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Technology opportunity discovery to R&D planning: Key technological performance analysis

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  • Lee, Jeongjin
  • Kim, Changseok
  • Shin, Juneseuk

Abstract

There is a gap between technological opportunities and R&D planning because opportunity information is too broadly defined. Thus, we suggest a method of transforming such technological opportunities into a customized and detailed R&D plan. We identify key information for R&D planning, extract such information from bibliometric data by chunk-based mining, and convert it to a usable form for R&D planning. A systematic analysis of normalized performance gaps, performance structure, R&D feasibility and technological alternatives identified important and feasible target technological performance metrics as well as R&D solutions. Our method can increase the practical value of technological opportunities while reducing the efforts required of experts.

Suggested Citation

  • Lee, Jeongjin & Kim, Changseok & Shin, Juneseuk, 2017. "Technology opportunity discovery to R&D planning: Key technological performance analysis," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 53-63.
    • Handle: RePEc:eee:tefoso:v:119:y:2017:i:c:p:53-63
    DOI: 10.1016/j.techfore.2017.03.011
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    Citations

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    Cited by:

    1. Richarz, Jan & Wegewitz, Stephan & Henn, Sarah & Müller, Dirk, 2023. "Graph-based research field analysis by the use of natural language processing: An overview of German energy research," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    2. Lijie Feng & Yuxiang Niu & Zhenfeng Liu & Jinfeng Wang & Ke Zhang, 2019. "Discovering Technology Opportunity by Keyword-Based Patent Analysis: A Hybrid Approach of Morphology Analysis and USIT," Sustainability, MDPI, vol. 12(1), pages 1-35, December.
    3. Yoon, Byungun & Magee, Christopher L., 2018. "Exploring technology opportunities by visualizing patent information based on generative topographic mapping and link prediction," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 105-117.
    4. Ma, Tingting & Zhou, Xiao & Liu, Jia & Lou, Zhenkai & Hua, Zhaoting & Wang, Ruitao, 2021. "Combining topic modeling and SAO semantic analysis to identify technological opportunities of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    5. Xuan Shi & Lingfei Cai & Hongfang Song, 2019. "Discovering Potential Technology Opportunities for Fuel Cell Vehicle Firms: A Multi-Level Patent Portfolio-Based Approach," Sustainability, MDPI, vol. 11(22), pages 1-22, November.
    6. Arash Rezazadeh & Ana Carvalho, 2018. "Towards a survival capabilities framework: Lessons from the Portuguese Textile and Clothing industry," NIPE Working Papers 14/2018, NIPE - Universidade do Minho.
    7. Kyuwoong Kim & Kyeongmin Park & Sungjoo Lee, 2019. "Investigating technology opportunities: the use of SAOx analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 45-70, January.
    8. Jing Ma & Yaohui Pan & Chih-Yi Su, 2022. "Organization-oriented technology opportunities analysis based on predicting patent networks: a case of Alzheimer’s disease," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5497-5517, September.
    9. Lee, MyoungHoon & Kim, Suhyeon & Kim, Hangyeol & Lee, Junghye, 2022. "Technology Opportunity Discovery using Deep Learning-based Text Mining and a Knowledge Graph," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    10. Rachel A Archer & Ritika Kapoor & Wanrudee Isaranuwatchai & Yot Teerawattananon & Birgitte Giersing & Siobhan Botwright & Jos Luttjeboer & Raymond C W Hutubessy, 2020. "‘It takes two to tango’: Bridging the gap between country need and vaccine product innovation," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-11, June.
    11. Tadeusz A. Grzeszczyk & Michal K. Grzeszczyk, 2021. "Improving the Discovery of Technological Opportunities Using Patent Classification Based on Explainable Neural Networks," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 402-409.
    12. Choi, Jaewoong & Lee, Changyong & Yoon, Janghyeok, 2023. "Exploring a technology ecology for technology opportunity discovery: A link prediction approach using heterogeneous knowledge graphs," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    13. Jinzhu Zhang & Wenqian Yu, 2020. "Early detection of technology opportunity based on analogy design and phrase semantic representation," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 551-576, October.
    14. Choi, Jaewoong & Jeong, Byeongki & Yoon, Janghyeok, 2019. "Technology opportunity discovery under the dynamic change of focus technology fields: Application of sequential pattern mining to patent classifications," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    15. Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.

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