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The impact of digital transformation on labour demand quantity and structure: Evidence from China

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  • Qin, Shuyuan
  • Liu, Ziqi
  • Wang, Jie
  • Wu, Yongqiu

Abstract

While the impact of digital transformation on firms’ labour demand has attracted considerable attention, no studies have examined how different types of digital transformation impact different workforce labour demand. Using data from Chinese A-share listed manufacturing companies from 2013 to 2022, this study employs a two-way fixed effects model, the instrumental variable method and multi-temporal difference-in-differences analysis. The findings reveal that digital convergence technologies significantly increase manufacturing firms’ labour demand, whereas e-commerce technologies have no significant effect on employment. Furthermore, digitalisation has a negative effect on the demand for operational employees and a positive effect on the demand for skilled and service employees. The mechanism test reveals that digital transformation primarily substitutes labour through productivity effects and generates labour demand via financing constraints and business scope effects, ultimately increasing manufacturing firms’ labour demand. These results further enhance the understanding of how digital technology development impacts labour demand.

Suggested Citation

  • Qin, Shuyuan & Liu, Ziqi & Wang, Jie & Wu, Yongqiu, 2024. "The impact of digital transformation on labour demand quantity and structure: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1452-1469.
    • Handle: RePEc:eee:ecanpo:v:84:y:2024:i:c:p:1452-1469
    DOI: 10.1016/j.eap.2024.10.036
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    as
    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. Ying Wu & Yuanyue Deng, 2024. "Does digital transformation crowd out the employment of lower skill labor?," Bulletin of Economic Research, Wiley Blackwell, vol. 76(3), pages 726-748, July.
    3. David A. Matsa, 2018. "Capital Structure and a Firm's Workforce," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 387-412, November.
    4. Hess, Thomas & Matt, Christian & Benlian, Alexander & Wiesböck, Florian, 2016. "Options for Formulating a Digital Transformation Strategy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 81032, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Jiatong Yu & Jiajue Wang & Taesoo Moon, 2022. "Influence of Digital Transformation Capability on Operational Performance," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    6. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    7. Zhang, Chuan & Liu, Lixia, 2023. "Corporate inventory and cash holdings in digital economy strategy: Evidence from China," Finance Research Letters, Elsevier, vol. 53(C).
    8. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    9. Daron Acemoglu & Pascual Restrepo, 2017. "Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation," American Economic Review, American Economic Association, vol. 107(5), pages 174-179, May.
    10. Niu, Yuhao & Wen, Wen & Wang, Sai & Li, Sifei, 2023. "Breaking barriers to innovation: The power of digital transformation," Finance Research Letters, Elsevier, vol. 51(C).
    11. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    12. Fabien Postel-Vinay, 2002. "The Dynamics of Technological Unemployment," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(3), pages 737-760, August.
    13. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    14. Daron Acemoglu & Ufuk Akcigit & Harun Alp & Nicholas Bloom & William Kerr, 2018. "Innovation, Reallocation, and Growth," American Economic Review, American Economic Association, vol. 108(11), pages 3450-3491, November.
    15. 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.
    16. repec:eme:reps00:reps-11-2019-0145 is not listed on IDEAS
    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. Ricarda B. Bouncken & Sascha Kraus & Norat Roig-Tierno, 2021. "Knowledge- and innovation-based business models for future growth: digitalized business models and portfolio considerations," Review of Managerial Science, Springer, vol. 15(1), pages 1-14, January.
    19. Nicole Maestas & Kathleen J. Mullen & David Powell, 2023. "The Effect of Population Aging on Economic Growth, the Labor Force, and Productivity," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 306-332, April.
    20. Liu, Guangqiang & Wang, Shenghua, 2023. "Digital transformation and trade credit provision: Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
    21. Masahina Sarabdeen & Hind Alofaysan, 2023. "Investigating the Impact of Digital Transformation on the Labor Market in the Era of Changing Digital Transformation Dynamics in Saudi Arabia," Economies, MDPI, vol. 11(1), pages 1-14, January.
    22. Dou, Bin & Guo, SongLin & Chang, XiaoChen & Wang, Yong, 2023. "Corporate digital transformation and labor structure upgrading," International Review of Financial Analysis, Elsevier, vol. 90(C).
    23. Li, Feng, 2020. "The digital transformation of business models in the creative industries: A holistic framework and emerging trends," Technovation, Elsevier, vol. 92.
    24. Marco Savastano & Carlo Amendola & Francesco Bellini & Fabrizio D’Ascenzo, 2019. "Contextual Impacts on Industrial Processes Brought by the Digital Transformation of Manufacturing: A Systematic Review," Sustainability, MDPI, vol. 11(3), pages 1-38, February.
    25. Hess, Thomas & Matt, Christian & Benlian, Alexander & Wiesböck, Florian, 2016. "Options for Formulating a Digital Transformation Strategy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 82423, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    26. Ramos, Minerva E. & Garza-Rodríguez, Jorge & Gibaja-Romero, Damian E., 2022. "Automation of employment in the presence of industry 4.0: The case of Mexico," Technology in Society, Elsevier, vol. 68(C).
    27. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    28. Nathan Nunn & Nancy Qian, 2014. "US Food Aid and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1630-1666, June.
    29. Han, Yue & Yang, Jie & Ying, Limeng & Niu, Yanfang, 2024. "The impact of corporate digital transformation on labor employment," Finance Research Letters, Elsevier, vol. 60(C).
    30. Li, Wencong & Yang, Xingquan & Yin, Xingqiang, 2024. "Digital transformation and labor upgrading," Pacific-Basin Finance Journal, Elsevier, vol. 83(C).
    31. Heidi Aly, 2020. "Digital transformation, development and productivity in developing countries: is artificial intelligence a curse or a blessing?," Review of Economics and Political Science, Emerald Group Publishing Limited, vol. 7(4), pages 238-256, May.
    32. Feng, Rui & Shen, Chen & Guo, Yiyang, 2024. "Digital finance and labor demand of manufacturing enterprises: Theoretical mechanism and heterogeneity analysis," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 17-32.
    33. Su, Chi-Wei & Yuan, Xi & Umar, Muhammad & Lobonţ, Oana-Ramona, 2022. "Does technological innovation bring destruction or creation to the labor market?," Technology in Society, Elsevier, vol. 68(C).
    34. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    35. Debao Dai & Shengnan Han & Min Zhao & Jiaping Xie, 2023. "The Impact Mechanism of Digital Transformation on the Risk-Taking Level of Chinese Listed Companies," Sustainability, MDPI, vol. 15(3), pages 1-20, January.
    36. Zhai, Huayun & Yang, Min & Chan, Kam C., 2022. "Does digital transformation enhance a firm's performance? Evidence from China," Technology in Society, Elsevier, vol. 68(C).
    37. Ryan Michaels & T Beau Page & Toni M Whited, 2019. "Labor and Capital Dynamics under Financing Frictions," Review of Finance, European Finance Association, vol. 23(2), pages 279-323.
    38. Janet Bercovitz & Will Mitchell, 2007. "When is more better? The impact of business scale and scope on long‐term business survival, while controlling for profitability," Strategic Management Journal, Wiley Blackwell, vol. 28(1), pages 61-79, January.
    39. Yituan Liu & Yabin Bian & Wenhao Zhang, 2022. "How Does Enterprises’ Digital Transformation Impact the Educational Structure of Employees? Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-25, August.
    40. Edwin Juma Omol, 2023. "Organizational digital transformation: from evolution to future trends," Digital Transformation and Society, Emerald Group Publishing Limited, vol. 3(3), pages 240-256, December.
    41. Gaglio, Cyrielle & Kraemer-Mbula, Erika & Lorenz, Edward, 2022. "The effects of digital transformation on innovation and productivity: Firm-level evidence of South African manufacturing micro and small enterprises," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    42. Yan Zou & Qinghui Bai & Daqing Gong, 2022. "The Impact of Dividend Policies and Financing Strategies on the Speed of Firms’ Capital Structure Adjustment," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-12, February.
    43. Hu, Yan & Che, Dexin & Wu, Fei & Chang, Xi, 2023. "Corporate maturity mismatch and enterprise digital transformation: Evidence from China," Finance Research Letters, Elsevier, vol. 53(C).
    44. Steven N. Kaplan & Luigi Zingales, 1997. "Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 169-215.
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