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Does public data openness accelerate new quality productive forces? Evidence from China

Author

Listed:
  • Zhong, Yuan
  • Lai, Huisu
  • Zhang, Liang
  • Guo, Lixiang
  • Lai, Xiaobing

Abstract

This study explores the impact of public data openness on Chinese listed companies' new quality productive forces. Based on text analysis and machine learning, the results show that public data openness significantly improves the new quality productive forces of enterprises. Through the channels of improving the quality of information disclosure, enhancing the quality of innovation, and improving the efficiency of the supply chain, the new quality productive forces of enterprises can be promoted to achieve a leap. In addition, intellectual property protection, science and technology financial expenditure, and digital transformation positively moderated the relationship between public data openness and new quality productive forces. The results have important implications for emerging market economies to enhance the new quality productive forces of enterprises through the opening of public data.

Suggested Citation

  • Zhong, Yuan & Lai, Huisu & Zhang, Liang & Guo, Lixiang & Lai, Xiaobing, 2025. "Does public data openness accelerate new quality productive forces? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 1409-1427.
    • Handle: RePEc:eee:ecanpo:v:85:y:2025:i:c:p:1409-1427
    DOI: 10.1016/j.eap.2025.01.025
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    Citations

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    Cited by:

    1. Debao Dai & Yu Zheng, 2025. "The New Quality Productive Force, Science and Technology Innovation, and Optimization of Industrial Structure," Sustainability, MDPI, vol. 17(10), pages 1-21, May.
    2. Yuan Yuan & Hong Dai & Jiaqi Ma, 2025. "The Impact of Corporate ESG Performance on Supply Chain Resilience: A Mediation Analysis Based on New Quality Productive Forces," Sustainability, MDPI, vol. 17(10), pages 1-20, May.
    3. Jie Wang & Xiaohui Zhou & Yunning Ma & Yongrok Choi, 2025. "Public Data Elements and Enterprise Digital Transformation: A Quasi-Natural Experiment Based on Open Government Data Platforms for Sustainable Urban Planning," Sustainability, MDPI, vol. 17(10), pages 1-32, May.

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