IDEAS home Printed from https://ideas.repec.org/p/hhs/cbsnow/2015_003.html
   My bibliography  Save this paper

Automation, Performance and International Competition: Firm-level Comparisons of Process Innovation

Author

Listed:

Abstract

This paper presents new evidence on tradeinduced automation in manufacturing firms using unique data combining a retrospective survey that we have assembled with register data for 2005-2010. In particular, we establish a causal effect where firms that have specialized in product types for which the Chinese exports to the world market has risen sharply invest more in automated capital compared to firms that have specialized in other product types. We also study the relationship between automation and firm performance and find that firms with high increases in scale and scope of automation have faster productivity growth than other firms. Moreover, automation improves the efficiency of all stages of the production process by reducing setup time, run time, and inspection time and increasing uptime and quantity produced per worker. The efficiency improvement varies by type of automation.

Suggested Citation

  • Kromann, Lene & Sørensen, Anders, 2015. "Automation, Performance and International Competition: Firm-level Comparisons of Process Innovation," Working Papers 03-2015, Copenhagen Business School, Department of Economics.
    • Handle: RePEc:hhs:cbsnow:2015_003
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10398/9192
    File Function: Full text
    Download Restriction: Full text not avaiable
    ---><---

    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. 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).
    2. 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).
    3. 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.
    4. Antonioli, Davide & Marzucchi, Alberto & Rentocchini, Francesco & Vannuccini, Simone, 2024. "Robot adoption and product innovation," Research Policy, Elsevier, vol. 53(6).
    5. 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.
    6. 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).

    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. Khalil, Umair, 2017. "Do more guns lead to more crime? Understanding the role of illegal firearms," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 342-361.
    2. Díez-Esteban, José María & Farinha, Jorge Bento & García-Gómez, Conrado Diego, 2016. "The role of institutional investors in propagating the 2007 financial crisis in Southern Europe," Research in International Business and Finance, Elsevier, vol. 38(C), pages 439-454.
    3. Nam, Changwoo, 2016. "Impact of Corporate Tax Cuts on Corporate Investment," KDI Policy Forum 264, Korea Development Institute (KDI).
    4. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    5. Ensar Yılmaz & Zeynep Kaplan, 2022. "Heterogeneity of market power: firm-level evidence," Economic Change and Restructuring, Springer, vol. 55(2), pages 1207-1228, May.
    6. Nuno Carlos LEITÃO & Muhammad SHAHBAZ, 2012. "Migration and Tourism Demand," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(567)), pages 39-48, February.
    7. Geoffrey Barrows & Hélène Ollivier & Ariell Reshef, 2023. "Production Function Estimation with Multi-Destination Firms," CESifo Working Paper Series 10716, CESifo.
    8. Ornaghi, Carmine, 2008. "Price deflators and the estimation of the production function," Economics Letters, Elsevier, vol. 99(1), pages 168-171, April.
    9. Nucci, Francesco & Pozzolo, Alberto Franco, 2010. "The exchange rate, employment and hours: What firm-level data say," Journal of International Economics, Elsevier, vol. 82(2), pages 112-123, November.
    10. Benoit Dostie & Pierre Thomas Léger, 2014. "Firm-Sponsored Classroom Training: Is It Worth It for Older Workers?," Canadian Public Policy, University of Toronto Press, vol. 40(4), pages 377-390, December.
    11. Sanjaya Malik, 2015. "Conditional technology spillovers from foreign direct investment: evidence from Indian manufacturing industries," Journal of Productivity Analysis, Springer, vol. 43(2), pages 183-198, April.
    12. 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.
    13. Carlos Carreira & Luís Lopes, 2016. "Collecting new pieces to the regional knowledge spillovers puzzle: high-tech versus low-tech industries," GEMF Working Papers 2016-06, GEMF, Faculty of Economics, University of Coimbra.
    14. Ioannis Bournakis & Mike Tsionas, 2024. "A Non‐parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 641-671, June.
    15. Bertrand, Olivier & Zuniga, Pluvia, 2006. "R&D and M&A: Are cross-border M&A different? An investigation on OECD countries," International Journal of Industrial Organization, Elsevier, vol. 24(2), pages 401-423, March.
    16. 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.
    17. María José Quinteros & Rafael Sánchez & Mauricio G. Villena, 2020. "How do business schools compete in Latin America? Stability and best predictors of success for the AmericaEconomia MBA Ranking," Applied Economics, Taylor & Francis Journals, vol. 52(50), pages 5546-5563, October.
    18. Matteo G. Richiardi & Luis Valenzuela, 2024. "Firm heterogeneity and the aggregate labour share," LABOUR, CEIS, vol. 38(1), pages 66-101, March.
    19. 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.
    20. David Van Dijcke, 2022. "On the Non-Identification of Revenue Production Functions," Papers 2212.04620, arXiv.org, revised May 2024.

    More about this item

    Keywords

    automation; productivity; production theory; efficiency;
    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:cbsnow:2015_003. 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: CBS Library Research Registration Team (email available below). General contact details of provider: https://edirc.repec.org/data/incbsdk.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.