35 Pages Posted: 24 Sep 2009
Date Written: September 24, 2009
Even experts cannot be fully aware of all the promising developments in broad and complex fields of technology, such as renewable energy. Fortunately, there exist many diverse sources of information that report new technological developments, such as journal publications, news stories, and blogs. However, the volume of data contained in these sources is enormous; it would be difficult for a human to read and digest all of this information - especially in a timely manner. This paper describes a novel application of technology mining techniques to these diverse information sources to study, visualize, and identify the evolution of promising new technologies - a challenge we call 'early growth technology analysis.' For the work reported herein, we use as inputs information about millions of published documents contained in sources such as SCIRCUS, Inspec, and Compendex. We accomplish this analysis through the use of bibliometric analysis, consisting of three key steps: 1. Extract related keywords (from keywords in articles) 2. Determine the annual occurrence frequencies of these keywords 3. Identify those exhibiting rapid growth, particularly if starting from a low base. To provide a focus for the experiments and subsequent discussions, a pilot study was conducted in the area of 'renewable energy,' though the techniques and methods developed are neutral to the domain of study. Preliminary results and conclusions from the case study are presented and are discussed in the context of the effectiveness of the proposed methodology.
Suggested Citation: Suggested Citation
Ziegler, Blaine and Kaya Firat, Ayse and Madnick, Stuart and Woon, Wei Lee and Camina, Steven and Li, Clare and Fogg, Erik, Approach and Preliminary Results for Early Growth Technology Analysis (September 24, 2009). MIT Sloan Research Paper No. 4756-09. Available at SSRN: https://ssrn.com/abstract=1478001 or http://dx.doi.org/10.2139/ssrn.1478001