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A novel three-dimension perspective to explore technology evolution

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  • Munan Li

    (South China University of Technology)

Abstract

In terms of technology evolution pathways, patents, articles and projects are the traditional analytical dimensions, particularly patent analysis. Analysis results based on traditional dimensions are used to present the evolutionary stage based on the theory of the technology life cycle (TLC). However, traditional TLC is insufficient to explain the inner driving force of technology evolution; instead, it just describes the process. Promoting ideality degree, one of evolutionary principles in the framework of Teoriya Resheniya Izobreatatelskikh Zadatch, is combined with patent and article analysis, and then a novel three-dimensional analytical method is introduced. In a case study with one curial material and novel technology, graphene attracted the attention of all types of organizations, but the development prospects of the graphene industry are not clear, and its potential abilities and applications should be deeply explored.

Suggested Citation

  • Munan Li, 2015. "A novel three-dimension perspective to explore technology evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1679-1697, December.
  • Handle: RePEc:spr:scient:v:105:y:2015:i:3:d:10.1007_s11192-015-1591-9
    DOI: 10.1007/s11192-015-1591-9
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    2. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    3. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    4. Mario COCCIA, 2017. "The Fishbone diagram to identify, systematize and analyze the sources of general purpose technologies," Journal of Social and Administrative Sciences, KSP Journals, vol. 4(4), pages 291-303, December.
    5. Chang, Shu-Hao & Fan, Chin-Yuan, 2016. "Identification of the technology life cycle of telematics: A patent-based analytical perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 1-10.
    6. Huang, Ying & Li, Ruinan & Zou, Fang & Jiang, Lidan & Porter, Alan L. & Zhang, Lin, 2022. "Technology life cycle analysis: From the dynamic perspective of patent citation networks," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    7. Li, Munan & Wang, Wenshu & Zhou, Keyu, 2021. "Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    8. Parraguez, Pedro & Škec, Stanko & e Carmo, Duarte Oliveira & Maier, Anja, 2020. "Quantifying technological change as a combinatorial process," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    9. Wang, Chang & Geng, Hongjun & Sun, Rui & Song, Huiling, 2022. "Technological potential analysis and vacant technology forecasting in the graphene field based on the patent data mining," Resources Policy, Elsevier, vol. 77(C).
    10. Li, Munan & Porter, Alan L. & Suominen, Arho & Burmaoglu, Serhat & Carley, Stephen, 2021. "An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

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