Predicting Technology Success: Identifying Key Predictors and Assessing Expert Evaluation for Advanced Technologies

Craig Galbraith, Sanford Ehrlich and Alex DeNoble

The Journal of Technology Transfer, 2006, vol. 31, issue 6, 673-684

Abstract: This study investigates a set of precursor factors that appear related to future technology success, and whether or not expert evaluators can a priori provide useful information during the technology review process. Sixty-nine highly advanced post 9–11 technologies are tracked over time. Based upon the results of this study, we conclude that a reasonably good predictive model can be constructed from organizational and technology factors, such as firm size, stage of development, and strategic partnerships. The results also indicate that the incremental value of expert reviewers and technology evaluators to predict future technology success is relatively small. Reviewers that provided the greatest predicative power, however, had current scientific responsibilities. These results raise important issues regarding the capability of developing predictive models of technology success. Copyright Springer Science+Business Media, LLC 2006

Keywords: technology commercialization; prediction model; technology transfer; O32 (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:kap:jtecht:v:31:y:2006:i:6:p:673-684

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DOI: 10.1007/s10961-006-0022-8

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The Journal of Technology Transfer is currently edited by Albert N. Link, Donald S. Siegel, Barry Bozeman and Simon Mosey

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