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A 3-dimensional analysis for evaluating technology emergence indicators

Author

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  • Xiaoyu Liu

    (Beijing Institute of Technology)

  • Alan L. Porter

    (Georgia Institute of Technology
    Search Technology, Inc)

Abstract

Technology emergence has become a hot topic in R&D policy and management communities. Various methods of measuring technology emergence have been developed. However, there is little literature discussing how to evaluate the results identified by different methods. This research sharpens a promising Technology Emergence Indicator (TEI) set by assessing alternative formulations on three distinct datasets: Dye-Sensitized Solar Cells, Non-Linear Programming, and Nano-Enabled Drug Delivery. Our TEIs derive from a conceptual foundation including three attributes of emergence: persistence, community, and growth that we systematically address through a 3-dimensional evaluation framework. Comparing TEI behavior through sensitivity analyses shows good robustness for the measures. The TEI serve to distinguish emerging R&D topics in the field under study. They can further be used to identify highly active players publishing on those topics. Importantly, results show that identified emerging terms and topics persist to a strong degree; thus, they serve to predict highly active R&D foci within the technical domain under study.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:124:y:2020:i:1:d:10.1007_s11192-020-03432-6
    DOI: 10.1007/s11192-020-03432-6
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    References listed on IDEAS

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    Cited by:

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    2. Xiaoli Wang & Yun Liu & Lingdi Chen & Yifan Zhang, 2022. "Correlation Monitoring Method and model of Science-Technology-Industry in the AI Field: A Case of the Neural Network," SAGE Open, , vol. 12(4), pages 21582440221, December.
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    4. 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).

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    More about this item

    Keywords

    Technology emergence indicators; Technology forecasting; Emerging technologies; Technology emergence assessment; R&D emergence; Predictive indicators;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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