IDEAS home Printed from https://ideas.repec.org/a/oup/ecpoli/v34y2019i100p691-722..html
   My bibliography  Save this article

Automation, performance and international competition: a firm-level comparison of process innovation

Author

Listed:
  • Lene Kromann
  • Anders Sørensen

Abstract

SUMMARYThe automation of production processes is an important topic on the policy agenda in high-wage countries, and Denmark is no exception. However, the knowledge of the adoption of automation technologies across firms, of drivers of investments in automation, and on the association between automation and firm performance are limited. This paper uses a new survey to collect data on automation combined with register data to examine these issues. The variation in the adoption of automation technologies is high but the change in adoption over time is slow, and almost half of Danish manufacturing firms relied greatly on manual production processes in 2010. Increasing international competition from China is a driver for investments in automation, i.e. the manufacturing firms that are exposed to intensifying competition from China in their output markets invest more in automation than firms that are not exposed to this type of competition. We conduct external validation of the automation survey by examining the association between the automation measures and firm performance measures constructed from completely independent data sources. We find that the measures of automation are significantly associated with productivity and profitability.

Suggested Citation

  • Lene Kromann & Anders Sørensen, 2019. "Automation, performance and international competition: a firm-level comparison of process innovation," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 691-722.
  • Handle: RePEc:oup:ecpoli:v:34:y:2019:i:100:p:691-722.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/epolic/eiaa002
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    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. Davide Antonioli & Alberto Marzucchi & Francesco Rentocchini & Simone Vannuccini, 2022. "Robot Adoption and Innovation Activities (last revised: December 2023)," Munich Papers in Political Economy 21, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
    2. Antonioli, Davide & Marzucchi, Alberto & Rentocchini, Francesco & Vannuccini, Simone, 2024. "Robot adoption and product innovation," Research Policy, Elsevier, vol. 53(6).
    3. Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Gu, Grace & Malik, Samreen & Pozzoli, Dario & Rocha, Vera, 2021. "Worker Reallocation, Firm Innovation, and Chinese Import Competition," Working Papers 9-2021, Copenhagen Business School, Department of Economics.
    5. Wilson, Grant Alexander & Case, Tyler & Dobni, C. Brooke, 2023. "A global study of innovation-oriented firms: Dimensions, practices, and performance," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    6. Wang, Shusheng & Yan, Yan & Li, Haitong & Wang, Baolin, 2024. "Whom you know matters: Network structure, industrial environment and digital orientation," Technological Forecasting and Social Change, Elsevier, vol. 206(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. Nam, Changwoo, 2016. "Impact of Corporate Tax Cuts on Corporate Investment," KDI Policy Forum 264, Korea Development Institute (KDI).
    2. Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
    3. Ornaghi, Carmine, 2008. "Price deflators and the estimation of the production function," Economics Letters, Elsevier, vol. 99(1), pages 168-171, April.
    4. Dalle Nogare, Chiara & Kauder, Björn, 2017. "Term limits for mayors and intergovernmental grants: Evidence from Italian cities," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 1-11.
    5. Dietmar Harhoff & Elisabeth Mueller & John Van Reenen, 2014. "What are the Channels for Technology Sourcing? Panel Data Evidence from German Companies," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 23(1), pages 204-224, March.
    6. Matteo G. Richiardi & Luis Valenzuela, 2024. "Firm heterogeneity and the aggregate labour share," LABOUR, CEIS, vol. 38(1), pages 66-101, March.
    7. Kathryn Rudie Harrigan & Maria Chiara Guardo & Bo Cowgill, 2017. "Multiplicative-innovation synergies: tests in technological acquisitions," The Journal of Technology Transfer, Springer, vol. 42(5), pages 1212-1233, October.
    8. David Van Dijcke, 2022. "On the Non-Identification of Revenue Production Functions," Papers 2212.04620, arXiv.org, revised May 2024.
    9. Anupam Das Gupta & Syed Moudud-Ul-Huq, 2020. "Do competition and revenue diversification have significant effect on risk-taking? Empirical evidence from BRICS banks," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(01), pages 1-28, March.
    10. Meschi, Elena & Taymaz, Erol & Vivarelli, Marco, 2011. "Trade, technology and skills: Evidence from Turkish microdata," Labour Economics, Elsevier, vol. 18(S1), pages 60-70.
    11. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    12. Thushyanthan Baskaran & Zohal Hessami, 2012. "Public education spending in a globalized world:," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(5), pages 677-707, October.
    13. Garcia, Angel & Jaumandreu, Jordi & Rodriguez, Cesar, 2004. "Innovation and jobs: evidence from manufacturing firms," MPRA Paper 1204, University Library of Munich, Germany.
    14. Francesco Bogliacino & Marco Vivarelli, 2012. "The Job Creation Effect Of R&D Expenditures," Australian Economic Papers, Wiley Blackwell, vol. 51(2), pages 96-113, June.
    15. Jesús Crespo Cuaresma & Wolfgang Lutz & Warren Sanderson, 2014. "Is the Demographic Dividend an Education Dividend?," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 299-315, February.
    16. Måns Söderbom & Francis Teal, 2003. "Openness and human capital as sources of productivity growth: An empirical investigation," CSAE Working Paper Series 2003-06, Centre for the Study of African Economies, University of Oxford.
    17. Chad Turner & Robert Tamura & Sean Mulholland & Scott Baier, 2007. "Education and income of the states of the United States: 1840–2000," Journal of Economic Growth, Springer, vol. 12(2), pages 101-158, June.
    18. Mina Baliamoune-Lutz, 2017. "Trade and Environmental Quality in African Countries: Do Institutions Matter?," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 155-172, January.
    19. Lee, Grace H.Y. & Azali, M., 2010. "The endogeneity of the Optimum Currency Area criteria in East Asia," Economic Modelling, Elsevier, vol. 27(1), pages 165-170, January.
    20. Teplykh, Grigorii & Galimardanov, Amal, 2017. "Modeling of innovative investment in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 104-125.

    More about this item

    Keywords

    F14; L2; O30; M2; O14;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • 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:oup:ecpoli:v:34:y:2019:i:100:p:691-722.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/cebruuk.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.