Based on the hierarchical principal component analysis techinigue, a set of data involving evaluative ratings (5-point scale) on 10 most advanced scientific technologies were analysed, for the purpose of identifying basic as well as specific evaluative dimensions associated with these advanced technologies. A data set for the present analysis maintained a structure to conform the three-mode factor anaysis: subjects rated by using the same set of scales 10 different technologies (i. e., artificial intelligence, bio-technology, nuclear power generation, space technology, linear motor car, tube baby, 5th generation computer, super conductivity, organ transplant, and high-speed reactor). A series of conventional factor analyses (principal axes followed by Varimax rotation) and a present hierarchical component analysis as well produced basically the same image structure on advanced technologies. For basic common dimensions, three factors namely useful and development, dagerous and harmful , and personally beneficial were identified, while another three factors were derived to represent specific dimensions unique to each technology.