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A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale?

Author

Listed:
  • Stephen F. Carley

    (Georgia Tech
    Search Technology, Inc)

  • Nils C. Newman

    (Search Technology, Inc
    Intelligent Information Services Corporation)

  • Alan L. Porter

    (Georgia Tech
    Search Technology, Inc)

  • Jon G. Garner

    (Search Technology, Inc)

Abstract

This study advances a four-part indicator for technical emergence. While doing so it focuses on a particular class of emergent concepts—those which display the ability to repeatedly maintain an emergent status over multiple time periods. The authors refer to this quality as staying power and argue that those concepts which maintain this ability are deserving of greater attention. The case study we consider consists of 15 subdatatsets within the dye-sensitized solar cell framework. In this study the authors consider the impact technical domain and scale have on the behavior of persistently emergent concepts and test which of these has a greater influence.

Suggested Citation

  • Stephen F. Carley & Nils C. Newman & Alan L. Porter & Jon G. Garner, 2017. "A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 2077-2087, June.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2342-x
    DOI: 10.1007/s11192-017-2342-x
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    References listed on IDEAS

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    1. Lu An & Xia Lin & Chuanming Yu & Xinwen Zhang, 2015. "Measuring and visualizing the contributions of Chinese and American LIS research institutions to emerging themes and salient themes," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1605-1634, December.
    2. Sanjay K. Arora & Alan L. Porter & Jan Youtie & Philip Shapira, 2013. "Capturing new developments in an emerging technology: an updated search strategy for identifying nanotechnology research outputs," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 351-370, April.
    3. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    4. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
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    Citations

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    Cited by:

    1. Burmaoglu, Serhat & Sartenaer, Olivier & Porter, Alan, 2019. "Conceptual definition of technology emergence: A long journey from philosophy of science to science policy," Technology in Society, Elsevier, vol. 59(C).
    2. Serhat Burmaoglu & Olivier Sartenaer & Alan Porter & Munan Li, 2019. "Analysing the theoretical roots of technology emergence: an evolutionary perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 97-118, April.
    3. Woo, Seokkyun & Youtie, Jan & Ott, Ingrid & Scheu, Fenja, 2021. "Understanding the long-term emergence of autonomous vehicles technologies," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    4. Porter, Alan L. & Garner, Jon & Carley, Stephen F. & Newman, Nils C., 2019. "Emergence scoring to identify frontier R&D topics and key players," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 628-643.
    5. Xiaoyu Liu & Alan L. Porter, 2020. "A 3-dimensional analysis for evaluating technology emergence indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 27-55, July.
    6. Wang, Zhinan & Porter, Alan L. & Wang, Xuefeng & Carley, Stephen, 2019. "An approach to identify emergent topics of technological convergence: A case study for 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 723-732.
    7. Porter, Alan L. & Chiavetta, Denise & Newman, Nils C., 2020. "Measuring tech emergence: A contest," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    8. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
    9. Stephen F. Carley & Nils C. Newman & Alan L. Porter & Jon G. Garner, 2018. "An indicator of technical emergence," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 35-49, April.

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