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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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    1. Campbell, Richard S., 1983. "Patent trends as a technological forecasting tool," World Patent Information, Elsevier, vol. 5(3), pages 137-143.
    2. Yongtae Park & Sungjoo Lee & Sora Lee, 2012. "Patent analysis for promoting technology transfer in multi-technology industries: the Korean aerospace industry case," The Journal of Technology Transfer, Springer, vol. 37(3), pages 355-374, June.
    3. Xiao Zhou & Yi Zhang & Alan L. Porter & Ying Guo & Donghua Zhu, 2014. "A patent analysis method to trace technology evolutionary pathways," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 705-721, September.
    4. Taylor, Margaret & Taylor, Andrew, 2012. "The technology life cycle: Conceptualization and managerial implications," International Journal of Production Economics, Elsevier, vol. 140(1), pages 541-553.
    5. Huang, Lu & Zhang, Yi & Guo, Ying & Zhu, Donghua & Porter, Alan L., 2014. "Four dimensional Science and Technology planning: A new approach based on bibliometrics and technology roadmapping," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 39-48.
    6. David Roessner & Alan L. Porter & Nancy J. Nersessian & Stephen Carley, 2013. "Validating indicators of interdisciplinarity: linking bibliometric measures to studies of engineering research labs," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 439-468, February.
    7. Carvalho, M.M. & Fleury, André & Lopes, Ana Paula, 2013. "An overview of the literature on technology roadmapping (TRM): Contributions and trends," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1418-1437.
    8. Haupt, Reinhard & Kloyer, Martin & Lange, Marcus, 2007. "Patent indicators for the technology life cycle development," Research Policy, Elsevier, vol. 36(3), pages 387-398, April.
    9. Gao, Lidan & Porter, Alan L. & Wang, Jing & Fang, Shu & Zhang, Xian & Ma, Tingting & Wang, Wenping & Huang, Lu, 2013. "Technology life cycle analysis method based on patent documents," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 398-407.
    10. Cui Huang & Jun Su & Xiang Xie & Xuanting Ye & Zhang Li & Alan Porter & Jiang Li, 2015. "A bibliometric study of China’s science and technology policies: 1949–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1521-1539, February.
    11. Basberg, Bjorn L., 1987. "Patents and the measurement of technological change: A survey of the literature," Research Policy, Elsevier, vol. 16(2-4), pages 131-141, August.
    12. Raymond Vernon, 1966. "International Investment and International Trade in the Product Cycle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 80(2), pages 190-207.
    13. Yi Zhang & Xiao Zhou & Alan L. Porter & Jose M. Vicente Gomila & An Yan, 2014. "Triple Helix innovation in China’s dye-sensitized solar cell industry: hybrid methods with semantic TRIZ and technology roadmapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 55-75, April.
    14. Wolfgang Glänzel & Ping Zhou, 2011. "Publication activity, citation impact and bi-directional links between publications and patents in biotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 505-525, February.
    15. Yuniol Alvarez-Betancourt & Miguel Garcia-Silvente, 2014. "An overview of iris recognition: a bibliometric analysis of the period 2000–2012," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 2003-2033, December.
    16. Fu-ying Zhang & Yan-shen Xu, 2007. "Research on technical strategy for new product development based on TRIZ evolution theory," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 4(1/2), pages 96-108.
    17. Thanh-Dong Pham & Byeong-Kyu Lee & Chi Hyeon Lee & Minh Viet Nguyen, 2015. "Emission Control Technology," Chapters, in: Farhad Nejadkoorki (ed.), Current Air Quality Issues, IntechOpen.
    18. Jeong, Do-Heon & Song, Min, 2014. "Time gap analysis by the topic model-based temporal technique," Journal of Informetrics, Elsevier, vol. 8(3), pages 776-790.
    19. Mohsen Bahmani-Oskooee & Artatrana Ratha, 2008. "S-Curve at the industry level: evidence from US–UK commodity trade," Empirical Economics, Springer, vol. 35(1), pages 141-152, August.
    20. Gort, Michael & Klepper, Steven, 1982. "Time Paths in the Diffusion of Product Innovations," Economic Journal, Royal Economic Society, vol. 92(367), pages 630-653, September.
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    Cited by:

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    2. Munan Li & Alan L. Porter, 2018. "Facilitating the discovery of relevant studies on risk analysis for three-dimensional printing based on an integrated framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 277-300, January.
    3. 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).
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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).
    9. 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.
    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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