How to Combine Term Clumping and Technology Roadmapping for Newly Emerging Science & Technology Competitive Intelligence: The Semantic TRIZ Tool and Case Study

Autores UPV
Revista Scientometrics


Competitive Technical Intelligence (CTI) addresses the landscape of both opportunities and competition for emerging technologies as the boom of Newly Emerging Science & Technology (NEST) ¿ characterized by a challenging combination of great uncertainty and great potential ¿ has become a significant feature of the globalized world. We have been focusing on the construction of a ¿NEST Competitive Intelligence¿ methodology, which blends bibliometric and text mining methods to explore key technological system components, current R&D emphases, and key players for a particular NEST. As an important part of these studies, this paper emphasizes the semantic TRIZ approach as a useful tool to represent ¿Term Clumping¿ results and apply them to Technology Roadmapping (TRM), with the help of semantic Problem & Solution (P&S) patterns. A greater challenge lies in the attempt to extend our approach into NEST Competitive Intelligence studies by using both inductive and purposive bibliometric approaches. Finally, an empirical study for Dye-Sensitized Solar Cells (DSSCs) is used to demonstrate these analyses.