A pattern of images on advanced scientific technologies: Examining the image structure based on the hierarchical principal component analysis - HIROOKA, Shuuichi; MATSUURA, Hitoshi; WAKABAYASHI, Mitsuru; MURAKAMI, Takashi (Japanese Journal of Administrative Science, 1989)
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.