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Collaborative Research and Development: New Insights from Cyclic Models of the Innovation Process

Author

Listed:
  • John Steen

    (School of Management, University of Tasmania, GPO Box 252-16, Hobart, Tasmania, Australia)

  • Dallas Hanson

    (School of Management, University of Tasmania, GPO Box 252-16, Hobart, Tasmania, Australia)

  • Peter Liesch

    (School of Management, University of Tasmania, GPO Box 252-16, Hobart, Tasmania, Australia)

Abstract

Traditional linear models of innovation, in which it is assumed that government funding of R&D will axiomatically create innovative industries, have become obsolete. This paper suggests that innovation is in fact a complex and interactive process that involves cycles of learning. However, these "knowledge cycle" models of innovation are largely unvalidated empirically and further research will be required to extend the current theory. Knowledge cycle models appear to be superior to the linear models for a number of reasons. These include major roles for tacit (uncodified) knowledge as well as explicit (codified) knowledge, which are largely ignored in linear innovation models. An emphasis upon iterative collaboration between firms and researchers and the importance of firms participating more directly in the research and development (R&D) process may enhance the utilisation of these forms of knowledge.

Suggested Citation

  • John Steen & Dallas Hanson & Peter Liesch, 1998. "Collaborative Research and Development: New Insights from Cyclic Models of the Innovation Process," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 2(01), pages 107-121.
    • Handle: RePEc:wsi:ijimxx:v:02:y:1998:i:01:n:s1363919698000055
    DOI: 10.1142/S1363919698000055
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    Cited by:

    1. Eva Mora-Valentín & Marta Ortiz-de-Urbina-Criado, 2009. "Improving the effectiveness of academic-business models: an analysis of obstacles in R&D activities in service industries," Service Business, Springer;Pan-Pacific Business Association, vol. 3(4), pages 395-413, December.
    2. Martie-Louise Verreynne & Rui Torres de Oliveira & John Steen & Marta Indulska & Jerad A. Ford, 2020. "What motivates ‘free’ revealing? Measuring outbound non-pecuniary openness, innovation types and expectations of future profit growth," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 271-301, July.

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