IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0308287.html

The impact of internet usage preferences on labor income: Evidence from China

Author

Listed:
  • Kefeng Yuan
  • Xiaoxia Zhang

Abstract

Background: The widespread application and iterative updating of computers and Internet communication technologies have not only increased productivity and enhanced intra- and inter-enterprise collaboration, but have also led to significant changes in the labor market and residents’ labor income. In the digital era, accepting digital technology and possessing a certain degree of digital literacy have become the necessary abilities for people to survive and develop. However, the differences in digital literacy caused by individual differences will inevitably bring about a series of chain reactions. Therefore, it is necessary to study the subtle impact of Internet usage preference on residents’ labor income in the context of digital transformation to promote digital equity. Objective: This study aims to empirically analyze micro-level survey data to reveal the impact of individual differences in internet usage preferences on their labor income. The findings provide theoretical references for government policy formulation and individual development. Methods: A function model was established to analyze the impact of individual internet usage preferences on labor income. Relevant data from the authoritative Chinese General Social Survey (CGSS2017) were selected, and empirical analyses for significance, heterogeneity, and robustness were conducted using the ZINB and CMP models in the Stata statistical software. Conclusion: (1) Higher Internet Usage Frequency (IUF) increases the likelihood of higher income. (2) Engaging in Online Social Networking (OSN) helps in accumulating social capital, leading to higher labor income. Meanwhile, participating in Online Entertainment (OE) relieves work and life stresses, thereby increasing labor income. Proficiency in Accessing Online Information (AOI) is associated with higher labor income, while frequent involvement in Online Business (OB) is correlated with higher personal income. Additionally, the Marginal utility of these internet usage preferences indicate that OB > AOI > OSN > OE. (3) Individual variations in physical, psychological, and social characteristics significantly influence the labor income effects of internet usage preferences. (4) There are substantial differences in the labor income effects of internet usage preferences between urban and rural areas and across different regions. (5) Education attainment has a positive mediating effect on the labour income effect of individual Internet use preferences, and enhancing residents’ digital literacy has a positive effect on increasing their labour income and alleviating inequality in digital gains. (6) The popularity of Internet technology is the background that triggers an individual’s Internet use, and the acceptance of a particular Internet technology is catalyzed by an individual’s perception of the value and difficulty of mastering that technology; an individual’s biased learning or proficiency in a particular Internet technology in order to gain higher competitiveness and value in the labour market is an important internal driving force.

Suggested Citation

  • Kefeng Yuan & Xiaoxia Zhang, 2024. "The impact of internet usage preferences on labor income: Evidence from China," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-25, August.
  • Handle: RePEc:plo:pone00:0308287
    DOI: 10.1371/journal.pone.0308287
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0308287
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0308287&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0308287?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
    ---><---

    References listed on IDEAS

    as
    1. Bauer, Johannes M., 2018. "The Internet and income inequality: Socio-economic challenges in a hyperconnected society," Telecommunications Policy, Elsevier, vol. 42(4), pages 333-343.
    2. Eric TC Lai & Ruby Yu & Jean Woo, 2020. "The Associations of Income, Education and Income Inequality and Subjective Well-Being among Elderly in Hong Kong—A Multilevel Analysis," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    3. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    4. Lex Borghans & Bas ter Weel, 2008. "Understanding the Technology of Computer Technology Diffusion: Explaining Computer Adoption Patterns and Implications for the Wage Structure," Journal of Income Distribution, Ad libros publications inc., vol. 17(3-4), pages 37-70, September.
    5. Miller, Paul & Mulvey, Charles, 1997. "Computer Skills and Wages," Australian Economic Papers, Wiley Blackwell, vol. 36(68), pages 106-113, June.
    6. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    7. Entorf, Horst & Kramarz, Francis, 1997. "Does unmeasured ability explain the higher wages of new technology workers?," European Economic Review, Elsevier, vol. 41(8), pages 1489-1509, August.
    8. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    Full references (including those not matched with items on IDEAS)

    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. Borghans, Lex & Weel, Bas ter, 2001. "What happens when agent T gets a computer?," Research Memorandum 017, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    2. Jurkat, Anne & Klump, Rainer & Schneider, Florian, 2025. "Robots and wages: A meta-analysis," Structural Change and Economic Dynamics, Elsevier, vol. 75(C), pages 541-567.
    3. Borghans, Lex & Weel, Bas ter, 2001. "What happens when agent T gets a computer?," Research Memorandum 017, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    4. Berg, Andrew & Buffie, Edward F. & Zanna, Luis-Felipe, 2018. "Should we fear the robot revolution? (The correct answer is yes)," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 117-148.
    5. Thanos Fragkandreas, 2022. "Three Decades of Research on Innovation and Inequality: Causal Scenarios, Explanatory Factors, and Suggestions," Working Papers 60, Birkbeck Centre for Innovation Management Research, revised Feb 2022.
    6. Theodore Koutmeridis, 2013. "The Market for "Rough Diamonds": Information, Finance and Wage Inequality," CDMA Working Paper Series 201307, Centre for Dynamic Macroeconomic Analysis, revised 14 Oct 2013.
    7. Pintera, Jan, 2025. "Skill-bias and wage inequality in the EU New Member States: Empirical investigation," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 761-791.
    8. Lex Borghans & Bas ter Weel, 2008. "Understanding the Technology of Computer Technology Diffusion: Explaining Computer Adoption Patterns and Implications for the Wage Structure," Journal of Income Distribution, Ad libros publications inc., vol. 17(3-4), pages 37-70, September.
    9. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    10. Jaewon Jung, 2024. "The Labor Market and Growth Implications of Skill Distribution: A Dynamic General Equilibrium Model with Skill Heterogeneity," Mathematics, MDPI, vol. 12(21), pages 1-22, October.
    11. Emilio Colombo & Alberto Marcato, 2021. "Skill Demand and Labour Market Concentration: Theory and Evidence from Italian Vacancies," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis2104, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
    12. Pi, Jiancai & Zhang, Pengqing, 2018. "Skill-biased technological change and wage inequality in developing countries," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 347-362.
    13. Riccardo Lucchetti & Stefano Staffolani & Alessandro Sterlacchini, 2004. "Computers, Wages and Working Hours in Italy," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 63(3-4), pages 329-353, December.
    14. Qiang Wu, 2025. "How Does AI Affect the Pay Gap Within Firms: Mechanism Analysis Based on Personnel Structure and Corporate Investment," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(2), pages 717-733, March.
    15. Tomas Havranek & Zuzana Irsova & Lubica Laslopova & Olesia Zeynalova, 2020. "Skilled and Unskilled Labor Are Less Substitutable than Commonly Thought," Working Papers IES 2020/29, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    16. Songul Tolan & Annarosa Pesole & Fernando Martinez-Plumed & Enrique Fernandez-Macias & José Hernandez-Orallo & Emilia Gomez, 2020. "Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks," JRC Working Papers on Labour, Education and Technology 2020-02, Joint Research Centre.
    17. repec:ecb:ecbwps:20141800 is not listed on IDEAS
    18. Lex Borghans & Bas ter Weel, 2011. "Computers, skills and wages," Applied Economics, Taylor & Francis Journals, vol. 43(29), pages 4607-4622.
    19. Naude, Wim & Nagler, Paula, 2015. "Industrialisation, Innovation, Inclusion," MERIT Working Papers 2015-043, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    20. Pauline Charnoz & Elise Coudin & Mathilde Gaini, 2014. "Forty Years of Decreasing Wage Inequality in France : The Role of Supply and Hidden Skill-Biased Technical Change," Working Papers 2014-20, Center for Research in Economics and Statistics.
    21. Tan, Joanne, 2024. "Multidimensional heterogeneity and matching in a frictional labor market — An application to polarization," Labour Economics, Elsevier, vol. 90(C).

    More about this item

    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:plo:pone00:0308287. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.