The Sustainable Innovation of AI: Text Mining the Core Capabilities of Researchers in the Digital Age of Industry 4.0
Year: 2024
Type: article
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.
Source: Sustainability
DOI: 10.3390/su16177767
Authors: Yajun Ji, Shengtai Zhang, Fang Han, Ran Cui, Tao Jiang
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,728
Award: 移动社交网络微信的知识传播机理研究
OpenAlex ID: W4402315871
