Using technological entropy to identify technology life cycle. Issue 2 (May 2021)

• Record Type: Journal Article
• Authors: Lin, Deming; Liu, Wenbin; Guo, Yinxin; Meyer, Martin
• Is Part Of: Journal of informetrics. Volume 15:Issue 2(2021)
• Publication Date: 2021-05
• Subjects: Entropy -- Technology life cycle -- Technology evolution -- Patent -- 3D printing; Library statistics -- Periodicals; Information science -- Statistical methods -- Periodicals; Bibliometrics -- Periodicals; Bibliothèques -- Statistiques -- Périodiques; Sciences de l'information -- Méthodes statistiques -- Périodiques; Bibliométrie -- Périodiques; 020.727
• DOI: 10.1016/j.joi.2021.101137
• Languages: English
• ISSNs: 1751-1577

Abstract

Highlights: The shifts in technology paradigms can be detected by analyzing the technological entropy. The technological entropy method for the identification of technology life circles is proposed. The entropy-based method for the identification of technology life circles has three advantages: clear logical structure, convenience, and expansibility. 3D printing technology is identified to be at the growth stage as an empirical example using entropy. 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.