Enterprise Artificial Intelligence Application and Digital-Industrial Technology Integration: Evidence from Chinese Listed Enterprises

Main Article Content

Wan Liu
School of Finance, Hubei University of Economics, 430205, Wuhan, China

Fan Su
Hubei Key Laboratory of Digital Finance Innovation, Hubei University of Economics, 430205, Wuhan, China

DOI: https://doi.org/10.70267/fer.250301.156164

Keywords

artificial intelligence application, digital-industrial technology integration, digital transformation

Abstract

Based on data from Chinese non-financial listed enterprises from 2010 to 2023, this paper systematically investigates the impact of enterprise artificial intelligence applications on digital-industrial technology integration. The results indicate that enterprise artificial intelligence applications can effectively promote digital-industrial technology integration, with enhancing corporate knowledge absorption capacity and elevating corporate digitalization level of business scenarios serving as effective mechanisms. Heterogeneity tests reveal that the integration-promoting effect of artificial intelligence applications is stronger for enterprises with less financing constraints, higher synergy between human capital and artificial intelligence applications, and stronger digital economy policy support in their cities. This study provides important policy implications for uncovering the economic value of artificial intelligence applications and accelerating digital-industrial integration.

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References

  • [1] Zhao, M., Liu, R. and Dai, D. Synergistic effect between China’s digital transformation and economic development: A study based on sustainable development. Sustainability. 2021, 13(24), p. 13773. https://doi.org/10.3390/su132413773.
  • [2] Jin, C., Xu, A., Zhu, Y. and Li, J. Technology growth in the digital age: Evidence from China. Technological Forecasting and Social Change. 2023, 187, p. 122221. https://doi.org/10.1016/j.techfore.2022.122221.
  • [3] Prytkov, N. and Zamorev, A. Barriers to the integration of digital twin technology in manufacturing. Philosophical Problems of IT & Cyberspace (PhilIT&C). 2023, 1, pp. 53-64. https://doi.org/10.17726/philit.2023.1.5.
  • [4] Marioni, L. d. S., Rincon-Aznar, A. and Venturini, F. Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe. Journal of Economic Behavior & Organization. 2024, 228, p. 106762. https://doi.org/10.1016/j.jebo.2024.106762.
  • [5] Zhai, S. and Liu, Z. Artificial intelligence technology innovation and firm productivity: Evidence from China. Finance Research Letters. 2023, 58, p. 104437. https://doi.org/10.1016/j.frl.2023.104437.
  • [6] Zhang, B. and Peng, B. Artificial Intelligence and the Development of “Specialized, Refined, Unique, and Innovative” Small- and Medium-Sized Enterprises. Managerial and Decision Economics. 2025, 46(2), pp. 843-861. https://doi.org/10.1002/mde.4407.
  • [7] Bahoo, S., Cucculelli, M. and Qamar, D. Artificial intelligence and corporate innovation: A review and research agenda. Technological Forecasting and Social Change. 2023, 188, p. 122264. https://doi.org/10.1016/j.techfore.2022.122264.
  • [8] Wang, S., Huang, X., Xia, M. and Shi, X. Does Artificial Intelligence Promote Firms’ Innovation Efficiency: Evidence from the Robot Application. Journal of the Knowledge Economy. 2024, 15(4), pp. 16373-16394. https://doi.org/10.1007/s13132-023-01707-w.
  • [9] Shen, L., Jin, Y. and Xue, Q. Artificial intelligence and corporate investment efficiency. Finance Research Letters. 2025, 85, p. 108050. https://doi.org/10.1016/j.frl.2025.108050.
  • [10] Broekhuizen, T., Dekker, H., de Faria, P., Firk, S., Nguyen, D. K. and Sofka, W. AI for managing open innovation: Opportunities, challenges, and a research agenda. Journal of Business Research. 2023, 167, p. 114196. https://doi.org/10.1016/j.jbusres.2023.114196.
  • [11] Kuzior, A., Sira, M. and Brożek, P. Use of artificial intelligence in terms of open innovation process and management. Sustainability. 2023, 15(9), p. 7205. https://doi.org/10.3390/su15097205.
  • [12] An, Q., Wang, Y., Liu, F. and Wang, R. Does the integration of digital and real economies enhance corporate supply chain resilience? Evidence from China’s listed firms. Finance Research Letters. 2025, 85, p. 107953. https://doi.org/10.1016/j.frl.2025.107953.
  • [13] Sun, G., Fang, J., Li, J. and Wang, X. Research on the impact of the integration of digital economy and real economy on enterprise green innovation. Technological Forecasting and Social Change. 2024, 200, p. 123097. https://doi.org/10.1016/j.techfore.2023.123097.
  • [14] Sun, G., Yin, D., Kong, T. and Yin, L. The impact of the integration of the digital economy and the real economy on the risk of stock price collapse. Pacific-Basin Finance Journal. 2024, 85, p. 102373. https://doi.org/10.1016/j.pacfin.2024.102373.
  • [15] Wang, F. and Ye, L. Digital transformation and export quality of Chinese products: An analysis based on innovation efficiency and total factor productivity. Sustainability. 2023, 15(6), p. 5395. https://doi.org/10.3390/su15065395.
  • [16] Li, C., Xu, Y., Zheng, H., Wang, Z., Han, H. and Zeng, L. Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China’s listed companies. Resources Policy. 2023, 81, p. 103324. https://doi.org/10.1016/j.resourpol.2023.103324.
  • [17] Wang, Z., Li, M., Lu, J. and Cheng, X. Business Innovation based on artificial intelligence and Blockchain technology. Information Processing & Management. 2022, 59(1), p. 102759. https://doi.org/10.1016/j.ipm.2021.102759.
  • [18] Guo, L., Pei, H. and Liu, Y. Artificial intelligence and corporate green innovation: Evidence from China. Research in International Business and Finance. 2025, 79, p. 103039. https://doi.org/10.1016/j.ribaf.2025.103039.
  • [19] Liu, L., Cui, L., Han, Q. and Zhang, C. The impact of digital capabilities and dynamic capabilities on business model innovation: the moderating effect of organizational inertia. Humanities and Social Sciences Communications. 2024, 11(1), p. 420. https://doi.org/10.1057/s41599-024-02910-z.
  • [20] Wang, Y. and Han, P. Digital transformation, service-oriented manufacturing, and total factor productivity: Evidence from a-share listed companies in China. Sustainability. 2023, 15(13), p. 9974. https://doi.org/10.3390/su15139974.
  • [21] Zhang, Q., Wang, A. and Li, R. Enterprise value creation effects of artificial intelligence technology from the perspective of digital agility: evidence from China. Technology Analysis & Strategic Management. 2025, 37(12), pp. 2874-2888. https://doi.org/10.1080/09537325.2024.2383605.
  • [22] Hui, L., Xie, H. and Chen, X. Digital technology, the industrial internet, and cost stickiness. China Journal of Accounting Research. 2024, 17(1), p. 100339. https://doi.org/10.1016/j.cjar.2023.100339.
  • [23] Jalil, M. F., Lynch, P., Marikan, D. A. B. A. and Isa, A. H. B. M. The influential role of artificial intelligence (AI) adoption in digital value creation for small and medium enterprises (SMEs): does technological orientation mediate this relationship? AI & SOCIETY. 2025, 40(3), pp. 1875-1896. https://doi.org/10.1007/s00146-024-01969-1.
  • [24] Tianren, L. and Sufeng, H. Does digital-industrial technology integration reduce corporate carbon emissions? Environmental Research. 2024, 257, p. 119313. https://doi.org/10.1016/j.envres.2024.119313.
  • [25] Chen, L., Li, S. and She, Z. A study on the impact of artificial intelligence applications on corporate green technological innovation: A mechanism analysis from multiple perspectives. International Review of Economics & Finance. 2025, 103, p. 104490. https://doi.org/10.1016/j.iref.2025.104490.
  • [26] Xin, W. The impact of corporate artificial intelligence on financial risk: Evidence from China. Finance Research Letters. 2025, 81, p. 107435. https://doi.org/10.1016/j.frl.2025.107435.
  • [27] Kim, S., Kim, H. and Kim, E. How knowledge flow affects Korean ICT manufacturing firm performance: a focus on open innovation strategy. Technology Analysis & Strategic Management. 2016, 28(10), pp. 1167-1181. https://doi.org/10.1080/09537325.2016.1182150.
  • [28] Luo, K. and Zor, S. How does social network in patent provide changes in the Chinese manufacturing firm market value? Heliyon. 2023, 9(3), p. e14358. https://doi.org/10.1016/j.heliyon.2023.e14358.
  • [29] Hadlock, C. J. and Pierce, J. R. New evidence on measuring financial constraints: Moving beyond the KZ index. The Review of Financial Studies. 2010, 23(5), pp. 1909-1940. https://doi.org/10.1093/rfs/hhq009.
  • [30] Jin, Y., Li, X., Tian, G., Shi, J. and Wang, Y. Employee education level and efficiency of corporate investment. Journal of Accounting Literature. 2023, 47(2), pp. 277-297. https://doi.org/10.1108/JAL-08-2023-0150.
  • [31] Hong, S., Wang, T., Fu, X. and Li, G. Research on quantitative evaluation of digital economy policy in China based on the PMC index model. PLOS ONE. 2024, 19(2), p. e0298312. https://doi.org/10.1371/journal.pone.0298312.
  • [32] Zhao, W., Yang, X. and Sun, N. Do digital city policies promote corporate ESG performance? Evidence from research on textual analysis of China. Emerging Markets Finance and Trade. 2024, 60(13), pp. 2960-2979. https://doi.org/10.1080/1540496X.2024.2331013.

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Published
Mar 12, 2026
Issue
Vol. 3 No. 1 (2026)
Section
Research Articles
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How to Cite

Liu, W., & Su, F. (2026). Enterprise Artificial Intelligence Application and Digital-Industrial Technology Integration: Evidence from Chinese Listed Enterprises. Financial Economics Research, 3(1), 156-164. https://doi.org/10.70267/fer.250301.156164