Quantum technology research field variability to explain scientific and technical development in society

Bilal Kargı & Mario Coccia

International Journal of Technological Learning, Innovation and Development2025https://doi.org/10.1504/ijtlid.2025.149366article
AJG 1
Weight
0.50

What the paper says

This study explores how variations in research topics impact the evolution of technologies, focusing on quantum technologies such as optics, metrology, imaging, and sensing. It finds that older fields, like quantum optics (established in 1958), exhibit lower topic diversity (entropy: 0.827) and are more concentrated on specific research areas (standard deviation: 4,330.3). In contrast, newer fields like quantum sensing (since 2000) show greater diversity (entropy: 0.925), suggesting a broader range of potential evolutionary paths (standard deviation: 49.6). Analysis reveals that quantum optics tends to focus on established topics, while quantum sensing explores emerging areas. Furthermore, 91.7% of topic variation occurs within fields, and statistical tests (ANOVA with F-test = 18.29, p-value = 0.001) confirm significant differences in topic distribution. The study suggests two key principles: 1) the diversity of research topics decreases as a field matures; 2) a field's inherent characteristics shape its technological trajectory, offering insights for better scientific forecasting and resource allocation.

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https://doi.org/https://doi.org/10.1504/ijtlid.2025.149366

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@article{bilal2025,
  title        = {{Quantum technology research field variability to explain scientific and technical development in society}},
  author       = {Bilal Kargı & Mario Coccia},
  journal      = {International Journal of Technological Learning, Innovation and Development},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijtlid.2025.149366},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.