Affiliation:
1. National Research Council of Italy
2. Allameh Tabataba'i University
Abstract
Abstract
The goal of this study is to develop a technology analysis for examining the evolutionary phases of some critical quantum technologies to explain on-going technological development. Method applies S-shaped model based on logistic function that is estimated with patent data to analyze the phases of quantum technologies over the course of their technological evolution. Findings reveal that the technological cycle of recent quantum technologies has a shorter period in emergence phase and a longer period in growth and maturity phases than older quantum technologies. In particular, structure of technological cycle also shows that for quantum technologies originated after 1980, technological phase of emergence (to reach to the point of growth) is reduced to 52% of the total length of the cycle, compared to 68% of technologies originated before 1980, whereas the growth and maturity phases for technologies originated after 1980 have a higher percentage weight on the total duration of the cycle than technologies originated before 1980: growth stage is 22.78% of total duration of cycle in new technologies originated after 1980 vs. 15.76% in older technologies originated before the 1980; maturity stage is 25.32% vs. 16.08%, respectively of total technological cycle. Results here can provide theoretical implications to explain dynamics and structure of the technological evolution of emerging quantum innovations that support the technological forecasting for improving decisions of R&D investments in specific technologies that can be major sources of next technological, industrial, economic and social change.
Publisher
Research Square Platform LLC
Reference156 articles.
1. Patterns of industrial innovation;Abernathy WJ;Technology Review,1978
2. Aduba, J. J., Asgari, B. 2021. Analysing and forecasting the diffusion of electronic payments system in Nigeria. Technology Analysis & Strategic Management, 1–19.
3. Altuntas S., Aba S. 2022. Technology Forecasting of Unmanned Aerial Vehicle Technologies through Hierarchical S-Curves¸ Defence Science Journal, Vol. 72, No. 1, January 2022, pp. 18–29, DOI: 10.14429/dsj.72.16823
4. Analysis of patent documents with utility mining: A case study of wind energy technology;Altuntas F;Kybernetes,2021
5. Altuntas, S.; Dereli, T. & Kusiak, A. 2015. Forecasting technology success based on patent data. Technol. Forecast. Soc. Change., 2015, 96 (July), 202–214.doi: 10.1016/j.techfore.2015.03.011.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献