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Impact of digital government construction on the intelligent transformation of enterprises: Evidence from China

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  • Zhang, Longpeng
  • Zhang, Xingye

Abstract

In the digital age, driving the intelligent transformation of enterprises is a crucial research topic. This study examines the impact of digital government development on enterprise transformation and explores the pathways to achieve it. Drawing from digital governance and institutional economics theories, government data openness, cloud platform construction, and intelligent government services provide a favorable external environment for enterprise transformation. Digital government development also reduces institutional transaction costs, thus enabling enterprises to invest more resources in technological innovation, including artificial intelligence applications. Empirical research on Chinese listed firms supports these findings. Furthermore, the construction of digital government can effectively promote innovation and management intelligence within the internal value chain of enterprises. Other heterogeneity analyses indicate that this effect is more pronounced in technology-intensive industries and developed regions.

Suggested Citation

  • Zhang, Longpeng & Zhang, Xingye, 2025. "Impact of digital government construction on the intelligent transformation of enterprises: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    • Handle: RePEc:eee:tefoso:v:210:y:2025:i:c:s0040162524005857
    DOI: 10.1016/j.techfore.2024.123787
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    as
    1. Maduku, Daniel K. & Mpinganjira, Mercy & Duh, Helen, 2016. "Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework," International Journal of Information Management, Elsevier, vol. 36(5), pages 711-723.
    2. Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K, 2019. "Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda," International Journal of Information Management, Elsevier, vol. 48(C), pages 63-71.
    3. Mohan, Sarah, 2016. "Institutional Change in Value Chains: Evidence from Tea in Nepal," World Development, Elsevier, vol. 78(C), pages 52-65.
    4. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    5. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    6. Rajan, Raghuram G & Zingales, Luigi, 1998. "Financial Dependence and Growth," American Economic Review, American Economic Association, vol. 88(3), pages 559-586, June.
    7. Zhai, Shaoxuan & Liu, Zhenpeng, 2023. "Artificial intelligence technology innovation and firm productivity: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PB).
    8. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    9. Xu, Nianhang & Li, Xiaorong & Yuan, Qingbo & Chan, Kam C., 2014. "Excess perks and stock price crash risk: Evidence from China," Journal of Corporate Finance, Elsevier, vol. 25(C), pages 419-434.
    10. Kabengele, Christian & Hahn, Rüdiger, 2021. "Institutional and firm-level factors for mobile money adoption in emerging markets–A configurational analysis," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    11. Amit Das & Shobha S. Das, 2022. "E-Government and Entrepreneurship: Online Government Services and the Ease of Starting Business," Information Systems Frontiers, Springer, vol. 24(3), pages 1027-1039, June.
    12. Kafouros, Mario & Chandrashekar, Subramanya Prasad & Aliyev, Murod & Au, Alan Kai Ming, 2022. "How do formal and informal institutions influence firm profitability in emerging countries?," Journal of International Management, Elsevier, vol. 28(1).
    13. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    14. Yiming Cao & Shuo Chen, 2022. "Rebel on the Canal: Disrupted Trade Access and Social Conflict in China, 1650–1911," American Economic Review, American Economic Association, vol. 112(5), pages 1555-1590, May.
    15. Siwei Wang & Xin Li & Zibiao Li & Yongwei Ye, 2023. "The effects of government support on enterprises' digital transformation: Evidence from China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(5), pages 2520-2539, July.
    16. Du, Jun & Mickiewicz, Tomasz, 2016. "Subsidies, rent seeking and performance: Being young, small or private in China," Journal of Business Venturing, Elsevier, vol. 31(1), pages 22-38.
    17. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    18. Kirill Borusyak & Xavier Jaravel & Jann Spiess, 2024. "Revisiting Event-Study Designs: Robust and Efficient Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3253-3285.
    19. Na Li & Ziyang Liu & Xi Zhang, 2022. "A Study on the Impact of Dynamic Visitor Demand on the Digital Transformation of Enterprises—Considerations Based on the Regional Innovation Environment and the Level of Big Data," Sustainability, MDPI, vol. 15(1), pages 1-19, December.
    20. Bessen, James & Impink, Stephen Michael & Reichensperger, Lydia & Seamans, Robert, 2022. "The role of data for AI startup growth," Research Policy, Elsevier, vol. 51(5).
    21. Tekic, Zeljko & Füller, Johann, 2023. "Managing innovation in the era of AI," Technology in Society, Elsevier, vol. 73(C).
    22. Jinqiang Wang & Yaobin Lu & Si Fan & Peng Hu & Bin Wang, 2021. "How to survive in the age of artificial intelligence? Exploring the intelligent transformations of SMEs in central China," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 17(4), pages 1143-1162, December.
    23. Enji Li & Qing Chen & Xinyan Zhang & Chen Zhang, 2023. "Digital Government Development, Local Governments’ Attention Distribution and Enterprise Total Factor Productivity: Evidence from China," Sustainability, MDPI, vol. 15(3), pages 1-19, January.
    24. Meiqun Yin & Lei Sheng, 2019. "Corporate governance, innovation input and corporate performance," Nankai Business Review International, Emerald Group Publishing Limited, vol. 10(1), pages 120-137, January.
    25. Kim, Youngok & Lui, Steven S., 2015. "The impacts of external network and business group on innovation: Do the types of innovation matter?," Journal of Business Research, Elsevier, vol. 68(9), pages 1964-1973.
    26. Thomas H. Davenport, 2018. "From analytics to artificial intelligence," Journal of Business Analytics, Taylor & Francis Journals, vol. 1(2), pages 73-80, July.
    27. Commons, John R., 1931. "Institutional Economics," History of Economic Thought Articles, McMaster University Archive for the History of Economic Thought, vol. 21, pages 648-657.
    28. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    29. Diego Reforgiato Recupero & Mario Castronovo & Sergio Consoli & Tarcisio Costanzo & Aldo Gangemi & Luigi Grasso & Giorgia Lodi & Gianluca Merendino & Misael Mongiovì & Valentina Presutti & Salvatore D, 2016. "An Innovative, Open, Interoperable Citizen Engagement Cloud Platform for Smart Government and Users’ Interaction," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 7(2), pages 388-412, June.
    30. Gan, Tian & Zhang, Mingxin & Zhang, Zhiqiang, 2023. "The impact of digital government policy on entrepreneurial activity in China," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 479-496.
    31. Nathan Nunn & Nancy Qian, 2014. "US Food Aid and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1630-1666, June.
    32. Yu, Feifei & Wang, Liting & Li, Xiaotong, 2020. "The effects of government subsidies on new energy vehicle enterprises: The moderating role of intelligent transformation," Energy Policy, Elsevier, vol. 141(C).
    33. Emrah Acar & Ismail Kocak & Yildiz Sey & David Arditi, 2005. "Use of information and communication technologies by small and medium-sized enterprises (SMEs) in building construction," Construction Management and Economics, Taylor & Francis Journals, vol. 23(7), pages 713-722.
    34. Anna Sanina & Aleksey Balashov & Mariia Rubtcova, 2023. "The Socio-Economic Efficiency of Digital Government Transformation," International Journal of Public Administration, Taylor & Francis Journals, vol. 46(1), pages 85-96, January.
    35. Hu, Juncheng & Li, Xiaorong & Duncan, Keith & Xu, Jia, 2020. "Corporate relationship spending and stock price crash risk: Evidence from China's anti-corruption campaign," Journal of Banking & Finance, Elsevier, vol. 113(C).
    36. Hongbin Cai & Hanming Fang & Lixin Colin Xu, 2011. "Eat, Drink, Firms, Government: An Investigation of Corruption from the Entertainment and Travel Costs of Chinese Firms," Journal of Law and Economics, University of Chicago Press, vol. 54(1), pages 55-78.
    37. Aroon P. Manoharan & James Melitski & Marc Holzer, 2023. "Digital Governance: An Assessment of Performance and Best Practices," Public Organization Review, Springer, vol. 23(1), pages 265-283, March.
    38. Xu, Chang & Jin, Long, 2024. "Effects of government digitalization on firm investment efficiency: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 819-834.
    39. Conceição Castro & Cristina Lopes, 2022. "Digital Government and Sustainable Development," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(2), pages 880-903, June.
    40. J. Ramon Gil-Garcia & Sharon S. Dawes & Theresa A. Pardo, 2018. "Digital government and public management research: finding the crossroads," Public Management Review, Taylor & Francis Journals, vol. 20(5), pages 633-646, May.
    41. Muhammad Tariq Majeed & Amna Malik, 2016. "E-government, Economic Growth and Trade: A Simultaneous Equation Approach," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 55(4), pages 499-519.
    42. Zhengxin Wang & Minghuan Shou & Shuai Wang & Ruinan Dai & Keqian Wang, 2019. "An Empirical Study on the Key Factors of Intelligent Upgrade of Small and Medium-sized Enterprises in China," Sustainability, MDPI, vol. 11(3), pages 1-16, January.
    43. Zhao, Shuliang & Teng, Linjiao & Arkorful, Vincent Ekow & Hu, Hui, 2023. "Impacts of digital government on regional eco-innovation: Moderating role of dual environmental regulations," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    44. Ellen Hughes-Cromwick & Julia Coronado, 2019. "The Value of US Government Data to US Business Decisions," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 131-146, Winter.
    45. Chen, Charles J.P. & Li, Zengquan & Su, Xijia & Sun, Zheng, 2011. "Rent-seeking incentives, corporate political connections, and the control structure of private firms: Chinese evidence," Journal of Corporate Finance, Elsevier, vol. 17(2), pages 229-243, April.
    46. Wan, Qunchao & Tang, Shiyi & Jiang, Zhenwu, 2023. "Does the development of digital technology contribute to the innovation performance of China's high-tech industry？," Technovation, Elsevier, vol. 124(C).
    47. Emiliana Blasio & Donatella Selva, 2019. "Implementing open government: a qualitative comparative analysis of digital platforms in France, Italy and United Kingdom," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 871-896, March.
    48. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    49. Yongyi Zhu & Di Yu, 2024. "Can government digitalization promote firm productivity? Evidence from Chinese listed firms," Applied Economics, Taylor & Francis Journals, vol. 56(33), pages 3939-3952, July.
    50. Yilin Zhong & Feng Xu & Longpeng Zhang, 2024. "Influence of artificial intelligence applications on total factor productivity of enterprises—evidence from textual analysis of annual reports of Chinese-listed companies," Applied Economics, Taylor & Francis Journals, vol. 56(43), pages 5205-5223, September.
    51. Martins, João & Veiga, Linda Gonçalves, 2022. "Digital government as a business facilitator," Information Economics and Policy, Elsevier, vol. 60(C).
    52. Bernd W. Wirtz & Jan C. Weyerer & Marcel Becker & Wilhelm M. Müller, 2022. "Open government data: A systematic literature review of empirical research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2381-2404, December.
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