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Technology Adoption and Skills A Pilot Study of Kent SMEs

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  • Catherine Robinson
  • Christian Siegel
  • Sisi Liao

Abstract

Does the successful deployment of digital technologies require complementary investment in skills? We conducted a pilot survey to investigate. The survey elicited information on whether the firm was adopting one of the three digital technologies of interest (AI, robotics, big data), provided in-house training, and whether they experienced any problems recruiting workers. We find evidence that new technologies require complementary skill investments and that firms deem both new technologies and training of their workforce important for productivity. While there is some heterogeneity across the type of technologies (Robotics, AI, Big Data) introduced, firms facing difficulties attracting workers with the right skills are more likely to run own training programmes. This might suggest that there is a skills gap that may be holding back productivity and economic growth. Overall, the findings from our pilot survey demonstrate firms's awareness of the need for skills to complement new technologies to realise the productivity benefits in full.

Suggested Citation

  • Catherine Robinson & Christian Siegel & Sisi Liao, 2021. "Technology Adoption and Skills A Pilot Study of Kent SMEs," Studies in Economics 2114, School of Economics, University of Kent.
    • Handle: RePEc:ukc:ukcedp:2114
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    References listed on IDEAS

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    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Giulia Faggio & Kjell G. Salvanes & John Van Reenen, 2010. "The evolution of inequality in productivity and wages: panel data evidence," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 19(6), pages 1919-1951, December.
    3. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    4. Andy Feng & Anna Valero, 2020. "Skill-Biased Management: Evidence from Manufacturing Firms," The Economic Journal, Royal Economic Society, vol. 130(628), pages 1057-1080.
    5. Ministry of Finance,, 2015. "Economic Survey 2014-15," OUP Catalogue, Oxford University Press, number 9780199460182.
    6. Erik Brynjolfsson & Kristina McElheran, 2016. "The Rapid Adoption of Data-Driven Decision-Making," American Economic Review, American Economic Association, vol. 106(5), pages 133-139, May.
    7. Ann Bartel & Casey Ichniowski & Kathryn Shaw, 2007. "How Does Information Technology Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement, and Worker Skills," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1721-1758.
    8. MORIKAWA Masayuki, 2020. "Heterogeneous Relationships between Automation Technologies and Skilled Labor: Evidence from a Firm Survey," Discussion papers 20004, Research Institute of Economy, Trade and Industry (RIETI).
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    More about this item

    Keywords

    capital-skill complementarity; business performance; technology adoption;
    All these keywords.

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • M53 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Training
    • 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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