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Multidimensional indicators to identify emerging technologies: Perspective of technological knowledge flow

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  • Jiang, Man
  • Yang, Siluo
  • Gao, Qiang

Abstract

The identification of emerging technologies (ETs) is pivotal for advancing technological innovation. However, current methods fail to sufficiently clarify ETs' innovation mechanisms and lack a consistent perspective to integrate the five attributes proposed by Rotolo. This paper presents an innovative term-level framework to identify and comprehend ETs through the perspective of technological knowledge flow (TKF). By dissecting TKF comprehensively, encompassing aspects of knowledge absorption, growth, and diffusion, we construct and explicate multidimensional indicators reflective of ETs' attributes, including relatively rapid growth, radical novelty, coherence, prominent impact, as well as uncertainty and ambiguity. Through the analysis of digital medical patent dataset, our framework proves effective in assessing emergent scores and pinpointing ETs with specificity at the term level, clarifying their technological components and efficacy. This is beneficial for technology developers to overcome technical difficulties and strategic decision makers to manage IP for competitive advantage.

Suggested Citation

  • Jiang, Man & Yang, Siluo & Gao, Qiang, 2024. "Multidimensional indicators to identify emerging technologies: Perspective of technological knowledge flow," Journal of Informetrics, Elsevier, vol. 18(1).
    • Handle: RePEc:eee:infome:v:18:y:2024:i:1:s1751157723001086
    DOI: 10.1016/j.joi.2023.101483
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    References listed on IDEAS

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