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Big science, learning, and innovation: evidence from CERN procurement

Author

Listed:
  • Massimo Florio
  • Francesco Giffoni
  • Anna Giunta
  • Emanuela Sirtori

Abstract

We study the way in which public procurement by big research infrastructures enhances suppliers’ performance. Using survey data on 669 CERN’s suppliers, we built a unique data set to analyze, through an ordered logit model and Bayesian networks, the determinants of suppliers’ sales, profits, and development activities. We find that collaborative relations between CERN and its suppliers improve suppliers’ performance and increase positive spillovers along the supply chain. This suggests that public procurement as a mission-oriented innovation policy should promote cooperative relations and not only market mechanisms.

Suggested Citation

  • Massimo Florio & Francesco Giffoni & Anna Giunta & Emanuela Sirtori, 2018. "Big science, learning, and innovation: evidence from CERN procurement," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(5), pages 915-936.
    • Handle: RePEc:oup:indcch:v:27:y:2018:i:5:p:915-936.
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    File URL: http://hdl.handle.net/10.1093/icc/dty029
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    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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