The impact of artificial intelligence on enterprise production capacity from the perspective of integrated innovation

Chen Zili, Zhu Guilong

Science Research Management ›› 2026, Vol. 47 ›› Issue (10) : 21-29.

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Science Research Management ›› 2026, Vol. 47 ›› Issue (10) : 21-29. DOI: 10.19571/j.cnki.1000-2995.2026.10.003  CSTR: 32148.14.kygl.2026.10.003

The impact of artificial intelligence on enterprise production capacity from the perspective of integrated innovation

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Abstract

Promoting the deep integration of artificial intelligence (AI) and manufacturing is critical for driving high-quality development in the manufacturing sector and enhancing capacity utilization. Using a sample of A-share manufacturing firms listed on the Shanghai and Shenzhen stock exchanges between 2008 and 2022, this study applies Python text analysis to construct AI metrics and employs a panel fixed-effects model to investigate how the integrated innovation of AI with manufacturing technology impacts capacity utilization and its heterogeneous effects across technology types. The findings reveal that AI technology innovation and manufacturing technology innovation both significantly improve capacity utilization, with their integration yielding an even greater enhancement. Compared to exploitative manufacturing technologies, the integrated innovation of AI with exploratory manufacturing technologies produces a more pronounced capacity-enhancing effect. The integrated innovation of AI with manufacturing technology positively affects capacity utilization by improving asset flexibility and product competitiveness. This study contributes to the understanding of AI's enabling characteristics and offers valuable insights for improving capacity utilization.

Key words

artificial intelligence / capacity utilization / exploratory manufacturing technology / exploitative manufacturing technology

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Chen Zili , Zhu Guilong. The impact of artificial intelligence on enterprise production capacity from the perspective of integrated innovation[J]. Science Research Management. 2026, 47(10): 21-29 https://doi.org/10.19571/j.cnki.1000-2995.2026.10.003

References

[1]
皮建才, 宋大强. 中国制造业的产能过剩与就业波动[J]. 金融研究, 2023(11):115-131.
Pi Jiancai, Song Daqiang. Manufacturing overcapacity and employment volatility in China[J]. Journal of Financial Research, 2023(11):115-131.
[2]
Wang Z A, Zheng C. Is technological innovation the cure for overcapacity? Exploring mediating and moderating mechanisms[J]. Journal of Business Research, 2022, 147:348-361.
[3]
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, 40(5):40-59.
Huang Zhuo, Tao Yunqing, Liu Zhaoda, et al. How does intelligent manufacturing improve enterprise capacity utilization? Based on the perspective of integration of production and consumption[J]. Journal of Management World, 2024, 40(5):40-59.
[4]
Egger J, Masood T. Augmented reality in support of intelligent manufacturing:A systematic literature review[J]. Computers & Industrial Engineering, 2020, 140:106195.
[5]
Yang S P. Entry and exit decisions with switching regime excess capacity[J]. International Advances in Economic Research, 2018, 24(4):351-369.
[6]
林毅夫, 巫和懋, 邢亦青. “潮涌现象”与产能过剩的形成机制[J]. 经济研究, 2010, 45(10):4-19.
Lin Yifu, Wu Hemao, Xing Yiqing. "Wave phenomena" and formation of excess capacity[J]. Economic Research Journal, 2010, 45(10):4-19.
[7]
卞元超, 白俊红. 区域市场整合能否提升企业的产能利用率?[J]. 财经研究, 2021, 47(11):64-77.
Bian Yuanchao, Bai Junhong. Can regional market integration improve the capacity utilization of enterprises?[J]. Journal of Finance and Economics, 2021, 47(11):64-77.
[8]
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 Yongjin, Kuang Xia, Shao Wenbo. Informatization,firm's flexibility and capacity utilization[J]. The Journal of World Economy, 2017, 40(1):67-90.
[9]
Chen J, Chen X, Hou Q, et al. Haste doesn't bring success:Top-down amplification of economic growth targets and enterprise overcapacity[J]. Journal of Corporate Finance, 2021, 70:102059.
[10]
韩国高, 高铁梅, 王立国, 等. 中国制造业产能过剩的测度、波动及成因研究[J]. 经济研究, 2011, 46(12):18-31.
Han Guogao, Gao Tiemei, Wang Liguo, et al. Research on measurement, volatility and causes of excess production capacity of Chinese manufacturing industries[J]. Economic Research Journal, 2011, 46(12):18-31.
[11]
Wang H, Liao L, Wu J G. Robot adoption and firm's capacity utilization:Evidence from China[J]. Pacific-Basin Finance Journal, 2023, 82:102196.
[12]
Chen A, Zhao D, He C. Firm digital investments and capacity utilisation:A perspective of factor inputs[J]. Technological Forecasting & Social Change, 2024, 200:123182.
[13]
杜传忠, 曹效喜, 任俊慧. 人工智能影响我国全要素生产率的机制与效应研究[J]. 南开经济研究, 2024(2):3-24.
Du Chuanzhong, Cao Xiaoxi, Ren Junhui. Research on the mechanism and effect of artificial intelligence on total factor productivity in China[J]. Nankai Economic Studies, 2024(2):3-24.
[14]
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, 40(2):101-116,133.
Yao Jiaquan, Zhang Kunpeng, Guo Lipeng, et al. How does artificial intelligence improve firm productivity? Based on the perspective of labor skill structure adjustment[J]. Journal of Management World, 2024, 40(2):101-116,133.
[15]
Wang F, Li Q, Chen H. The interplay of intelligent manufacturing,innovation equilibrium and cost stickiness in the artificial intelligence era[J]. Systems Research and Behavioral Science, 2025, 42(4):1232-1244.
[16]
Bansak C, Morin N, Starr M. Technology,capital spending,and capacity utilization[J]. Economic Inquiry, 2007, 45(3):631-645.
[17]
Verganti R, Vendraminelli L, Iansiti M. Innovation and design in the age of artificial intelligence[J]. Journal of Product Innovation Management, 2020, 37(3):212-227.
[18]
Abou-Foul M, Ruiz-Alba J L, López-Tenorio P J. The impact of artificial intelligence capabilities on servitization:The moderating role of absorptive capacity:A dynamic capabilities perspective[J]. Journal of Business Research, 2023, 157:113609.
[19]
Johnson P C, Laurell C, Ots M, et al. Digital innovation and the effects of artificial intelligence on firms' research and development:Automation or augmentation,exploration or exploitation?[J]. Technological Forecasting and Social Change, 2022, 179:121636.
[20]
Leone D, Schiavone F, Appio F P, et al. How does artificial intelligence enable and enhance value co-creation in industrial markets? An exploratory case study in the healthcare ecosystem[J]. Journal of Business Research, 2021, 129:849-859.
[21]
Jakubovskis A. Flexible production resources and capacity utilization rates:A robust optimization perspective[J]. International Journal of Production Economics, 2017, 189:77-85.
[22]
马鸿佳, 林樾, 苏中锋, 等. 人工智能可供性、智能制造平台价值共创与制造企业数字化转型绩效[J]. 中国工业经济, 2024(6):155-173.
Ma Hongjia, Lin Yue, Su Zhongfeng, et al. Artificial intelligence affordance,intelligent manufacturing platform value co-creation and digital transformation performance of manufacturing enterprises[J]. China Industrial Economics, 2024(6):155-173.
[23]
Pillai R, Sivathanu B, Mariani M, et al. Adoption of AI-empowered industrial robots in auto component manufacturing companies[J]. Production Planning & Control, 2022, 33(16):1517-1533.
[24]
Yoo Y, Henfridsson O, Lyytinen K. The new organizing logic of digital innovation:An agenda for information systems research[J]. Information Systems Research, 2010, 21(4):724-735.
In this essay, we argue that pervasive digitization gives birth to a new type of product architecture: the layered modular architecture. The layered modular architecture extends the modular architecture of physical products by incorporating four loosely coupled layers of devices, networks, services, and contents created by digital technology. We posit that this new architecture instigates profound changes in the ways that firms organize for innovation in the future. We develop (1) a conceptual framework to describe the emerging organizing logic of digital innovation and (2) an information systems research agenda for digital strategy and the creation and management of corporate information technology infrastructures.
[25]
王凤彬, 陈建勋, 杨阳. 探索式与利用式技术创新及其平衡的效应分析[J]. 管理世界, 2012(3):96-112.
Wang Fengbin, Chen Jianxun, Yang Yang. An analysis of the effect of the explorative and exploitative innovations and their balance[J]. Journal of Management World, 2012(3):96-112.
[26]
徐翔, 赵墨非, 李涛, 等. 数据要素与企业创新:基于研发竞争的视角[J]. 经济研究, 2023, 58(2):39-56.
Xu Xiang, Zhao Mofei, Li Tao, et al. Data factor and enterprise innovation:The perspective of R&D competition[J]. Economic Research Journal, 2023, 58(2):39-56.
[27]
卢小平. 现代制造技术[M]. 2版. 北京: 清华大学出版社, 2011.
Lu Xiaoping. Modern manufacturing technology[M]. 2nd ed. Beijing: Tsinghua University Press, 2011.
[28]
刘凤朝, 张淑慧, 马荣康. 利用性创新对探索性创新的作用分析:技术景观复杂性的调节作用[J]. 管理评论, 2020, 32(9):97-106.
Liu Fengchao, Zhang Shuhui, Ma Rongkang. The effect of exploitative innovation on exploratory innovation:The moderating influence of technology landscape complexity[J]. Management Review, 2020, 32(9):97-106.
[29]
苏涛永, 陈永恒, 张亮亮, 等. 异质性业绩期望差距与企业双元创新:家族企业与非家族企业的比较研究[J]. 研究与发展管理, 2021, 33(4):169-182.
Su Taoyong, Chen Yongheng, Zhang Liangliang, et al. Heterogeneous performance aspiration gap and firm ambidextrous innovation: A comparative study on family firms and non-family firms[J]. R&D Management, 2021, 33(4):169-182.
[30]
赵涛, 张智, 梁上坤. 数字经济、创业活跃度与高质量发展:来自中国城市的经验证据[J]. 管理世界, 2020, 36(10):65-76.
Zhao Tao, Zhang Zhi, Liang Shangkun. Digital economy, entrepreneurship,and high-quality economic development:Empirical evidence from urban China[J]. Journal of Management World, 2020, 36(10):65-76.
[31]
Di Giuli A, Laux P A. The effect of media-linked directors on financing and external governance[J]. Journal of Financial Economics, 2022, 145(2):103-131.
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