Mapping the Intellectual Structure and Global Research Landscape of Digital Twin Technology: A Citation-Based Scientometric Analysis

Abstract

The proposed research paper will chart the intellectual authority and the research landscape on Digital Twin technology (DTT) through giving necessary trends, actors, and theme advancements. A citation-based scientometric analysis was conducted using 12,843 articles in the Web of Science Core Collection (1968 to 2025). Patterns and relationships would be visualised using bibliometric methods, including citation, co-citation, and collaboration networks, with VOSviewer and Biblioshiny. The results show that Digital Twin research grew exponentially in 2020 due to the emergence of Industry 4.0, the Internet of Things, and data analytics. Some of the major fields of study include smart manufacturing, predictive maintenance, and sustainability. It is a very interdisciplinary field whose work has been greatly facilitated through strong international partnerships with China, Europe, and the USA at the lead. The citation network uncovers a hub of leading authors and original research contributing to the field, and also revitalizing research. In this paper, the Digital Twin research ecosystem is provided with a strong, integrated overview that integrates multiple dimensions of scientometry. It offers profound insights into research trends and the body of knowledge and further identifies gaps in interdisciplinary and sustainability-related research.