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科学技術政策における非連続イノベーションの評価：メタサイエンス研究の動向から
Evaluation of Discontinuous Innovation in Science and Technology Policy: Trends in Metascience Research
Research Institute of Economy, Trade and Industry | Local Language | AcademicThink | July 8, 2025 | UndeterminedTech Development/Adoption
Discontinuous innovation plays a critical role in driving economic growth and reshaping industrial and market structures. Early identification and objective evaluation of such innovations are key challenges for science and technology policy. Recent advances in metascience use quantitative methods, including big data analysis, to assess the disruptive potential of scientific papers. The Disruption Index (D-Index), developed in 2019, quantifies how a paper changes citation networks by distinguishing whether it initiates new flows or deepens existing ones. Papers with high D-Index scores are considered disruptive, while those with low scores are viewed as developmental.
A 2025 study analyzing 49 million documents up to 2024 validated the Disruption Index against expert assessments, confirming its effectiveness in identifying groundbreaking research. Notable examples include Watson & Crick’s DNA structure paper (D=0.96) and Mandelbrot’s fractals (D=0.95). In Japan, widely cited works such as Akaike’s paper on the Akaike Information Criterion show high citation counts but moderate or low disruption scores, indicating developmental rather than disruptive impact. Conversely, Fujishima’s research on photocatalysts exhibits the highest D-Index among Japanese papers (D=0.998), suggesting significant novelty despite lower citation counts for some highly disruptive works.
Because the Disruption Index relies on subsequent citations, it is limited in assessing recent publications. To overcome this, novelty metrics have been developed that compare current papers to prior literature based on new combinations of cited fields, unusual pairings of fields or vocabulary, and novel word pairs in abstracts. These approaches aim to capture unprecedented ideas early in the research cycle.
Quantitative metascience methods offer policymakers tools to identify discontinuous innovation and guide resource allocation and risk assessment. Initiatives like the UK Research and Innovation’s Metascience Novelty Indicators Challenge demonstrate growing interest in developing and applying such indicators. However, the article stresses the importance of integrating quantitative metrics with qualitative judgment given the inherent limitations of these tools and the complexity of capturing emerging technological trends solely through literature analysis. Ongoing international collaboration and validation remain essential for refining science and technology policy frameworks.