Emerging Research in Science and Technology: Patterns of New Knowledge Development
By Phin Upham and Henry Small
Abstract
Research fronts represent the most dynamic areas of science and technology and the areas that attract the most scientific interest. We construct a methodology to identify these fronts, and we use quantitative and qualitative methodology to analyze and describe them. Our methodology is able to identify these fronts as they form—with potential use by firms, venture capitalists, researchers, and governments looking to identify emerging high-impact technologies. We also examine how science and technology absorbs the knowledge developed in these fronts and find that fronts which maximize impact have very different characteristics than fronts which maximize growth, with consequences for the way science develops over time.
Introduction
Areas of scientific research that generate intense interest from other scientists tend to be perceived as the most promising (Braam et al. 1988, Hirschman 1970), are particularly well funded (Boyack and Borner 2003), and are more likely to result in commercial discoveries (Narin et al, 1997; Trajtenberg 1990). In this paper we study small clusters of highly cited research, called “research fronts.” We work to provide quantitative and qualitative support for continued, focused study of these areas as important for understanding the development of science and technology more broadly. These areas of intensive work are interesting to R&D laboratories looking for future innovation breakthroughs, venture capitalists looking to allocate investment, governments interested in promoting emerging science, and researchers hoping to work on promising topics.
The long term goal of this work is to develop a robust and efficient methodology for identifying and tracking highly cited research areas at the micro-speciality level. This includes detecting them as they emerge and understanding the role these fronts play in the development of science and technology. The broad requirement of this methodology is that it does not presuppose the existence of any specific research area, such as would be required in a traditional literature-searching approach, nor any prior knowledge about the scientific area, but instead relies on an objective, comprehensive monitoring of citations. It should be possible to increase or decrease the sensitivity of the detection by adjusting parameters and make direct comparisons of different time slices. In addition, the method should be multidisciplinary and utilize field normalization to obtain a systematic view across different disciplines. The scope should be scalable from the micro-structure to the macro-structure of science to see the context of the innovation. Finally, the method should capture both social aspects and the topical content of scientific areas.
