IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i3p1341-d1333745.html
   My bibliography  Save this article

Impact of Artificial Intelligence on Manufacturing Industry Global Value Chain Position

Author

Listed:
  • Jun Liu

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
    School of Digital Economics and Management, Wuxi University, Wuxi 214105, China)

  • Xin Jiang

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Mengxue Shi

    (Bank of Suzhou Co., Ltd., Suzhou 215028, China)

  • Yuning Yang

    (School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China)

Abstract

Using transnational panel data from 61 nations and regions from 2000 to 2019, this article empirically examines both the influence of artificial intelligence on the Global Value Chain as it pertains to the manufacturing industry and its mechanism of action. According to the report, AI significantly improves the industrial sector’s GVC position; this finding still holds after multiple robustness and endogeneity tests of the model. The findings of the heterogeneity test at the national level demonstrate that, in developing nations as opposed to developed countries, AI has a stronger impact on advancing the GVC position of the manufacturing industry. Heterogeneity tests at the industry level show that AI has a significant role in promoting the GVC of high, medium and low technology manufacturing industries. The mechanism test demonstrates three primary ways by which AI contributes to improving the GVC position of the manufacturing industry: by improving both production efficiency and technological innovation capacity, and by reducing trade costs. This study provides policy implications for the promotion of AI with respect to China’s manufacturing industry GVC position.

Suggested Citation

  • Jun Liu & Xin Jiang & Mengxue Shi & Yuning Yang, 2024. "Impact of Artificial Intelligence on Manufacturing Industry Global Value Chain Position," Sustainability, MDPI, vol. 16(3), pages 1-17, February.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1341-:d:1333745
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/3/1341/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/3/1341/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Katharine G. Abraham & Justine Mallatt, 2022. "Measuring Human Capital," Journal of Economic Perspectives, American Economic Association, vol. 36(3), pages 103-130, Summer.
    2. Keun Lee & Franco Malerba & Annalisa Primi, 2020. "The fourth industrial revolution, changing global value chains and industrial upgrading in emerging economies," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 23(4), pages 359-370, October.
    3. Cédric Durand & Wiliiam Milberg, 2020. "Intellectual monopoly in global value chains," Review of International Political Economy, Taylor & Francis Journals, vol. 27(2), pages 404-429, March.
    4. Federico Carril‐Caccia & Elena Pavlova, 2020. "Mergers and acquisitions & trade: A global value chain analysis," The World Economy, Wiley Blackwell, vol. 43(3), pages 586-614, March.
    5. Amat Adarov & Robert Stehrer, 2021. "Implications of foreign direct investment, capital formation and its structure for global value chains," The World Economy, Wiley Blackwell, vol. 44(11), pages 3246-3299, November.
    6. 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.
    7. Dai, Feng & Liu, Ruixiang & Guo, Hao & Du, Xiuhong, 2020. "How does intermediate consumption affect GVC positions? - A comparison between China and US," China Economic Review, Elsevier, vol. 63(C).
    8. Karishma Banga, 2019. "Digital technologies and 'value' capture in global value chains: Empirical evidence from Indian manufacturing firms," WIDER Working Paper Series wp-2019-43, World Institute for Development Economic Research (UNU-WIDER).
    9. Vlačić, Ernest & Dabić, Marina & Daim, Tugrul & Vlajčić, Davor, 2019. "Exploring the impact of the level of absorptive capacity in technology development firms," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 166-177.
    10. Stefan Pahl & Marcel P. Timmer, 2020. "Do Global Value Chains Enhance Economic Upgrading? A Long View," Journal of Development Studies, Taylor & Francis Journals, vol. 56(9), pages 1683-1705, July.
    11. Sabina Szymczak & Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2022. "Position in global value chains and wages in Central and Eastern European countries," European Journal of Industrial Relations, , vol. 28(2), pages 211-230, June.
    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. Lorenzo Cresti & Maria Enrica Virgillito, 2023. "Weak sectors and weak ties? Labour dependence and asymmetric positioning in GVCs," LEM Papers Series 2023/10, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. 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.
    3. Parteka, Aleksandra & Wolszczak-Derlacz, Joanna & Nikulin, Dagmara, 2024. "How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    4. repec:gdk:wpaper:69 is not listed on IDEAS
    5. Tsakanikas, Aggelos & Roth, Felix & Caliò, Simone & Caloghirou, Yannis & Dimas, Petros, 2020. "The contribution of intangible inputs and participation in global value chains to productivity performance – Evidence from the EU-28, 2000-2014," Hamburg Discussion Papers in International Economics 5, University of Hamburg, Department of Economics.
    6. Stojčić, Nebojša & Matić, Matija, 2024. "A journey toward global value chain upgrading: Exploring the transition from backward to forward integration," Technology in Society, Elsevier, vol. 76(C).
    7. Carlo Pietrobelli & Roberta Rabellotti & Ari Van Assche, 2021. "Making sense of global value chain-oriented policies: The trifecta of tasks, linkages, and firms," Journal of International Business Policy, Palgrave Macmillan, vol. 4(3), pages 327-346, September.
    8. Marek Pekarčík & Júlia Ďurčová & Jozef Glova, 2022. "Intangible ICT and Their Importance within Global Value Chains: An Empirical Analysis Based on Longitudinal Data Regression," Mathematics, MDPI, vol. 10(7), pages 1-14, April.
    9. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    10. Matteo G. Richiardi & Luis Valenzuela, 2024. "Firm heterogeneity and the aggregate labour share," LABOUR, CEIS, vol. 38(1), pages 66-101, March.
    11. Gideon Ndubuisi & Solomon Owusu, 2021. "How important is GVC participation to export upgrading?," The World Economy, Wiley Blackwell, vol. 44(10), pages 2887-2908, October.
    12. Huang, Siyu & Shi, Yi & Chen, Qinghua & Li, Xiaomeng, 2022. "The growth path of high-tech industries: Statistical laws and evolution demands," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    13. Hammoudeh, Shawkat & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adeabah, David, 2023. "Global value chains in sub-Saharan Africa: The role of business regulations, policies and institutions," Emerging Markets Review, Elsevier, vol. 57(C).
    14. Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
    15. Joel Rabinovich & Niall Reddy, 2024. "Corporate Financialization: A Conceptual Clarification and Critical Review of the Literature," Working Papers PKWP2402, Post Keynesian Economics Society (PKES).
    16. Enrico Sergio Levrero & Giacomo Sbrenna, 2022. "Some Factors Affecting US Capital Profitability over the Last Decades," Bulletin of Political Economy, Bulletin of Political Economy, vol. 16(2), pages 77-101, December.
    17. Sharon Belenzon & Victor Manuel Bennett & Andrea Patacconi, 2019. "Flexible Production and Entry: Institutional, Technological, and Organizational Determinants," Strategy Science, INFORMS, vol. 4(3), pages 193-216, September.
    18. Burkhard Heer & Andreas Irmen & Bernd Süssmuth, 2023. "Explaining the decline in the US labor share: taxation and automation," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(6), pages 1481-1528, December.
    19. Bağış, Mehmet & Kryeziu, Liridon & Akbaba, Yılmaz & Ramadani, Veland & Karagüzel, Ensar Selman & Krasniqi, Besnik A., 2022. "The micro-foundations of a dynamic technological capability in the automotive industry," Technology in Society, Elsevier, vol. 70(C).
    20. David Kunst, 2019. "Deskilling among Manufacturing Production Workers," Tinbergen Institute Discussion Papers 19-050/VI, Tinbergen Institute, revised 30 Dec 2020.
    21. Dilip Mookherjee & Debraj Ray, 2022. "Growth, Automation and the Long-Run Share of Labor," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 46, pages 1-26, October.

    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:gam:jsusta:v:16:y:2024:i:3:p:1341-:d:1333745. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.