Technological Forecasting and Social Change· 2026Q1
Discovering early signals of technological opportunities: Insights from interdisciplinary innovation
- 0citations
- Q1SCImago
- 2026year
Short summary
A new framework identifies emerging interdisciplinary topics and their innovation potential by analyzing multidimensional knowledge networks from scientific publications, successfully detecting early signals of technological opportunities in rice genetic improvement.
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Key points
- Proposes a framework to identify potential interdisciplinary topics and assess their innovation characteristics.
- Constructs a multidimensional knowledge network from scientific publications to analyze disciplinary structures.
- Utilizes bibliometric and social network analysis to measure innovation characteristics during dynamic evolution.
- Empirically validates the method's capacity to detect early signals of technological opportunities in rice genetic improvement.
AI-generated from the title and abstract; the full text is not read.
Abstract
Interdisciplinary research is important for achieving original scientific innovation. As a carrier of knowledge advancement, scientific literature records the early stages of the integration process, providing a critical data source for identifying early signals of technological opportunities. This paper proposes a theory-driven analytical framework that identifies potential interdisciplinary topics and assesses their innovation characteristics to detect early signals of technological opportunities arising from interdisciplinary integration. The framework begins by constructing a multidimensional knowledge network from scientific publications to clarify disciplinary structures and innovation trajectories. Through analyses of interdisciplinary potential and knowledge integration processes, potential interdisciplinary topics are identified as emerging interdisciplinary foundations for innovation. Building upon these topics, bibliometric and social network analysis methods are used to comprehensively measure multiple innovation characteristics during the dynamic evolution of disciplines. An empirical analysis in the field of rice genetic improvement confirms the feasibility of the proposed method and demonstrates its capacity to identify early signals of technological opportunities. This study enhances the ability to detect such signals and offers valuable insights for researchers and policymakers.
The authors' abstract, as published at the source. Technological Forecasting and Social Change, 2026 · DOI ↗
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Statistics, Probability and UncertaintyDecision Sciences