This paper constructs an Impelling Technology Foresight Model (ITFM) for foreseeing impelling technology in the field of life science, which is a comprehensive model consisting of four class indicators: international scientific environment, evolving of papers and patents, collaboration features of patent assignees’ collaboration networks, and impacts. A case study was carried out in the field of life science. Recombinant DNA (RbDNA) and Monoclonal Antibody (mAb) were selected as impelling technologies to carry out the case study. ELISA Diagnosis (ELISA) and Fermentation Technology (FT) were defined as non-impelling technologies to be control group. Results revealed that impelling technologies have higher evolving rates from the stage of growth to maturity. Significant policies or programs usually boost the rapid progress of impelling technologies. Impelling
technologies have much higher impact than non-impelling ones. Collaboration behaviour is much more broad and general for impelling technologies. To our knowledge, this is the first study carried out to date to foreseeing impelling technologies at this way.
Author(s): Yunwei Chen, Yong Deng, Fang Chen, Chenjun Ding, Ying Zheng and Shu Fang
Organization: Chengdu Library of the Chinese Academy of Sciences
Source: Proceeding of 15th International Conference on Scientometrics and Infometrics