/j.jenvman.2025.125171
    [5]
    辛大楞, 季存睿, 辛立国. 智能转型对企业出口规模的影响研究: 基于"智能制造试点示范专项行动"的准自然实验[J]. 世界经济研究, 2024(6): 45-59, 136.
    [6]
    尹洪英, 李闯. 智能制造赋能企业创新了吗?——基于中国智能制造试点项目的准自然试验[J]. 金融研究, 2022(10): 98-116.
    [7]
    曹玉平, 侯迎信. 智能制造计划可以跨越"生产率悖论"吗: 来自智能制造试点示范项目的准自然实验[J]. 中国软科学, 2024(6): 23-32. doi: 10.3969/j.issn.1002-9753.2024.06.003
    [8]
    沈坤荣, 乔刚, 林剑威. 智能制造政策与中国企业高质量发展[J]. 数量经济技术经济研究, 2023(2): 5-25.
    [9]
    韩喜平, 马丽娟. 发展新质生产力与推动高质量发展[J]. 思想理论教育, 2024(4): 4-11.
    [10]
    温科, 李常洪. 数实技术融合对企业新质生产力的影响研究[J/OL]. 科研管理. http://kns.cnki.net/kcms/detail/11.1567.G3.20250122.1420.009.html.
    [11]
    宋佳, 张金昌, 潘艺. ESG发展对企业新质生产力影响的研究——来自中国A股上市企业的经验证据[J]. 当代经济管理, 2024(6): 1-11.
    [12]
    刁海璨. 企业基础研究与新质生产力培育[J]. 数量经济技术经济研究, 2025(3): 91-110.
    [13]
    周文, 何雨晴. 新质生产力: 中国式现代化的新动能与新路径[J]. 社会科学文摘, 2024(4): 3-15.
    [14]
    韩文龙, 张瑞生, 赵峰. 新质生产力水平测算与中国经济增长新动能[J]. 数量经济技术经济研究, 2024(6): 5-25.
    [15]
    印剑, 夏惟怡, 曹向. 新质生产力赋能全球价值链跃升的理论逻辑与推进路径[J]. 广东财经大学学报, 2025(2): 83-89. doi: 10.20209/j.gcxb.441711.20250319.001
    [16]
    张建伟, 王越, 张洪昌. 新质生产力赋能数字化审计发展: 逻辑、挑战与路径[J]. 财会月刊, 2024(23): 25-29.
    [17]
    肖有智, 张晓兰, 刘欣. 新质生产力与企业内部薪酬差距——基于共享发展视角[J]. 经济评论, 2024(3): 75-91.
    [18]
    刘洪, 仲黍林, 彭乔依. 智能制造何以驱动企业新质生产力发展——来自智能制造试点示范项目推广的证据[J]. 现代财经(天津财经大学学报), 2025(3): 3-24.
    [19]
    万长松, 徐志源, 柴亚杰. 新质生产力论[J]. 河南师范大学学报(哲学社会科学版), 2024(2): 1-6.
    [20]
    LI L. China's manufacturing locus in 2025: with a comparison of 'made-in-China 2025' and 'industry 4.0'[J]. Technological Forecasting and Social Change, 2018, 135: 66-74.
    [21]
    BARARI A, DE SALES GUERRA TSUZUKI M, COHEN Y, et al. Editorial: intelligent manufacturing systems towards industry 4.0 era[J]. Journal of Intelligent Manufacturing, 2021, 32(7): 1793-1796.
    [22]
    HANG L, LU W, GE X, et al. R&D innovation, industrial evolution and the labor skill structure in China manufacturing[J]. Technological Forecasting and Social Change, 2024, 204: 123434.
    [23]
    MOEUF A, PELLERIN R, LAMOURI S, et al. The industrial management of smes in the era of industry 4.0[J]. International Journal of Production Research, 2017, 56(3): 1118-1136.
    [24]
    VELDKAMP L, CHUNG C. Data and the aggregate economy[J]. Journal of Economic Literature, 2024, 62(2): 458-484.
    [25]
    刘伟, 卢泓方, 于龙振, 等. 智能化转型、经济政策不确定性与制造业创新——基于创新动机视角[J]. 广东财经大学学报, 2024(3): 4-19. https://song.cbpt.cnki.net/WKG/WebPublication/paperDigest.aspx?paperID=a8babc0b-1559-4af9-a8b2-4d3816b17609
    [26]
    MOHD ARIPIN N, NAWANIR G, HUSSAIN S. Save it for a rainy day! lean strategies for cost saving: the role of lean maturity[J]. Journal of Industrial Engineering and Management, 2023, 16(1): 115.
    [27]
    ACEMOGLU D. Technical change, inequality, and the labor market[J]. Journal of Economic Literature, 2002, 40(1): 7-72.
    [28]
    ACEMOGLU D, RESTREPO P. Robots and jobs: evidence from US labor markets[J]. Journal of Political Economy, 2020, 128(6): 2188-2244.
    [29]
    FRANK A G, DALENOGARE L S, AYALA N F. Industry 4.0 technologies: implementation patterns in manufacturing companies[J]. International Journal of Production Economics, 2019, 210: 15-26.
    [30]
    郑世林, 张果果. 制造业发展战略提升企业创新的路径分析——来自十大重点领域的证据[J]. 经济研究, 2022(9): 155-173.
    [31]
    张雪兰, 王剑, 徐子尧, 等. 惟精惟勤, 玉汝于成: 信贷专业化与企业新质生产力发展[J]. 金融经济学研究, 2024(5): 3-21.
    [32]
    郭冬梅, 王继彬, 胡瀚清, 等. 基于文本的创新测度及对企业绩效的影响研究[J]. 系统工程理论与实践, 2024(6): 1896-1912.
    [33]
    RAMBACHAN A, ROTH J. A more credible approach to parallel trends[J]. Review of Economic Studies, 2023, 90(5): 2555-2591.
    [34]
    谷城, 张树山. 智能制造何以实现企业绿色创新"增量提质"[J]. 产业经济研究, 2023(1): 129-142.
    [35]
    姚加权, 张锟澎, 郭李鹏, 等. 人工智能如何提升企业生产效率?——基于劳动力技能结构调整的视角[J]. 管理世界, 2024(2): 101-116.
    [36]
    GOODMAN-BACON A. Difference-in-differences with variation in treatment timing[J]. Journal of Econometrics, 2021, 225(2): 254-277.
    [37]
    DE CHAISEMARTIN C, D'HAULTFOEUILLE X. Two-way fixed effects estimators with heterogeneous treatment effects[J]. American Economic Review, 2020, 110(9): 2964-2996.
    [38]
    江艇. 因果推断经验研究中的中介效应与调节效应[J]. 中国工业经济, 2022(5): 100-120.
    [39]
    FEE C E, HADLOCK C J, PIERCE J R. Investment, financing constraints, and internal capital markets: evidence from the advertising expenditures of multinational firms[J]. Review of Financial Studies, 2008, 22(6): 2361-2392.
    [40]
    郑世林, 汉馨语, 郭锡栋, 等. 国家战略科技力量与企业关键核心技术突破——来自国家和省级重点实验室的证据[J]. 中国工业经济, 2024(9): 62-80.
    [41]
    尹美群, 盛磊, 李文博. 高管激励、创新投入与公司绩效——基于内生性视角的分行业实证研究[J]. 南开管理评论, 2018(1): 109-117.
    [42]
    沈国兵, 黄铄珺. 城市层面知识产权保护对中国企业引进外资的影响[J]. 财贸经济, 2019(12): 143-157.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(2)  / Tables(9)

    Article Metrics

    Article Views(7) PDF Downloads(2) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return