IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v197y2023ics0040162523005668.html
   My bibliography  Save this article

The impact of the artificial intelligence industry on the number and structure of employments in the digital economy environment

Author

Listed:
  • Zhang, Zhuo

Abstract

This study endeavors to examine the intricate impact of the industries related to artificial intelligence (AI) on both the quantity of labor employment in terms of quantity and the evolving structure of the job market. The study constructs a mechanism and theoretical model to elucidate labor employment dynamics and structural transformations within the AI industry. The research findings reveal discernible trend in China's labor force characterized by a heightened emphasis on education and increased employment opportunities. This study makes a substantial contribution to the field by constructing innovative mechanisms and theoretical frameworks that facilitate a profound comprehension of the intricacies surrounding labor employment and structural changes in the AI industry. This comprehension is grounded in an analysis of the prevailing employment quantity and structure. This study is underpinned by an examination of employment distribution across diverse industries and a meticulous analysis of the workforce's skill diversity. By thoroughly analyzing China's digital economy policies and the strides made in digital technologies, the study formulates a set of recommendations aimed at fostering national economic growth and achieving successful digital transformation. The primary innovation of this study resides in its exploration of the impact of the AI industry with respect to China's labor employment structure through the lens of a Marxist theoretical perspective. Consequently, the study extends both innovative significance and practical value.

Suggested Citation

  • Zhang, Zhuo, 2023. "The impact of the artificial intelligence industry on the number and structure of employments in the digital economy environment," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:tefoso:v:197:y:2023:i:c:s0040162523005668
    DOI: 10.1016/j.techfore.2023.122881
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523005668
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122881?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. Kim, Sehoon & Connerton, Timothy Paul & Park, Cheongyeul, 2021. "Exploring the impact of technological disruptions in the automotive retail: A futures studies and systems thinking approach based on causal layered analysis and causal loop diagram," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    2. Paola Tubaro & Antonio A. Casilli & Marion Coville, 2020. "The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence," Post-Print hal-02554196, HAL.
    3. Kevin Jan DUFFY & Obiora Cornelius COLLINS & Thokozani SIMELANE, 2022. "System Dynamics Model Linking Demand, Employment Movement Between Sectors And The Economy For The South African Construction Sector," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 17(2), pages 5-15, May.
    4. Yu Chen & Scott Jensen & Leslie J. Albert & Sambhav Gupta & Terri Lee, 2023. "Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success," Information Systems Frontiers, Springer, vol. 25(1), pages 161-182, February.
    5. Singh, Shiwangi & Dhir, Sanjay & Das, V. Mukunda & Sharma, Anuj, 2020. "Bibliometric overview of the Technological Forecasting and Social Change journal: Analysis from 1970 to 2018," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    6. Novakova, Lucia, 2020. "The impact of technology development on the future of the labour market in the Slovak Republic," Technology in Society, Elsevier, vol. 62(C).
    7. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    8. Ma, Hongmei & Gao, Qian & Li, Xiuzhen & Zhang, Yun, 2022. "AI development and employment skill structure: A case study of China," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 242-254.
    9. Jung, Jin Hwa & Lim, Dong-Geon, 2020. "Industrial robots, employment growth, and labor cost: A simultaneous equation analysis," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    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. Song, Malin & Pan, Heting & Shen, Zhiyang & Tamayo-Verleene, Kristine, 2024. "Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value," Energy Economics, Elsevier, vol. 131(C).
    2. Jing Wang & Zhanggong Tian & Yi Sun, 2024. "Digital Economy, Employment Structure and Labor Share," Sustainability, MDPI, vol. 16(21), pages 1-16, November.
    3. Jin, Xing & Lyu, Kangyin, 2024. "The impact of digital economy on emerging employment trends: Insights from the China Family Panel Survey (CFPS)," Finance Research Letters, Elsevier, vol. 64(C).

    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. Yang Shen, 2024. "Future jobs: analyzing the impact of artificial intelligence on employment and its mechanisms," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-33, April.
    2. 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).
    3. 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).
    4. Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
    5. Du, Longzheng & Lin, Weifen, 2022. "Does the application of industrial robots overcome the Solow paradox? Evidence from China," Technology in Society, Elsevier, vol. 68(C).
    6. Dario Guarascio & Alessandro Piccirillo & Jelena Reljic, 2024. "Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis," LEM Papers Series 2024/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Xianpu Xu & Yuchen Song, 2023. "Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
    8. Ayhan, Fatih & Elal, Onuray, 2023. "The IMPACTS of technological change on employment: Evidence from OECD countries with panel data analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    9. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    10. Das, Kallol & Patel, Jayesh D. & Sharma, Anuj & Shukla, Yupal, 2023. "Creativity in marketing: Examining the intellectual structure using scientometric analysis and topic modeling," Journal of Business Research, Elsevier, vol. 154(C).
    11. Silvia Vannutelli & Sergio Scicchitano & Marco Biagetti, 2022. "Routine-biased technological change and wage inequality: do workers’ perceptions matter?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 409-450, September.
    12. Ghannouchi, Imen, 2023. "Examining the dynamic nexus between industry 4.0 technologies and sustainable economy: New insights from empirical evidence using GMM estimator across 20 OECD nations," Technology in Society, Elsevier, vol. 75(C).
    13. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    14. Ayat Sami ODEIBAT, 2021. "The Effect Of Technology Evolution On The Future Of Jobs," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 17, pages 57-67, June.
    15. Mirzaei Abbasabadi, Hamed & Soleimani, Mohammad, 2021. "Examining the effects of digital technology expansion on Unemployment: A cross-sectional investigation," Technology in Society, Elsevier, vol. 64(C).
    16. Vujović, Vuk & Denić, Nebojša & Stevanović, Vesna & Stevanović, Mališa & Stojanović, Jelena & Cao, Yan & Alhammadi, Yasir & Jermsittiparsert, Kittisak & Van Le, Hiep & Wakil, Karzan & Radojkovic, Ivan, 2020. "Project planning and risk management as a success factor for IT projects in agricultural schools in Serbia," Technology in Society, Elsevier, vol. 63(C).
    17. Grohmann, Rafael & Pereira, Gabriel & Guerra, Abel & Abilio, Ludmila Costhek & Moreschi, Bruno & Jurno, Amanda, 2022. "Platform scams: Brazilian workers’ experiences of dishonest and uncertain algorithmic management," LSE Research Online Documents on Economics 115622, London School of Economics and Political Science, LSE Library.
    18. Tubaro, Paola & Coville, Marion & Le Ludec, Clément & Casilli, Antonio A., 2022. "Hidden inequalities: The gendered labour of women on micro-tasking platforms," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 11(1), pages 1-26.
    19. Grinin, Leonid & Grinin, Anton & Korotayev, Andrey, 2022. "COVID-19 pandemic as a trigger for the acceleration of the cybernetic revolution, transition from e-government to e-state, and change in social relations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    20. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

    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:tefoso:v:197:y:2023:i:c:s0040162523005668. 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.sciencedirect.com/science/journal/00401625 .

    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.