IDEAS home Printed from https://ideas.repec.org/p/ipt/iptwpa/jrc139092.html
   My bibliography  Save this paper

Strategic Insights into the EU's Advanced Manufacturing Industry: Trends and Comparative Analysis

Author

Listed:

Abstract

The Advanced Manufacturing (ADMAN) study, launched in 2023, aims to support EU policymakers, industrial stakeholders, and Member States in assessing the performance of the advanced manufacturing industry in Europe and shaping EU industrial strategy. Focused on advanced technologies applied to manufacturing processes, the ADMAN study builds on the recommendations of the Industrial Forum’s Task Force on Advanced Manufacturing and aims at addressing existing data gaps by deploying a methodological approach that provides a comprehensive and comparative overview of the advanced manufacturing industry. This report describes the results of the study by DG GROW and JRC on advanced manufacturing worldwide, defining the metrics proposed to map the advanced manufacturing industry at global level as well as the main findings, with a special emphasis on the EU's position relative to global competitors. The report finds that the EU is a strong international advanced manufacturing player; however, it is increasingly under international competitive pressure. The ADMAM study includes also an online tool, allowing readers to further deep dive into the key findings of the report.

Suggested Citation

  • FABIANI Josefina & SOGUERO ESCUER Jorge & CALZA Elisa & DUNKER Cesare & DE PRATO Giuditta, 2024. "Strategic Insights into the EU's Advanced Manufacturing Industry: Trends and Comparative Analysis," JRC Research Reports JRC139092, Joint Research Centre.
    • Handle: RePEc:ipt:iptwpa:jrc139092
    as

    Download full text from publisher

    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC139092
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Zhiyuan & Zhang, Jie, 2019. "Types of patents and driving forces behind the patent growth in China," Economic Modelling, Elsevier, vol. 80(C), pages 294-302.
    2. Righi, Riccardo & Samoili, Sofia & López Cobo, Montserrat & Vázquez-Prada Baillet, Miguel & Cardona, Melisande & De Prato, Giuditta, 2020. "The AI techno-economic complex System: Worldwide landscape, thematic subdomains and technological collaborations," Telecommunications Policy, Elsevier, vol. 44(6).
    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. Zhangsheng Liu & Liuqingqing Yang & Liqin Fan, 2021. "Induced Effect of Environmental Regulation on Green Innovation: Evidence from the Increasing-Block Pricing Scheme," IJERPH, MDPI, vol. 18(5), pages 1-15, March.
    2. Mendonça, Sandro & Damásio, Bruno & Charlita de Freitas, Luciano & Oliveira, Luís & Cichy, Marcin & Nicita, António, 2022. "The rise of 5G technologies and systems: A quantitative analysis of knowledge production," Telecommunications Policy, Elsevier, vol. 46(4).
    3. Wen Yue, 2022. "Foreign direct investment and the innovation performance of local enterprises," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    4. Ma, Ding & Yu, Qian & Li, Jing & Ge, Mengni, 2021. "Innovation diffusion enabler or barrier: An investigation of international patenting based on temporal exponential random graph models," Technology in Society, Elsevier, vol. 64(C).
    5. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    6. Julius Tan Gonzales, 2023. "Implications of AI innovation on economic growth: a panel data study," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-37, December.
    7. Jingwen Sun & Jie Zhang, 2024. "Digital Financial Inclusion and Innovation of MSMEs," Sustainability, MDPI, vol. 16(4), pages 1-18, February.
    8. David Karpa & Torben Klarl & Michael Rochlitz, 2021. "Artificial Intelligence, Surveillance, and Big Data," Papers 2111.00992, arXiv.org.
    9. Stephany, Fabian & Teutloff, Ole, 2024. "What is the price of a skill? The value of complementarity," Research Policy, Elsevier, vol. 53(1).
    10. Hong-Wen Tsai & Hui-Chung Che, 2023. "Industry Difference on Patent Drawing’s Capability for Differentiating Stock Rates of Return of Chinese Listed Companies in Non-Manufacturing Industry Sectors -- An Explore into Invention Publication ," Bulletin of Applied Economics, Risk Market Journals, vol. 10(1), pages 21-67.
    11. Yanyang Yan & Juan Wang & Sijia Qiao, 2022. "Effects of Industrial Policy on Firms’ Innovation Outputs: Evidence From China," SAGE Open, , vol. 12(3), pages 21582440221, September.
    12. Dai, Shangze & Fan, Fei & Zhang, Keke, 2022. "Creative Destruction and Stock Price Informativeness in Emerging Economies," MPRA Paper 113661, University Library of Munich, Germany.
    13. Anabela Marques Santos & Francesco Molica & Carlos Torrecilla Salinas, 2024. "EU-funded investment in Artificial Intelligence and regional specialization," GEE Papers 181, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Jul 2024.
    14. 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).
    15. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    16. Boeing, Philipp & Mueller, Elisabeth, 2019. "Measuring China's patent quality: Development and validation of ISR indices," China Economic Review, Elsevier, vol. 57(C).
    17. Cai, Helen (Huifen) & Sarpong, David & Tang, Xiaoyun & Zhao, Guiqin, 2020. "Foreign patents surge and technology spillovers in China (1985–2009): Evidence from the patent and trade markets," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    18. Matheus E. Leusin & Bjoern Jindra & Daniel S. Hain, 2021. "An evolutionary view on the emergence of Artificial Intelligence," Papers 2102.00233, arXiv.org.
    19. Thomas Scherngell & Charlotte Rohde & Martina Neuländtner, 2020. "The dynamics of global R&D collaboration networks in ICT: Does China catch up with the US?," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-17, September.
    20. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(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:ipt:iptwpa:jrc139092. 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: Publication Officer (email available below). General contact details of provider: https://edirc.repec.org/data/ipjrces.html .

    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.