IDEAS home Printed from https://ideas.repec.org/a/gam/jbusin/v2y2022i2p13-200d796482.html
   My bibliography  Save this article

The Change in the Traditional Paradigm of Production under the Influence of Industrial Revolution 4.0

Author

Listed:
  • Jan Rymarczyk

    (Poznan School of Banking, WSB Universities, 61-895 Poznan, Poland)

Abstract

The modern history of technical progress is relatively short, as it encompasses merely around 250 years. Within it, we can distinguish four time periods called industrial revolutions. The fourth one of these, which is currently ongoing, is characterized by such ground-breaking inventions as advanced robots, artificial intelligence, Internet of Things, 3D printing, automated guided vehicles, cloud technology, augmented reality, big data, blockchain, nanotechnology, and biotechnology. The author argues that under the influence of these inventions, industrial production is gradually becoming fully digitalized, automated, and autonomous. As a consequence, it will be carried out more speedily, flexibly, effectively, and transparently and will be more environmentally friendly. The quality of products will be higher and the costs of their manufacturing lower, and it will be strictly adjusted to the tastes of the consumers. This means that, contrary to the traditional view, represented by Porter, that companies at a given time can only use one of the basic strategies of competition, i.e., low cost, high quality, and market niche, they are able to implement production that meets all three criteria simultaneously. The emergence of the new production paradigm is stimulated by expected economic and environmental benefits as well as political, social, and natural factors, including the COVID-19 pandemic. These factors contribute to the breakdown of global supply chains, which causes a tendency to insourcing, which is conditioned by the implementation of intelligent production.

Suggested Citation

  • Jan Rymarczyk, 2022. "The Change in the Traditional Paradigm of Production under the Influence of Industrial Revolution 4.0," Businesses, MDPI, vol. 2(2), pages 1-13, April.
    • Handle: RePEc:gam:jbusin:v:2:y:2022:i:2:p:13-200:d:796482
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2673-7116/2/2/13/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2673-7116/2/2/13/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jason Furman & Robert Seamans, 2019. "AI and the Economy," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 161-191.
    2. Chen Liu, 2017. "International Competitiveness and the Fourth Industrial Revolution," Entrepreneurial Business and Economics Review, Centre for Strategic and International Entrepreneurship at the Cracow University of Economics., vol. 5(4), pages 111-133.
    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. Peace Y. L. Liu & James J. H. Liou & Sun-Weng Huang, 2023. "Exploring the Barriers to the Advancement of 3D Printing Technology," Mathematics, MDPI, vol. 11(14), pages 1-20, July.

    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. Shrutika Mishra & A. R. Tripathi, 2021. "AI business model: an integrative business approach," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-21, December.
    2. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    3. Mohsen Mohammadi Khyareh & Nasrin Rostami, 2022. "Macroeconomic Conditions, Innovation and Competitiveness," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(2), pages 1321-1340, June.
    4. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    5. Wang, Linhui & Wang, Hui & Cao, Zhanglu & He, Yongda & Dong, Zhiqing & Wang, Shixiang, 2022. "Can industrial intellectualization reduce carbon emissions? — Empirical evidence from the perspective of carbon total factor productivity in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    6. Dana-Teodora MIERLUȚ & Adriana GIURGIU & Horia-Octavian MINTAȘ & Adrian TUNDUC, 2022. "The Latest Crises Challenging The Eu`S Exports. Any Chances To Maintain The Competitiveness?," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 2(2), pages 176-187, December.
    7. Xiaoyi Li & Qibo Tian, 2023. "How Does Usage of Robot Affect Corporate Carbon Emissions?—Evidence from China’s Manufacturing Sector," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    8. Joel Klinger & Juan Mateos-Garcia & Konstantinos Stathoulopoulos, 2021. "Deep learning, deep change? Mapping the evolution and geography of a general purpose technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5589-5621, July.
    9. Bernardo S Buarque & Ronald B Davies & Ryan M Hynes & Dieter F Kogler, 2020. "OK Computer: the creation and integration of AI in Europe," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 175-192.
    10. Shiguang Li & Yixiang Tian, 2023. "How Does Digital Transformation Affect Total Factor Productivity: Firm-Level Evidence from China," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    11. Goodell, John W. & Corbet, Shaen & Yadav, Miklesh Prasad & Kumar, Satish & Sharma, Sudhi & Malik, Kunjana, 2022. "Time and frequency connectedness of green equity indices: Uncovering a socially important link to Bitcoin," International Review of Financial Analysis, Elsevier, vol. 84(C).
    12. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2021. "Threats and opportunities in the digital era: Automation spikes and employment dynamics," Research Policy, Elsevier, vol. 50(7).
    13. Manav Raj & Robert Seamans, 2019. "Primer on artificial intelligence and robotics," Journal of Organization Design, Springer;Organizational Design Community, vol. 8(1), pages 1-14, December.
    14. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    15. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
    16. Dirk Nicolas Wagner, 2020. "Economic patterns in a world with artificial intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 17(1), pages 111-131, January.
    17. Ke-Liang Wang & Ting-Ting Sun & Ru-Yu Xu, 2023. "The impact of artificial intelligence on total factor productivity: empirical evidence from China’s manufacturing enterprises," Economic Change and Restructuring, Springer, vol. 56(2), pages 1113-1146, April.
    18. Huang, Geng & He, Ling-Yun & Lin, Xi, 2022. "Robot adoption and energy performance: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 107(C).
    19. Duch-Brown, Néstor & Gomez-Herrera, Estrella & Mueller-Langer, Frank & Tolan, Songül, 2022. "Market power and artificial intelligence work on online labour markets," Research Policy, Elsevier, vol. 51(3).
    20. Ramona Tiganasu & Gabriela Carmen Pascariu & Dan Lupu, 2022. "Competitiveness, fiscal policy and corruption: evidence from Central and Eastern European countries," Oeconomia Copernicana, Institute of Economic Research, vol. 13(3), pages 667-698, September.

    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:jbusin:v:2:y:2022:i:2:p:13-200:d:796482. 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.