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Twins or Strangers? Differences and Similarities between Industrial and Academic Science

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  • Henry Sauermann
  • Paula E. Stephan

Abstract

Some scholars view academic and industrial science as qualitatively different knowledge production regimes. Others claim that the two sectors are increasingly similar. Large-scale empirical evidence regarding similarities and differences, however, has been missing. Drawing on prior work on the organization of science, we first develop a framework to compare and contrast the two sectors along four key dimensions: (1) the nature of research (e.g., basic versus applied); (2) organizational characteristics (e.g., degree of independence, pay); (3) researchers' preferences (e.g., taste for independence); and (4) the use of alternative disclosure mechanisms (e.g., patenting and publishing). We then compare the two sectors empirically using detailed survey data from a representative sample of over 5,000 life scientists and physical scientists employed in a wide range of academic institutions and private firms. Building on prior work that has emphasized different "research missions", we also examine how the nature of research is related to other characteristics of science within and across the two sectors. Our results paint a complex picture of academic and industrial science. While we find significant industry-academia differences with respect to all four dimensions, we also observe remarkable similarities. For example, both academic institutions and private firms appear to allow their scientists to stay actively involved in the broader scientific community and provide them with considerable levels of independence in their jobs. Second, we find significant differences not just between industrial and academic science but also within each of the two sectors as well as across fields. Finally, while the nature of research is a significant predictor of other dimensions such as the use of patenting and publishing, it does not fully explain the observed industry-academia differences in those dimensions. Overall, our results suggest that stereotypical views of industrial and academic science may be misleading and that future work may benefit from a richer and more nuanced description of the organization of science.

Suggested Citation

  • Henry Sauermann & Paula E. Stephan, 2010. "Twins or Strangers? Differences and Similarities between Industrial and Academic Science," NBER Working Papers 16113, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16113
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    References listed on IDEAS

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    1. Jason Owen-Smith & Walter W. Powell, 2004. "Knowledge Networks as Channels and Conduits: The Effects of Spillovers in the Boston Biotechnology Community," Organization Science, INFORMS, vol. 15(1), pages 5-21, February.
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    Cited by:

    1. Ganguli, Ina & Gaule, Patrick & Čugalj, Danijela Vuletić, 2020. "Biased Beliefs and Entry into Scientific Careers," IZA Discussion Papers 13475, Institute of Labor Economics (IZA).
    2. Jiang, Lin & Clark, Brent B. & Turban, Daniel B., 2023. "Overcoming the challenge of exploration: How decompartmentalization of internal communication enhances the effect of exploration on employee inventive performance," Technovation, Elsevier, vol. 119(C).
    3. Fabiano, Gianluca & Marcellusi, Andrea & Favato, Giampiero, 2021. "R versus D, from knowledge creation to value appropriation: Ownership of patents filed by European biotechnology founders," Technovation, Elsevier, vol. 108(C).
    4. Silvia Dalla Fontana & Ramana Nanda, 2023. "Innovating to Net Zero: Can Venture Capital and Start-Ups Play a Meaningful Role?," Entrepreneurship and Innovation Policy and the Economy, University of Chicago Press, vol. 2(1), pages 79-105.
    5. Gans, Joshua S. & Murray, Fiona E. & Stern, Scott, 2017. "Contracting over the disclosure of scientific knowledge: Intellectual property and academic publication," Research Policy, Elsevier, vol. 46(4), pages 820-835.
    6. G. Steven Mcmillan, 2015. "Exploration And Exploitation In Science: Their Impact On Scientific And Technological Outcomes," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 1-11.
    7. Ganguli, Ina & Gaulé, Patrick & Čugalj, Danijela Vuletić, 2022. "Chasing the academic dream: Biased beliefs and scientific labor markets," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 17-33.
    8. Henry Sauermann & Wesley M. Cohen, 2010. "What Makes Them Tick? Employee Motives and Firm Innovation," Management Science, INFORMS, vol. 56(12), pages 2134-2153, December.
    9. Henry Sauermann & Michael Roach, 2011. "Not All Scientists pay to be Scientists:," DRUID Working Papers 11-03, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    10. Alessandra Scandura, 2019. "The role of scientific and market knowledge in the inventive process: evidence from a survey of industrial inventors," The Journal of Technology Transfer, Springer, vol. 44(4), pages 1029-1069, August.

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    More about this item

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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