Innovation Diffusion



Alan J. Thomson
B.Sc. DLSHTM M.Sc. Ph.D

Victoria, BC, Canada

email: ajthomson@AdaptiveKM.com

Innovation Diffusion:

Diffusion is

the process by which an innovation is communicated through certain channels over time among members of a social system (Rogers 1995:5)

Innovations are described by five attributes:

  • Relative advantage: the degree to which an innovation surpasses the idea it supersedes
  • Compatibility: the degree to which the innovation is compatible with the values, needs and norms of the population
  • Complexity: the extent to which the innovation is perceived as difficult to understand or use
  • Trialability: the ease with which people can try out the innovation
  • Observability: the degree to which others can observe the innovation

A model of the innovation diffusion process in which the effects of the 5 innovation attributes on adoption by a population are mediated by "fitness" and "exposure" (Thomson et al. 2004):

Figure: Model of the innovation diffusion process mediated by "fitness" and "exposure"

Understanding innovation diffusion processes helps increase the likelihood of adoption of systems or new policies or practices.


Innovation Diffusion publications:

Thomson, A.J. 2008. Diagnosis of sparse adoption data using an expert system-guided innovation diffusion simulation model. The Innovation Journal: The Public Sector Innovation Journal, Volume 13(3), 2008, article 11 [available at http://www.innovation.cc/peer-reviewed/thomson1dec2008jag_rev12i11.pdf]

Innes, T., Green, C. and Thomson, A. 2005. Surprising Futures. Pages 24-48 In: L. Hetemaki and S. Nilsson (eds.), Information Technology and the Forest Sector. IUFRO World Series Volume 18. Vienna, Austria: International Union of Forest Research Organizations. 235 pp. (http://www.metla.fi/julkaisut/muut/ICT-forest-sector-2005.pdf)

Thomson, A., M. Haggith and R. Prabhu. 2004. Innovation diffusion: predicting success of system development. Proc. 15th International Workshop on Database and Expert Systems, Zaragoza, Spain, 30 Aug-3 Sept 2004: 627-631. IEEE Computer Society.

Haggith, M., R. Prabhu, C.J.P. Colfer, B. Ritchie, A. Thomson and H. Mudavanhu. 2003. Infectious Ideas: Modelling the Diffusion of Ideas across Social Networks. Small-scale Forest Economics, Management and Policy, 2(2): 225-239.

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