IDEAS home Printed from https://ideas.repec.org/r/eee/infome/v14y2020i2s175115771930210x.html
   My bibliography  Save this item

Topic-linked innovation paths in science and technology

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Lewei Zhou & Mingliang Yue & Tingcan Ma & Chundong Li, 2025. "The impact of patent citation on the citation performance of academic papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(8), pages 4221-4248, August.
  2. Krzysztof Szczygielski & Jerzy Mycielski, 2024. "The mutual reinforcement of scientific and technological knowledge—a technology-level analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6533-6549, November.
  3. Yuhang Wang & Lei Pei & Jianjun Sun & Lele Kang, 2025. "Trace on both sides: a two-step text mining method to identify academic inventors’ patent–paper pairs," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(2), pages 833-860, February.
  4. Xu, Haiyun & Yue, Zenghui & Pang, Hongshen & Elahi, Ehsan & Li, Jing & Wang, Lu, 2022. "Integrative model for discovering linked topics in science and technology," Journal of Informetrics, Elsevier, vol. 16(2).
  5. Peng Liu & Wei Zhou & Lijie Feng & Jinfeng Wang & Kuo-Yi Lin & Xuan Wu & Dingtang Zhang, 2024. "Mapping and comparing the technology evolution paths of scientific papers and patents: an integrated approach for forecasting technology trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(4), pages 1975-2005, April.
  6. Matteo Lascialfari & Marie-Benoît Magrini & Guillaume Cabanac, 2022. "Unpacking research lock-in through a diachronic analysis of topic cluster trajectories in scholarly publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6165-6189, November.
  7. Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
  8. Li, Xin & Wang, Yan, 2024. "A novel integrated approach for quantifying the convergence of disruptive technologies from science to technology," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
  9. Zheng, Zhejun & Ma, Yaxue & Ba, Zhichao & Pei, Lei, 2024. "Tree knowledge structure for better insight: Capturing biomedical science-technology knowledge linkage with MeSH," Journal of Informetrics, Elsevier, vol. 18(4).
  10. Ba, Zhichao & Meng, Kai & Ma, Yaxue & Xia, Yikun, 2024. "Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
  11. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  12. Huailan Liu & Zhiwang Chen & Jie Tang & Yuan Zhou & Sheng Liu, 2020. "Mapping the technology evolution path: a novel model for dynamic topic detection and tracking," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2043-2090, December.
  13. Dieter F. Kogler & Thomas Brenner & Fatih Celebioglu & Hyunha Shin, 2024. "The science-innovation nexus in a regional context—introduction to the special issue, policy and future research directions," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 44(2), pages 141-149, June.
  14. Mila Cascajares & Alfredo Alcayde & José Antonio Garrido-Cardenas & Francisco Manzano-Agugliaro, 2020. "The Contribution of Spanish Science to Patents: Medicine as Case of Study," IJERPH, MDPI, vol. 17(10), pages 1-24, May.
  15. Weijie Zhu & Wucheng Han & Ruoyu Lu & Jiasu Lei, 2025. "The impact of enterprises’ scientific capabilities on innovation performance: evidence from an empirical analysis and simulation model," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-18, December.
  16. Shuo Xu & Ling Li & Xin An & Liyuan Hao & Guancan Yang, 2021. "An approach for detecting the commonality and specialty between scientific publications and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7445-7475, September.
  17. Dejian Yu & Zhaoping Yan, 2022. "Combining machine learning and main path analysis to identify research front: from the perspective of science-technology linkage," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4251-4274, July.
  18. Kang, Inje & Yang, Jiseong & Lee, Wonjae & Seo, Eun-Yeong & Lee, Duk Hee, 2023. "Delineating development trends of nanotechnology in the semiconductor industry: Focusing on the relationship between science and technology by employing structural topic model," Technology in Society, Elsevier, vol. 74(C).
  19. Jang, Hyejin & Lee, Suyeong & Yoon, Byungun, 2023. "Data-driven techno-socio co-evolution analysis based on a topic model and a hidden Markov model," Technovation, Elsevier, vol. 126(C).
  20. Keye Wu & Ziyue Xie & Jia Tina Du, 2024. "Does science disrupt technology? Examining science intensity, novelty, and recency through patent-paper citations in the pharmaceutical field," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5469-5491, September.
  21. Wang, Xiaoguang & He, Jing & Huang, Han & Wang, Hongyu, 2022. "MatrixSim: A new method for detecting the evolution paths of research topics," Journal of Informetrics, Elsevier, vol. 16(4).
  22. Ba, Zhichao & Liang, Zhentao, 2021. "A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling," Journal of Informetrics, Elsevier, vol. 15(3).
  23. Shuo Xu & Ling Li & Xin An, 2023. "Do academic inventors have diverse interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1023-1053, February.
  24. Chen, Xi & Mao, Jin & Li, Gang, 2024. "A co-citation approach to the analysis on the interaction between scientific and technological knowledge," Journal of Informetrics, Elsevier, vol. 18(3).
  25. Hengmin Zhu & Li Qian & Wang Qin & Jing Wei & Chao Shen, 2022. "Evolution analysis of online topics based on ‘word-topic’ coupling network," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3767-3792, July.
  26. Jinqing Yang & Xiufeng Cheng & Guanghui Ye & Yuchen Zhang, 2024. "Understanding scientific knowledge evolution patterns based on egocentric network perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6719-6750, November.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.