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

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  • 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.
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    File URL: http://hdl.handle.net/10.1093/epolic/eiaa002
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    References listed on IDEAS

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    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.
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    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. 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).
    3. 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.
    4. 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).
    5. Davide Antonioli & Alberto Marzucchi & Francesco Rentocchini & Simone Vannuccini, 2024. "Robot Adoption and Product Innovation," GREDEG Working Papers 2024-01, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.

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    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

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