IDEAS home Printed from https://ideas.repec.org/p/mod/depeco/0151.html
   My bibliography  Save this paper

Digital transformation in the automotive supply chain: China, Germany, Italy and Japan in a comparative perspective

Author

Listed:
  • Margherita Russo

Abstract

A wide literature on digital transformation in manufacturing and services has explored its impact on long term changes in labour demand and skills and on productivity and growth. A new perspective on the ongoing digital transformation has been prompted by Oecd to highlight specific metrics needed to assess its impact on the economy and society and to support innovation policies. Drawing on these contributions, this paper aims to shed light on the impact of digital transformation on the reorganization and relocation of the various segments of the automotive supply chain. In particular, it will focus on the effects generated by different paces of adoption of digital technologies in this supply chain, with regard to both the various segments and the various sizes of companies, in different countries. The causes of this heterogeneity will be discussed and the implications for the full impact of the ongoing transformation will be considered in relation to industrial and innovation policy in Europe. The paper addresses the issue by reviewing empirical evidence on the automotive supply chain, which includes the most advanced manufacturing and service companies that are now adopting digital technologies. Evidence from case studies in the automotive industry in China, Germany, Italy and Japan will help in identifying the main challenges of digital transformation for European countries, which will involve a strongly interrelated supply chain both within and outside Europe.

Suggested Citation

  • Margherita Russo, 2019. "Digital transformation in the automotive supply chain: China, Germany, Italy and Japan in a comparative perspective," Department of Economics 0151, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    • Handle: RePEc:mod:depeco:0151
    as

    Download full text from publisher

    File URL: http://155.185.68.2/wpdemb/0151.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rosenberg, Nathan, 1963. "Technological Change in the Machine Tool Industry, 1840–1910," The Journal of Economic History, Cambridge University Press, vol. 23(4), pages 414-443, December.
    2. David J. TEECE, 2008. "Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy," World Scientific Book Chapters, in: The Transfer And Licensing Of Know-How And Intellectual Property Understanding the Multinational Enterprise in the Modern World, chapter 5, pages 67-87, World Scientific Publishing Co. Pte. Ltd..
    3. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, March.
    4. Annamaria Simonazzi & Andrea Ginzburg & Gianluigi Nocella, 2013. "Economic relations between Germany and southern Europe," Cambridge Journal of Economics, Oxford University Press, vol. 37(3), pages 653-675.
    5. Yongxin Liao & Fernando Deschamps & Eduardo de Freitas Rocha Loures & Luiz Felipe Pierin Ramos, 2017. "Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal," International Journal of Production Research, Taylor & Francis Journals, vol. 55(12), pages 3609-3629, June.
    6. Alessia Amighini & Sara Gorgoni, 2014. "The International Reorganisation of Auto Production," The World Economy, Wiley Blackwell, vol. 37(7), pages 923-952, July.
    7. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, December.
    8. Chuah,Lay Lian & Loayza,Norman V. & Schmillen,Achim Daniel, 2018. "The Future of Work : Race with-not against-the Machine," Research and Policy Briefs 129680, The World Bank.
    9. MOTOHASHI Kazuyuki, 2017. "Survey of Big Data Use and Innovation in Japanese Manufacturing Firms," Policy Discussion Papers 17027, Research Institute of Economy, Trade and Industry (RIETI).
    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. Jorge Carreto Sanginés & Pasquale Pavone & Margherita Russo & Annamaria Simonazzi, 2019. "Digital upgrade in the automotive supply chain in Mexico: issues and challenges," Department of Economics 0153, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".

    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. Simone Vannuccini & Ekaterina Prytkova, 2021. "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series 2021-02, SPRU - Science Policy Research Unit, University of Sussex Business School.
    2. Mario Benassi & Elena Grinza & Francesco Rentocchini, 2020. "The rush for patents in the Fourth Industrial Revolution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(4), pages 559-588, December.
    3. Colin Wessendorf & Alexander Kopka & Dirk Fornahl, 2021. "The impact of the six European Key Enabling Technologies (KETs) on regional knowledge creation," Papers in Evolutionary Economic Geography (PEEG) 2127, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2021.
    4. Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113, October.
    5. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    6. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
    7. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    8. DUERNECKER Georg & SANCHEZ MARTINEZ Miguel, 2021. "Structural change and productivity growth in the European Union: Past, present and future," JRC Working Papers on Territorial Modelling and Analysis 2021-09, Joint Research Centre.
    9. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    10. Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2022. "Urban economics in a historical perspective: Recovering data with machine learning," Regional Science and Urban Economics, Elsevier, vol. 94(C).
    11. Vasiliki Koniakou, 2023. "From the “rush to ethics” to the “race for governance” in Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(1), pages 71-102, February.
    12. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
    13. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    14. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    15. Mario Benassi & Elena Grinza & Francesco Rentocchini & Laura Rondi, 2022. "Patenting in 4IR technologies and firm performance [Robots and jobs: evidence from US labor markets]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(1), pages 112-136.
    16. Charles M. A. Clark & Aleksandr V. Gevorkyan, 2020. "Artificial Intelligence and Human Flourishing," American Journal of Economics and Sociology, Wiley Blackwell, vol. 79(4), pages 1307-1344, September.
    17. Nicholas Crafts, 2022. "Slow real wage growth during the Industrial Revolution: productivity paradox or pro-rich growth? [Engels’ pause: technical change, capital accumulation, and inequality in the British industrial rev," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 1-13.
    18. Selale Tuzel & Miao Ben Zhang, 2021. "Economic Stimulus at the Expense of Routine‐Task Jobs," Journal of Finance, American Finance Association, vol. 76(6), pages 3347-3399, December.
    19. Bart van Ark & Anthony J. Venables, 2020. "A Concerted Effort to Tackle the UK Productivity Puzzle," International Productivity Monitor, Centre for the Study of Living Standards, vol. 39, pages 3-15, Fall.
    20. Yuki, Kazuhiro, 2012. "Mechanization, task assignment, and inequality," MPRA Paper 37754, University Library of Munich, Germany.

    More about this item

    Keywords

    digital transformation; automotive global supply chain; China; Germany Italy; Japan;
    All these keywords.

    JEL classification:

    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    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:mod:depeco:0151. 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: Sara Colombini (email available below). General contact details of provider: https://edirc.repec.org/data/demodit.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.