Emerging technologies embrace the very early stages of socio-technological evolution. Despite their appealing nature, they have been loosely defined and operationalized. In particular, operationalization approaches based on bibliometric methods have often tended to emphasize the exponential growth and the potential impacts of emerging technologies while overlooking their inherent uncertainty and ‘fluidity’. The purpose of this paper is to contribute to the operationalization of emerging technologies by presenting an approach for quantitatively interpreting technologies of an emerging nature along both dimensions. We do so by looking into the dynamic properties of scientific knowledge bases in terms of their rates and directions of change. Our approach integrates bibliometric indicators, social network analysis and multivariate statistical methods on scientific publications, and their citing and cited references. The empirical case of micro/nanoelectromechanical systems technologies (MEMS/NEMS), which embrace micro- and nano-sensors and actuators, is used. A total of thirteen MEMS/NEMS technologies are evaluated. Overall, our results provide a quantitative framework for discerning technological emergence through the evaluation of the dynamics of scientific knowledge bases. These results highlight the coupled intense patterns of growth and cognitive fluidity characterizing emerging technologies. We also provide a glimpse into the difficulties encountered by specific nanotechnology fields in bringing forward nano-enabled devices.
Author(s): Alfonso Ávila-Robinson and Kumiko Miyazaki
Organization(s): Tokyo Institute of Technology
Source: Technological Forecasting and Social Change