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Learning by Doing and the Locus of Innovative Capability in Biotechnology Research

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  • Amit Jain

    (Division of Engineering and Technology Management, and Department of Strategy and Policy, National University of Singapore, Singapore 117574)

Abstract

Innovative capability, the knowledge a firm uses to innovate, is an input into and an output of the process of innovation. In this paper, I put forward the notion that innovative capability, similar to experience in production, accumulates by learning by doing and that innovation is characterized by a learning curve. Using patent data from 20,886 scientists working in 611 biotechnology firms in the U.S. and Canadian biotechnology industry from 1970 to 2007, I estimate a learning curve in innovation and determine the loci of innovative capability. Although knowledge stocks in the different loci accumulate over time in day-to-day firm activities, empirical results suggest that the individual is the primary repository of innovative capability and that experience working together in teams has a secondary influence on productivity. Contrary to prior learning curve research, accumulated firm experience has no direct effect on productivity. However, when individuals possess relevant domain knowledge and have experience working together, they benefit from knowledge spillovers within the firm. This suggests that knowledge stocks in the different loci are complementary to one another and that the comingling of these disparate bins of knowledge is an important facet of innovative capability.

Suggested Citation

  • Amit Jain, 2013. "Learning by Doing and the Locus of Innovative Capability in Biotechnology Research," Organization Science, INFORMS, vol. 24(6), pages 1683-1700, December.
    • Handle: RePEc:inm:ororsc:v:24:y:2013:i:6:p:1683-1700
    DOI: 10.1287/orsc.2013.0821
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    7. C. Gizem Korpeoglu & Ersin Körpeoğlu & Sıdıka Tunç, 2021. "Optimal Duration of Innovation Contests," Manufacturing & Service Operations Management, INFORMS, vol. 23(3), pages 657-675, May.
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    11. Varshney, Mayank & Jain, Amit, 2023. "Technology acquisition following inventor exit in the biopharmaceutical industry," Technovation, Elsevier, vol. 126(C).
    12. Varshney, Mayank & Jain, Amit, 2023. "Understanding “reverse” knowledge flows following inventor exit in the semiconductor industry," Technovation, Elsevier, vol. 121(C).
    13. Fan, Terence & Schwab, Andreas & Geng, Xuesong, 2021. "Habitual entrepreneurship in digital platform ecosystems: A time-contingent model of learning from prior software project experiences," Journal of Business Venturing, Elsevier, vol. 36(5).
    14. Sunkee Lee & Philipp Meyer-Doyle, 2017. "How Performance Incentives Shape Individual Exploration and Exploitation: Evidence from Microdata," Organization Science, INFORMS, vol. 28(1), pages 19-38, February.
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    16. Christophe Pennetier & Karan Girotra & Jürgen Mihm, 2019. "R&D Spending: Dynamic or Persistent?," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 636-657, July.
    17. Varshney, Mayank, 2023. "Learning-by-hiring: How do rival firms learn from focal firm's hiring," Research Policy, Elsevier, vol. 52(2).
    18. Jain, Amit, 2023. "How knowledge loss and network-structure jointly determine R&D productivity in the biotechnology industry," Technovation, Elsevier, vol. 119(C).
    19. Maximiliano Machado, 2021. "Heterogeneous Innovation Persistence: Evidence From Uruguayan Firms," Documentos de Trabajo (working papers) 21-04, Instituto de Economía - IECON.
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