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Impact of data factor and data integration on economic development: Empirical insights from China

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  • Chu, Zhaopeng
  • Chen, Xin
  • Yang, Jun

Abstract

Data factor is the foundation of digital empowerment for economic development. This paper studies data factor and its integration with other production factors by theoretically deducing and empirically testing its impacts on economic development. Working with provincial level data from China, the investigation reveals a positive and nonlinear impact of data factor on economic development. When applied at an advanced level, data factor can transform capital and labor into digital production factors, which boost economic development. The effects of data and digital production factors vary across regions and industries. Mechanism analysis shows that the effects of data factor and digital production factors on economic development are mediated by total factor productivity. These results offer clear evidence that all countries can benefit from digital transformation of the economy.

Suggested Citation

  • Chu, Zhaopeng & Chen, Xin & Yang, Jun, 2025. "Impact of data factor and data integration on economic development: Empirical insights from China," Telecommunications Policy, Elsevier, vol. 49(8).
  • Handle: RePEc:eee:telpol:v:49:y:2025:i:8:s0308596125001016
    DOI: 10.1016/j.telpol.2025.103004
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    References listed on IDEAS

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    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    3. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    4. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    5. Laura Veldkamp & Cindy Chung, 2024. "Data and the Aggregate Economy," Journal of Economic Literature, American Economic Association, vol. 62(2), pages 458-484, June.
    6. Daron Acemoglu & Pascual Restrepo, 2018. "Modeling Automation," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 48-53, May.
    7. Shin, Dong-Hee, 2016. "Demystifying big data: Anatomy of big data developmental process," Telecommunications Policy, Elsevier, vol. 40(9), pages 837-854.
    8. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, January.
    9. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    10. 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).
    11. Tao, Chang-Qi & Yi, Meng-Ying & Wang, Chang-Song, 2023. "Coupling coordination analysis and Spatiotemporal heterogeneity between data elements and green development in China," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 1-15.
    12. Ferschli Benjamin & Rehm Miriam & Schnetzer Matthias & Zilian Stella, 2021. "Digitalization, Industry Concentration, and Productivity in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 241(5-6), pages 623-665, November.
    13. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    14. Gao, Qiang & Cheng, Changming & Sun, Guanglin, 2023. "Big data application, factor allocation, and green innovation in Chinese manufacturing enterprises," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    15. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    16. Ufuk Akcigit & Qingmin Liu, 2016. "The Role Of Information In Innovation And Competition," Journal of the European Economic Association, European Economic Association, vol. 14(4), pages 828-870, August.
    17. Lin, Runhui & Xie, Zaiyang & Hao, Yunhong & Wang, Jie, 2020. "Improving high-tech enterprise innovation in big data environment: A combinative view of internal and external governance," International Journal of Information Management, Elsevier, vol. 50(C), pages 575-585.
    18. Pan, Wenrong & Xie, Tao & Wang, Zhuwang & Ma, Lisha, 2022. "Digital economy: An innovation driver for total factor productivity," Journal of Business Research, Elsevier, vol. 139(C), pages 303-311.
    19. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    20. Maryam Farboodi & Laura Veldkamp, 2021. "A Model of the Data Economy," NBER Working Papers 28427, National Bureau of Economic Research, Inc.
    21. Lynn Wu & Lorin Hitt & Bowen Lou, 2020. "Data Analytics, Innovation, and Firm Productivity," Management Science, INFORMS, vol. 66(5), pages 2017-2039, May.
    22. HUO, Peng & WANG, Luxin, 2022. "Digital economy and business investment efficiency: Inhibiting or facilitating?," Research in International Business and Finance, Elsevier, vol. 63(C).
    23. Lin William Cong & Danxia Xie & Longtian Zhang, 2021. "Knowledge Accumulation, Privacy, and Growth in a Data Economy," Management Science, INFORMS, vol. 67(10), pages 6480-6492, October.
    24. Zuoyufan Sheng & Chengpeng Zhu & Mo Chen, 2024. "Exploring the Impact of the Digital Economy on Green Total Factor Productivity—Evidence from Chinese Cities," Sustainability, MDPI, vol. 16(7), pages 1-13, March.
    25. Wang, Di & Zhou, Tao & Lan, Feng & Wang, Mengmeng, 2021. "ICT and socio-economic development: Evidence from a spatial panel data analysis in China," Telecommunications Policy, Elsevier, vol. 45(7).
    26. Rizvi, Syed Kumail Abbas & Rahat, Birjees & Naqvi, Bushra & Umar, Muhammad, 2024. "Revolutionizing finance: The synergy of fintech, digital adoption, and innovation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    27. Mansell, Robin, 2021. "Adjusting to the digital: societal outcomes and consequences," LSE Research Online Documents on Economics 111571, London School of Economics and Political Science, LSE Library.
    28. Zhang, Wenkang & Wu, Jing, 2025. "Endogenous growth and data heterogeneity in data economics," Finance Research Letters, Elsevier, vol. 78(C).
    29. Mansell, Robin, 2021. "Adjusting to the digital: Societal outcomes and consequences," Research Policy, Elsevier, vol. 50(9).
    30. Shah, Tushar R., 2022. "Can big data analytics help organisations achieve sustainable competitive advantage? A developmental enquiry," Technology in Society, Elsevier, vol. 68(C).
    31. Vito Maria Manfredi Latilla & Andrea Urbinati & Angelo Cavallo & Simone Franzò & Antonio Ghezzi, 2021. "Organizational Re-Design for Business Model Innovation while Exploiting Digital Technologies: A Single Case Study of an Energy Company," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 1-28, April.
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