Exploring digital twin in sustainable development: a scientometric analysis

Exploring digital twin in sustainable development: a scientometric analysis

연구 분야: Software Development

학회: International Journal of Data Science and Analytics

Digital Twin (DT) technology has become a pivotal component of Industry 4.0, offering virtual representations of physical systems, processes, and assets. While DT has seen extensive adoption across various industries, a comprehensive understanding of its applications within the framework of Sustainable Development Goals (SDGs) remains underexplored. The study addresses this gap by employing CiteSpace and VOSviewer to perform a scientometric analysis of DT’s evolution and impact across Environmental (1327 records), Social (1016 records), Economic (933 records), and the Partnership-oriented (164 records) SDGs. By analysing data from Scopus (2017–2025) through Publication Pattern Analysis, Citation Pattern Analysis, Document Co-citation Analysis, Keyword Co-occurrence Analysis, Country Collaboration Analysis, and Author Co-citation Network Analysis, the research identifies emerging trends, key research domains, and opportunities for interdisciplinary collaboration. The findings provide valuable insights into DT’s contributions to SDGs and its potential to drive industrial transformation.