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Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020

Citations

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Cited by:

  1. Park, Mingyu & Geum, Youngjung, 2022. "Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
  2. Kangas, H.L. & Ollikka, K. & Ahola, J. & Kim, Y., 2021. "Digitalisation in wind and solar power technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  3. Juite Wang & Tzu-Yen Hsu, 2023. "Early discovery of emerging multi-technology convergence for analyzing technology opportunities from patent data: the case of smart health," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4167-4196, August.
  4. Park, Inchae & Yoon, Byungun, 2018. "Technological opportunity discovery for technological convergence based on the prediction of technology knowledge flow in a citation network," Journal of Informetrics, Elsevier, vol. 12(4), pages 1199-1222.
  5. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
  6. Joon Hyung Cho & Jungpyo Lee & So Young Sohn, 2021. "Predicting future technological convergence patterns based on machine learning using link prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5413-5429, July.
  7. Changyong Lee & Suckwon Hong & Juram Kim, 2021. "Anticipating multi-technology convergence: a machine learning approach using patent information," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1867-1896, March.
  8. Jong Wook Lee & So Young Sohn, 2021. "Patent data based search framework for IT R&D employees for convergence technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5687-5705, July.
  9. ZHU Chen & MOTOHASHI Kazuyuki, 2022. "Government R&D spending as a driving force of technology convergence," Discussion papers 22030, Research Institute of Economy, Trade and Industry (RIETI).
  10. Chand Bhatt, Priyanka & Kumar, Vimal & Lu, Tzu-Chuen & Daim, Tugrul, 2021. "Technology convergence assessment: Case of blockchain within the IR 4.0 platform," Technology in Society, Elsevier, vol. 67(C).
  11. Qian Xu & Hua Cheng, 2021. "Research on the Evolution of Textile Technological Convergence in China," Sustainability, MDPI, vol. 13(5), pages 1-13, February.
  12. Yun, Siyeong & Song, Kisik & Kim, Chulhyun & Lee, Sungjoo, 2021. "From stones to jewellery: Investigating technology opportunities from expired patents," Technovation, Elsevier, vol. 103(C).
  13. Pan, Maomao & Bai, Min & Ren, Xiaoxiao, 2022. "Does internet convergence improve manufacturing enterprises’ competitive advantage? Empirical research based on the mediation effect model," Technology in Society, Elsevier, vol. 69(C).
  14. Hamrouni, Daghbagi, 2022. "International diffusion of knowledge labor productivity and catching up between North and South," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 170-178.
  15. Sun, Bing & Yang, Xueting & Zhong, Shen & Tian, Shengnan & Liang, Tian, 2024. "How do technology convergence and expansibility affect information technology diffusion? Evidence from the internet of things technology in China," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
  16. Li, Jing & Yu, Qian, 2024. "Scientists’ disciplinary characteristics and collaboration behaviour under the convergence paradigm: A multilevel network perspective," Journal of Informetrics, Elsevier, vol. 18(1).
  17. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
  18. Sajad Ashouri & Anne-Laure Mention & Kosmas X. Smyrnios, 2021. "Anticipation and analysis of industry convergence using patent-level indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5727-5758, July.
  19. Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
  20. Qian Xu & Yabin Yu & Xiao Yu, 2022. "Analysis of the Technological Convergence in Smart Textiles," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
  21. Seo, Wonchul & Afifuddin, Mokh, 2024. "Developing a supervised learning model for anticipating potential technology convergence between technology topics," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
  22. Wenjing Zhu & Bohong Ma & Lele Kang, 2022. "Technology convergence among various technical fields: improvement of entropy estimation in patent analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7731-7750, December.
  23. Ying Tang & Xuming Lou & Zifeng Chen & Chengjin Zhang, 2020. "A Study on Dynamic Patterns of Technology Convergence with IPC Co-Occurrence-Based Analysis: The Case of 3D Printing," Sustainability, MDPI, vol. 12(7), pages 1-26, March.
  24. Kai Guo & Tiantian Zhang & Yan Liang & Jiyao Zhao & Xiangmin Zhang, 2023. "Research on the promotion path of green technology innovation of an enterprise from the perspective of technology convergence: configuration analysis using new energy vehicles as an example," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 4989-5008, June.
  25. Soyea Lee & Junseok Hwang & Eunsang Cho, 2022. "Comparing technology convergence of artificial intelligence on the industrial sectors: two-way approaches on network analysis and clustering analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 407-452, January.
  26. Chen Zhu & Kazuyuki Motohashi, 2023. "Government R&D spending as a driving force of technology convergence: a case study of the Advanced Sequencing Technology Program," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3035-3065, May.
  27. Zhao, Shengchao & Zeng, Deming & Li, Jian & Feng, Ke & Wang, Yao, 2023. "Quantity or quality: The roles of technology and science convergence on firm innovation performance," Technovation, Elsevier, vol. 126(C).
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