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Interdisciplinary knowledge combinations and emerging technological topics: Implications for reducing uncertainties in research evaluation
[Blade Runner Economics: Will Innovation Lead the Economic Recovery?]

Author

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  • Seokbeom Kwon
  • Jan Youtie
  • Alan L Porter

Abstract

This article puts forth a new indicator of emerging technological topics as a tool for addressing challenges inherent in the evaluation of interdisciplinary research. We present this indicator and test its relationship with interdisciplinary and atypical research combinations. We perform this test by using metadata of scientific publications in three domains with different interdisciplinarity challenges: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. Our analysis supports the connection between technological emergence and interdisciplinarity and atypicality in knowledge combinations. We further find that the contributions of interdisciplinary and atypical knowledge combinations to addressing emerging technological topics increase or stay constant over time. Implications for policymakers and contributions to the literature on interdisciplinarity and evaluation are provided.

Suggested Citation

  • Seokbeom Kwon & Jan Youtie & Alan L Porter, 2021. "Interdisciplinary knowledge combinations and emerging technological topics: Implications for reducing uncertainties in research evaluation [Blade Runner Economics: Will Innovation Lead the Economic," Research Evaluation, Oxford University Press, vol. 30(1), pages 127-140.
    • Handle: RePEc:oup:rseval:v:30:y:2021:i:1:p:127-140.
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    File URL: http://hdl.handle.net/10.1093/reseval/rvaa029
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    Cited by:

    1. Kwon, Seokbeom, 2022. "Interdisciplinary knowledge integration as a unique knowledge source for technology development and the role of funding allocation," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    2. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.

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