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The Impact of Market-Oriented Allocation of Data Elements on Enterprises’ New Quality Productive Forces

Author

Listed:
  • Yacheng Zhou

    (Business School, Zhejiang Wanli University, Ningbo 315100, China)

  • Guang Li

    (Business School, Zhejiang Wanli University, Ningbo 315100, China)

  • Tong Sun

    (Business School, Zhejiang Wanli University, Ningbo 315100, China)

  • Weidong Huo

    (Division of Economics, Liaoning University, Shenyang 110036, China)

Abstract

This paper takes the quasi-natural experiment from the National Big Data Comprehensive Pilot Zone (NBDCPZ) in China as an example to examine the impact of market-oriented allocation of data elements on enhancing enterprises’ New Quality Productive Forces (NQPF). Based on panel data from China’s A-share listed enterprises on the Shanghai and Shenzhen stock exchanges between 2011 and 2022, this study employs a robust policy evaluation method, the multi-way fixed effects staggered difference-in-differences (MWFE Staggered DID) method, to analyze the impact of the NBDCPZ on NQPF comprehensively. The key findings are threefold: First, the NBDCPZ significantly boosts enterprises’ NQPF within their jurisdictions. Second, the NBDCPZ enhances NQPF by accelerating enterprise digital transformation, and the digital talent can amplify the promotional effect of the NBDCPZ on enterprise digital transformation. Third, the NQPF-enhancing effects are more pronounced for privately owned enterprises (POEs), foreign-invested enterprises (FIEs), and smaller enterprises, whereas they exhibit an inhibitory impact on state-owned enterprises (SOEs) and large enterprises. Fourth, the promotional effect of the NBDCPZ on enterprises’ NQPF varies across different industries. Furthermore, regional (city-level) digital infrastructure and financial development levels amplify the NQPF-enhancing effects of the NBDCPZ.

Suggested Citation

  • Yacheng Zhou & Guang Li & Tong Sun & Weidong Huo, 2025. "The Impact of Market-Oriented Allocation of Data Elements on Enterprises’ New Quality Productive Forces," Sustainability, MDPI, vol. 17(18), pages 1-28, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8262-:d:1749418
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    References listed on IDEAS

    as
    1. Manasi Deshpande & Yue Li, 2019. "Who Is Screened Out? Application Costs and the Targeting of Disability Programs," American Economic Journal: Economic Policy, American Economic Association, vol. 11(4), pages 213-248, November.
    2. Fusheng Xie & Nan Jiang & Xiaolu Kuang, 2025. "Towards an accurate understanding of ‘new quality productive forces’," Economic and Political Studies, Taylor & Francis Journals, vol. 13(1), pages 1-15, January.
    3. Baker, Andrew C. & Larcker, David F. & Wang, Charles C.Y., 2022. "How much should we trust staggered difference-in-differences estimates?," Journal of Financial Economics, Elsevier, vol. 144(2), pages 370-395.
    4. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
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