Bibliometric Analysis of Digital Twin Technology - Loso Judijanto (Westscience Press, 2026)
Digital twin technology has emerged as a transformative innovation that enables the creation of virtual representations of physical systems, facilitating real-time monitoring, simulation, optimization, and decision-making across various domains. Given the rapid growth of scholarly interest in this field, a comprehensive understanding of its intellectual structure and research evolution is needed. This study aims to map the global research landscape of digital twin technology through a bibliometric analysis of publications indexed in the Scopus database. Bibliometric techniques were employed to examine publication trends, influential authors, institutions, countries, highly cited documents, collaboration networks, and keyword co-occurrence patterns. The analysis was conducted using VOSviewer to visualize scientific relationships and emerging research themes. The results indicate a substantial increase in digital twin research, particularly after the widespread adoption of Industry 4.0 initiatives. Keyword analysis identifies digital twin as the central research theme, strongly associated with artificial intelligence, Internet of Things, machine learning, smart manufacturing, sustainability, and decision-making. Overlay visualization reveals that recent studies increasingly focus on predictive analytics, energy efficiency, and sustainable development, while density analysis highlights artificial intelligence and IoT as dominant supporting technologies. Country collaboration analysis shows that China, the United States, and several European nations are the leading contributors to the field, whereas citation analysis demonstrates the significant influence of foundational conceptual and review studies. The findings suggest that digital twin technology is evolving toward more intelligent, interconnected, and sustainability-oriented applications. This study contributes to the literature by providing a comprehensive overview of the development, knowledge structure, and future research directions of digital twin technology.