Using technological entropy to identify technology life cycle

Abstract

Abstract Identification of technology life cycles(TLC) provides a crucial basis for managing national policy, regional planning, and enterprise investment. Thus, it is a significant challenge to determine the stages of TLC. To this end, an entropy-based indicator is proposed, as well as a quantitative method based on the S-curve of entropy is established to identify the stages of TLC. Furthermore, the effectiveness of the method is verified by the analogy of three typical cases (thin-film-transistor liquid-crystal displays, cathode ray tubes, and nano-biosensors). It is clear that the entropy calculation produces a sum of overall distributions for patent applications against the researchers in the field to be studied, which can be used to find out the stage changes of TLC, while the other analysis considers trends of many patent active measures such as patent applications and citations collectively, to figure out the changes. Thus, the former constructs an index that has clear meanings and then uses its characterization to identify the changes logically, while the latter can only try to identify them empirically often with no trivial difficulties as these trends are often inconsistent. Finally, three-dimensional (3D) printing is investigated as an empirical case study, which reveals that 3D printing is still in its growth stage.