Research on the identification of disruptive technology topics for future industries – taking the field of quantum communication as an example

Mon, 13 Apr 2026 00:00:00 GMT

Purpose

The purpose of this study is to address the challenges of ambiguous topics and unclear development paths in technological evolution by identifying disruptive technology topics. This work is of strategic significance for nations to proactively plan for and lay out future industries.

Design/methodology/approach

This paper innovatively integrates natural language processing techniques with the latent Dirichlet allocation (LDA) topic model to construct a disruptive technology topic identification framework based on multi-source heterogeneous data. Taking the field of quantum communication as a case study, it selects scholarly papers and patents as heterogeneous data sources and uses multi-dimensional indicators – including topic similarity, novelty and intensity – to identify technology topics.

Findings

The results indicate the following: the complementary fusion of scholarly papers and patent data significantly enhances the comprehensiveness and accuracy of technology theme identification. The classification framework based on theme novelty and intensity effectively distinguishes technical characteristics at different development stages, providing a quantitative basis for optimizing innovation resource allocation. The algorithm-driven theme identification method offers an extensible analytical tool for technological foresight.

Research limitations/implications

Future research on identifying disruptive technological innovations should focus on the dynamic weighted fusion of multi-source data, the precise management of technology life cycles and the balance between quantitative analysis and situational flexibility.

Practical implications

This study provides scientific decision support for the research and development of disruptive technologies.

Originality/value

This study lays a methodological foundation for the strategic layout of future industries by proposing a novel, data-driven framework for technology foresight.

Beyond AI substitution and cultivation of entrepreneurial competencies: a mediation framework based on the SOR model

Mon, 13 Apr 2026 00:00:00 GMT

Purpose

In the era of human–AI symbiosis, artificial intelligence (AI) is increasingly reshaping cognition, knowledge production and labor structures. These transformations, in turn, place growing pressure on higher education institutions to reform entrepreneurship education (EE). This study aims to examine how AI-enabled EE influences students’ entrepreneurial competencies by uncovering the underlying psychological mechanisms that remain resistant to AI substitution.

Design/methodology/approach

Grounded in the Stimulus–Organism–Response (SOR) model, this study explores how AI-enabled EE influences university students’ entrepreneurial competencies. This study conceptualized “AI adoption in higher education (AAHE)” in “entrepreneurship education (EE)” as the stimulus (S), “perceived usefulness (PU)” and “entrepreneurial self-efficacy (ESE)” as organismic states (O) and “entrepreneurial competency (EC)” as the response (R). A sample of 558 undergraduates from Shanghai and Zhejiang, China’s AI hub, was surveyed, and hypotheses were tested by Structural Equation Modeling.

Findings

The empirical results showed AAHE positively predicted EE; AAHE and EE both boosted PU and ESE; and PU and ESE mediated the path to EC. These findings highlight the critical role of psychological mechanisms in translating AI integration into competencies development.

Originality/value

This study makes two key contributions: theoretically, it extends the application of the SOR model to AI-enabled EE and clarifies the mediating mechanisms of PU and ESE; practically, this research provides guidance for higher education institutions to cultivate students’ entrepreneurial competencies by optimizing AI integration.

Asia Pacific Journal of Innovation and Entrepreneurship advanceAccess

Research on the identification of disruptive technology topics for future industries – taking the field of quantum communication as an example

Beyond AI substitution and cultivation of entrepreneurial competencies: a mediation framework based on the SOR model