Artificial Intelligence and Manufacturing Virtual Agglomeration

Abstract

Abstract: The deep application of AI in manufacturing is driving the evolution of manufacturing from traditional geographical agglomeration toward virtual agglomeration. However, the existing studies still focus primarily on geographical agglomeration and pay relatively limited attention to manufacturing virtual agglomeration, especially lacking systematic investigation into how AI influences manufacturing virtual agglomeration. Based on the panel data of 261 Chinese cities from 2014 to 2022, this paper measures the level of artificial intelligence development based on the number of patents, and constructs a comprehensive index of manufacturing virtual agglomeration that covers knowledge spillover networks, production platform networks, market networks, and network support capabilities. The results show that, first, the improvements in the level of AI can significantly enhance the degree of manufacturing virtual agglomeration at the city level. Second, human capital and entrepreneurial vitality serve as important transmission channels through which AI promotes manufacturing virtual agglomeration; by fostering human capital accumulation and stimulating entrepreneurial vitality, AI indirectly facilitates the formation and deepening of manufacturing virtual agglomeration. Third, the promoting effect of AI on manufacturing virtual agglomeration is more pronounced in eastern and central regions, in regions with higher levels of marketization, and in regions with greater R&D investment, indicating clear regional and contextual heterogeneity. These findings suggest that we should focus on the development of artificial intelligence, accumulation of human capital, and optimization of entrepreneurial ecology, implement differentiated regional layouts based on regional development stages, and form a policy pattern of coordinated promotion to better grasp the development trend of virtual agglomeration in the manufacturing industry under the background of digital economy.

Key words: AI, manufacturing virtual agglomeration, human capital, entrepreneurial vitality

CLC Number:

TP18
F426

Liu Xiao-nan, Chen Yun-ping. Artificial Intelligence and Manufacturing Virtual Agglomeration[J]. Contemporary Finance & Economics, 2026, 0(6): 73-85.

References

[1] 曹倩雯, 曾军平. 财政透明度与城市创业活力——基于新《预算法》实施的证据[J]. 当代财经, 2026, (4): 74-85.
[2] 钞小静, 廉园梅, 元茹静, 等. 数字基础设施建设与产业链韧性——基于产业链恢复能力数据的实证分析[J]. 数量经济技术经济研究, 2024, (11): 112-131.
[3] 陈楠, 蔡跃洲. 人工智能技术创新与区域经济协调发展——基于专利数据的技术发展状况及区域影响分析[J]. 经济与管理研究, 2023, (3): 16-40.
[4] 陈小勇. 产业集群的虚拟转型[J]. 中国工业经济, 2017, (12): 78-94.
[5] 段霞, 张蔷薇. 产业数字化、虚拟集聚与全要素生产率[J]. 西北师大学学报(社会科学版), 2023, (1): 135-144.
[6] 韩松岩. 人工智能技术对企业数字创新的影响研究[J]. 工业技术经济, 2022, (11): 13-22.
[7] 韩文龙, 陈其煜, 张瑞生. 人工智能推动劳动过程变革的内在机理与影响研究[J]. 江西财经大学学报, 2025, (6): 38-52.
[8] 黄群慧. 中国工业化进程与产业政策[J]. 中国经济报告, 2019, (1): 49-54.
[9] 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.
[10] 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.
[11] 苏涛永, 郭鑫, 李雅洁. 人工智能促进企业持续性创新了吗?——基于人力资本结构与知识吸收能力视角[J]. 商业经济与管理, 2025, (4): 71-86.
[12] 田霖, 韩岩博. 虚拟集聚理论与应用研究评介[J]. 重庆大学学报(社会科学版), 2021, (1): 77-90.
[13] 王如玉, 梁琦, 李广乾. 虚拟集聚:新一代信息技术与实体经济深度融合的空间组织新形态[J]. 管理世界, 2018, (2): 13-21.
[14] 王晓蕾, 杜传忠, 刘磊. 工业互联网赋能服务型制造网络的演化逻辑与路径优化研究[J]. 经济学家, 2022, (10): 108-118.
[15] 肖小虹, 彭金霞, 贺小刚. 技术市场赋能地方创业活力——来自中国省级地区的经验证据[J]. 经济问题探索, 2022, (10): 53-76.
[16] 谢伟丽, 石军伟, 张起帆. 人工智能、要素禀赋与制造业高质量发展——来自中国208个城市的经验证据[J]. 经济与管理研究, 2023, (4): 21-38.
[17] 徐浩, 肖毅, 祝志勇, 等. 人工智能赋能新质生产力的机制与效用研究——基于生产力要素新质化的视角[J]. 当代财经, 2025, (4): 84-96.
[18] 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+133+117-122.
[19] 叶云岭, 吴传清, 张力伟. 制造业集聚、空间知识溢出与城市创新绩效——来自中国283个城市的证据[J]. 统计与决策, 2023, (3): 73-77.
[20] 张莉, 陈凯, 李汉君. 数字经济赋能制造业产业链韧性: 多维机制与空间溢出[J]. 江西财经大学学报, 2025, (1): 35-47.
[21] 张青, 茹少峰. 制造业虚拟集聚模型构建、水平测度与行业差异研究[J]. 统计与决策, 2024, (15): 172-177.
[22] 张青, 茹少峰, 赵政楠. 虚拟集聚如何影响制造业企业高质量发展?[J]. 经济与管理研究, 2024, (6): 58-75.
[23] 张誉夫, 谢建国. 人工智能应用如何赋能企业供应链嵌入?——基于共享商业关联的网络结构视角[J]. 财经研究, 2025, (1): 63-77.
[24] 赵春明, 班元浩, 李宏兵, 等. 虚拟集聚能否促进城市出口产品质量升级[J]. 经济管理, 2022, (7): 23-41.
[25] 赵放, 李文婷, 马婉莹. 数字经济视域下地理集聚与虚拟集聚的演化特征及耦合关系[J]. 吉林大学社会科学学报, 2024, (1): 117-132+238.
[26] McAfee A, Brynjolfsson E. Machine, platform, crowd: Harnessing our digital future[M]. New York: WW Norton & Company, 2017.
[27] Neffke F, Henning M, Boschma R A.How do regions diversify over time? Industry relatedness and the development of new industries[J]. Economic Geography, 2009, 85(3): 227-257.
[28] Plathottam S J, Rzonca A, Lakhnori R, et al.A review of artificial intelligence applications in manufacturing operations[J/OL]. Journal of Advanced Manufacturing and Processing, 2023, 5(3): e10159.
[29] Porter M E.Clusters and the new economics of competition[M]. Boston: Harvard Business Review, 1998.
[30] Upadhyay A K, Khandelwal K.Applying artificial intelligence: Implications for recruitment[J]. Strategic HR Review, 2018, 17(5): 255-258.
[31] Vakola M, Wilson I E.The challenge of virtual organisation: Critical success factors in dealing with constant change[J]. Team Performance Management: An International Journal, 2004, 10(5/6): 112-120.