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Forecasting the diffusion of product and technology innovations

Using Google trends as an example
: Duwe, Daniel; Herrmann, Florian; Spath, Dieter


Kocaoglu, Dundar F. (Ed.) ; Institute of Electrical and Electronics Engineers -IEEE-; Portland State University, Dept. of Engineering and Technology Management:
PICMET 2018, Portland International Conference on Management of Engineering and Technology. Proceedings : Managing technological entrepreneurship: the engine for economic growth; August 19 - 23, 2018, Honolulu, Hawaii, USA
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-890843-38-0
ISBN: 978-1-890843-37-3
ISBN: 978-1-5386-7719-3
8 S.
Portland International Conference on Management of Engineering and Technology (PICMET) <2018, Honolulu/Hawaii>
Fraunhofer IAO ()

Product innovations represent the backbone of sustainable entrepreneurial success. In times of increasingly short development and life cycles of products on the one hand and an increasing degree of product complexity and individuality on the other hand, the right timing of the development and market introduction of physical and digital product innovations has become the key success factor for companies. The forecast of the diffusion of innovative product technologies and in particular the tipping point after which they significantly penetrate the market is therefore of paramount importance both for new and established companies. Research has found answers on how to identify technological change, yet the prediction of the timing of technological change remains unsolved. Traditional life cycle models usually measure the development of products and technologies based on one criterion such as sales or performance and lack in the definition of variables and their measurement. However, to predict the diffusion of innovative product technologies multiple factors and their operationalization have to be taken into account in technology push-market-pull systems. On the technology side, patents and publications have been acknowledged as valuable indicators for progress. On the market side, appropriate indicators still need to be identified. Therefore, in this paper a quantitative scientometric analysis of past innovations has been performed using Google Trends, a service which has recently taken on greater significance. The analysis yields a significant correlation.