IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v90y2023ics1057521923004209.html
   My bibliography  Save this article

Corporate digital transformation and labor structure upgrading

Author

Listed:
  • Dou, Bin
  • Guo, SongLin
  • Chang, XiaoChen
  • Wang, Yong

Abstract

Corporate digital transformation aims to transform general-purpose technology into specific technology truly needed for development. Unlike informatisation related to business outsourcing, digitalisation needs professional labourers skilled in digital hardware and software, which means that the corporate digital transformation would promote the upgrade of the labour structure. This paper examines the financial and text data of annual reports of listed companies in China to test this theoretical hypothesis. We use word segmentation technology and word frequency statistical methods to construct corporate digital transformation indicators and empirically test corporate digital transformation's impact on labour force structure. The empirical outcomes indicate that corporate digital transformation has significantly increased the proportion of highly educated, highly skilled and research and development researchers. In this process, China's unique ‘engineer dividend’ can enhance the positive impact of digital transformation on upgrading the labour structure. The conclusion of this paper provides rich empirical evidence for accelerating the digital transformation and taking advantage of the engineer dividend in China.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:finana:v:90:y:2023:i:c:s1057521923004209
    DOI: 10.1016/j.irfa.2023.102904
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521923004209
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2023.102904?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. Gary S. Becker & Kevin M. Murphy & Robert Tamura, 1994. "Human Capital, Fertility, and Economic Growth," NBER Chapters, in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition, pages 323-350, National Bureau of Economic Research, Inc.
    3. 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.
    4. 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.
    5. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 339-376.
    6. Liu, Shasha & Zhao, Huixian & Kong, Gaowen, 2023. "Enterprise digital transformation, breadth of ownership and stock price volatility," International Review of Financial Analysis, Elsevier, vol. 89(C).
    7. 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.
    8. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    9. Dirk Krueger & Krishna B. Kumar, 2004. "Skill-Specific rather than General Education: A Reason for US--Europe Growth Differences?," Journal of Economic Growth, Springer, vol. 9(2), pages 167-207, June.
    10. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    11. 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.
    12. 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.
    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 & 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.
    15. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
    16. Claudia Goldin & Lawrence F. Katz, 1998. "The Origins of Technology-Skill Complementarity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 693-732.
    17. Li, Min & Liu, Na & Kou, Aiju & Chen, Wenchuan, 2023. "Customer concentration and digital transformation," International Review of Financial Analysis, Elsevier, vol. 89(C).
    18. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    19. Giovanni Cerulli & Marco Ventura, 2019. "Estimation of pre- and posttreatment average treatment effects with binary time-varying treatment using Stata," Stata Journal, StataCorp LP, vol. 19(3), pages 551-565, September.
    20. Bartel, Ann P & Lichtenberg, Frank R, 1987. "The Comparative Advantage of Educated Workers in Implementing New Technology," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 1-11, February.
    21. Kelvin K. F. Law & Lillian F. Mills, 2015. "Taxes and Financial Constraints: Evidence from Linguistic Cues," Journal of Accounting Research, Wiley Blackwell, vol. 53(4), pages 777-819, September.
    22. Kyle Handley & J. Frank Li, 2020. "Measuring the Effects of Firm Uncertainty on Economic Activity: New Evidence from One Million Documents," NBER Working Papers 27896, National Bureau of Economic Research, Inc.
    23. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei Jiang & Ling Yang & Tao Wang & John McCollough, 2024. "Research on the Impact of Trade Policy Uncertainty on the Digital Transformation of Chinese Export Firms," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(5), pages 1-11.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Maria-Chiara Morandini & Anna Thum-Thysen & Anneleen Vandeplas, 2020. "Facing the Digital Transformation: Are Digital Skills Enough?," European Economy - Economic Briefs 054, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    3. Ben Vermeulen & Jan Kesselhut & Andreas Pyka & Pier Paolo Saviotti, 2018. "The Impact of Automation on Employment: Just the Usual Structural Change?," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    4. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    5. Zilian, Laura S. & Zilian, Stella S. & Jäger, Georg, 2021. "Labour market polarisation revisited: evidence from Austrian vacancy data," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-7.
    6. Colombo, Emilio & Mercorio, Fabio & Mezzanzanica, Mario, 2019. "AI meets labor market: Exploring the link between automation and skills," Information Economics and Policy, Elsevier, vol. 47(C), pages 27-37.
    7. Lu, Jing & Xiao, Qinglan & Wang, Taoxuan, 2023. "Does the digital economy generate a gender dividend for female employment? Evidence from China," Telecommunications Policy, Elsevier, vol. 47(6).
    8. Cheng, Can & Luo, Jiayu & Zhu, Chun & Zhang, Shangfeng, 2024. "Artificial intelligence and the skill premium: A numerical analysis of theoretical models," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    9. Adriaan Zon & Roberto Antonietti, 2016. "Education and training in a model of endogenous growth with creative wear-and-tear," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(1), pages 35-62, April.
    10. Egana del Sol, Pablo, 2020. "The Future of Work in Developing Economies: What can we learn from the South?," GLO Discussion Paper Series 483, Global Labor Organization (GLO).
    11. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, Institute of Labor Economics (IZA).
    12. Jay Dixon & Bryan Hong & Lynn Wu, 2021. "The Robot Revolution: Managerial and Employment Consequences for Firms," Management Science, INFORMS, vol. 67(9), pages 5586-5605, September.
    13. Barbieri, Laura & Mussida, Chiara & Piva, Mariacristina & Vivarelli, Marco, 2019. "Testing the employment and skill impact of new technologies: A survey and some methodological issues," MERIT Working Papers 2019-032, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    14. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    15. Huajie Jiang & Qiguo Gong, 2022. "Does Skill Polarization Affect Wage Polarization? U.S. Evidence 2009–2021," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    16. Stefan Schweikl & Robert Obermaier, 2020. "Lessons from three decades of IT productivity research: towards a better understanding of IT-induced productivity effects," Management Review Quarterly, Springer, vol. 70(4), pages 461-507, November.
    17. Łukasz Arendt & Eugeniusz Kwiatkowski, 2023. "Kontrowersje wokół wpływu nowoczesnych technologii na zatrudnienie i bezrobocie," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 195-216.
    18. Crowley, Frank & Doran, Justin, 2019. "Automation and Irish Towns: Who's Most at Risk?," SRERC Working Paper Series SRERCWP2019-1, University College Cork (UCC), Spatial and Regional Economic Research Centre (SRERC).
    19. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    20. Alonso, Cristian & Berg, Andrew & Kothari, Siddharth & Papageorgiou, Chris & Rehman, Sidra, 2022. "Will the AI revolution cause a great divergence?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 18-37.

    More about this item

    Keywords

    Digital transformation; Labour force structure; Engineer dividend; Textual analysis;
    All these keywords.

    JEL classification:

    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finana:v:90:y:2023:i:c:s1057521923004209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.