The Sustainable Innovation of AI: Text Mining the Core Capabilities of Researchers in the Digital Age of Industry 4.0

Sustainable innovation in the field of artificial intelligence (AI) is essential for the development of Industry 4.0. Recognizing the innovation abilities of researchers is fundamental to achieving sustainable innovation within organizations. This study proposes a method for identifying the core innovative competency field of researchers through text mining, which involves the extraction of core competency tags, topic clustering, and calculating the relevance between researchers and topics. Using AI as a case study, the research identifies the core innovative competency field of researchers, uncovers opportunities for sustainable innovation, and highlights key innovators. This approach offers deeper insights for AI R&D activities, providing effective support for promoting sustainable innovation. Compared to traditional expertise identification methods, this approach provides a more in-depth and detailed portrayal of researchers’ expertise, particularly highlighting potential innovation domains with finer granularity. It is less influenced by subjective factors and can be conveniently applied to identify the core innovative competency field of researchers in any other research field, making it especially suitable for interdisciplinary areas. By offering a precise and comprehensive understanding of researchers’ capability fields, this method enhances the strategic planning and execution of innovative projects, ensuring that organizations can effectively leverage the expertise of their researchers to drive forward sustainable innovation.

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Publication Details

Journal
Sustainability
Published
2024-09-06
DOI
https://doi.org/10.3390/su16177767
Primary Topic
Expert finding and Q&A systems
Type
article
Field-Weighted Citation Impact
0.00

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article

The Sustainable Innovation of AI: Text Mining the Core Capabilities of Researchers in the Digital Age of Industry 4.0

Ran Cui, Fang Han, Shengtai Zhang, Yajun Ji et al.
Sustainability
Expert finding and Q&A systems
article

The Sustainable Innovation of AI: Text Mining the Core Capabilities of Researchers in the Digital Age of Industry 4.0

Ran Cui, Fang Han, Shengtai Zhang, Yajun Ji, Tao Jiang
article en

Abstract

Sustainable innovation in the field of artificial intelligence (AI) is essential for the development of Industry 4.0. Recognizing the innovation abilities of researchers is fundamental to achieving sustainable innovation within organizations. This study proposes a method for identifying the core innovative competency field of researchers through text mining, which involves the extraction of core competency tags, topic clustering, and calculating the relevance between researchers and topics. Using AI as a case study, the research identifies the core innovative competency field of researchers, uncovers opportunities for sustainable innovation, and highlights key innovators. This approach offers deeper insights for AI R&D activities, providing effective support for promoting sustainable innovation. Compared to traditional expertise identification methods, this approach provides a more in-depth and detailed portrayal of researchers’ expertise, particularly highlighting potential innovation domains with finer granularity. It is less influenced by subjective factors and can be conveniently applied to identify the core innovative competency field of researchers in any other research field, making it especially suitable for interdisciplinary areas. By offering a precise and comprehensive understanding of researchers’ capability fields, this method enhances the strategic planning and execution of innovative projects, ensuring that organizations can effectively leverage the expertise of their researchers to drive forward sustainable innovation.

SustainabilityVol. 16(17)
Beijing University of Posts and Telecommunications (CN), National Science Library (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 77%
Expert finding and Q&A systems
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