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Digital transformation and total factor productivity: Empirical evidence from China

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  • Zhonghao Lei
  • Dongmei Wang

Abstract

Digital transformation plays a crucial role in improving the quality development of companies in this era of digital economy with ever-changing technologies. This paper empirically investigates the impact of corporate digital transformation on total factor productivity and the mechanism of action, using A-share listed companies in Shanghai and Shenzhen from 2011–2021 as the research sample, and found that the digital transformation of companies significantly improves total factor productivity, with the plausibility of the findings being verified by a series of robustness tests. Based on the heterogeneity study, it is found that such effect is stronger for private companies, non-high-tech companies, and companies with a high degree of industry competition. The mechanism test indicates that digital transformation facilitates total factor productivity through four ways: strengthening company technological innovation, reducing operational costs, increasing resource allocation efficiency, and improving human capital structure. The findings of this paper support a better understanding of the micro effects of digital transformation and provide empirical evidence for policy formulation and adjustment.

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  • Zhonghao Lei & Dongmei Wang, 2023. "Digital transformation and total factor productivity: Empirical evidence from China," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-18, October.
    • Handle: RePEc:plo:pone00:0292972
    DOI: 10.1371/journal.pone.0292972
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    References listed on IDEAS

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    Cited by:

    1. Ren, Yuheng & Zhang, Jue & Wang, Xin, 2024. "How does data factor utilization stimulate corporate total factor productivity: A discussion of the productivity paradox," International Review of Economics & Finance, Elsevier, vol. 96(PC).
    2. Qi Zhang & Jinghuai She, 2024. "Digital transformation and corporate tax avoidance: An analysis based on multiple perspectives and mechanisms," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-30, September.
    3. Yujiao Bai & Hao Zhang, 2024. "Research on the impact of enterprise mergers and acquisitions on technological innovation: An empirical analysis based on listed Chinese enterprises," PLOS ONE, Public Library of Science, vol. 19(11), pages 1-24, November.

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