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Tracking the evolution of new and emerging S&T via statement-linkages: Vision assessment in molecular machines

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  • Douglas K. R. Robinson

    (University of Twente)

  • Martin Ruivenkamp

    (University of Twente)

  • Arie Rip

    (University of Twente)

Abstract

The past 10 years has seen an explosion of interest for the area of science and technology labelled “nanotechnology.” Although at an early stage, nanotechnology is providing a space for the creation of new alliances and the forging of new ties in many actor arenas, initiated based on promises and high expectations of the fruits that could be harvested from development and investment into nanotechnology. Those trying to characterise the dynamics of emerging ties and networks within this field are faced with a number of complexities which are characteristic of the nanotechnology umbrella term, which covers many technologies, various mixes of disciplines and actors, and ongoing debates about definitions of fields and terminology. In this paper we explore an approach for capturing dynamics of emergence of a particular area of nanotechnology by investigating visions of possible futures in relation to molecular mechanical systems (molecular machines). The focus of this text is to outline an approach used to map and analyse visions in an emerging field by taking as the unit of analysis linkages made in statements in texts, and the agglomeration of linkages around certain nodes. Taking the linkage, rather than node, allows one to probe deeper into the dynamics of emergence at early stages when definitions and meanings of certain words/nodes are in flux and patterns of their use change dramatically over short periods of time. As part of a larger project on single and macromolecular machines we explore the dynamics of visions in the field of molecular machines with the eventual aim to elucidate the shaping strength of visions within nanotechnology.

Suggested Citation

  • Douglas K. R. Robinson & Martin Ruivenkamp & Arie Rip, 2007. "Tracking the evolution of new and emerging S&T via statement-linkages: Vision assessment in molecular machines," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(3), pages 831-858, March.
    • Handle: RePEc:spr:scient:v:70:y:2007:i:3:d:10.1007_s11192-007-0314-2
    DOI: 10.1007/s11192-007-0314-2
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    References listed on IDEAS

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    Cited by:

    1. Can Huang & Ad Notten & Nico Rasters, 2011. "Nanoscience and technology publications and patents: a review of social science studies and search strategies," The Journal of Technology Transfer, Springer, vol. 36(2), pages 145-172, April.
    2. Douglas K. R. Robinson & Lu Huang & Yan Guo & Alan L. Porter, 2013. "Forecasting Innovation Pathways (FIP) for new and emerging science and technologies," Post-Print hal-01070417, HAL.
    3. Xiwen Liu & Xuezhao Wang & Lucheng Lyu & Yanpeng Wang, 2022. "Identifying disruptive technologies by integrating multi-source data," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5325-5351, September.
    4. Rezaeian, M. & Montazeri, H. & Loonen, R.C.G.M., 2017. "Science foresight using life-cycle analysis, text mining and clustering: A case study on natural ventilation," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 270-280.
    5. Morteza Maghrebi & Ali Abbasi & Saeid Amiri & Reza Monsefi & Ahad Harati, 2011. "A collective and abridged lexical query for delineation of nanotechnology publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 15-25, January.
    6. Mario Coccia, 2017. "General purpose technologies in dynamic systems: visual representation and analyses of complex drivers," IRCrES Working Paper 201705, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    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. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    9. Gustafsson, Robin & Kuusi, Osmo & Meyer, Martin, 2015. "Examining open-endedness of expectations in emerging technological fields: The case of cellulosic ethanol," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 179-193.
    10. 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.

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